A two-wheeled single seat Segway robot is a special kind of wheeled mobile robot, using it as a human transporter system needs applying a robust control system to overcome its inherent unstable problem. The mathematical model of the system dynamics is derived and then state space formulation for the system is presented to enable design state feedback controller scheme. In this research, an optimal control system based on linear quadratic regulator (LQR) technique is proposed to stabilize the mobile robot. The LQR controller is designed to control the position and yaw rotation of the two-wheeled vehicle. The proposed balancing robot system is validated by simulating the LQR using Matlab software. Two tuning methods, genetic algorithm (GA) and bacteria foraging optimization algorithm (BFOA) are used to obtain optimal values for controller parameters. A comparison between the performance of both controllers GA-LQR and BFO-LQR is achieved based on the standard control criteria which includes rise time, maximum overshoot, settling time and control input of the system. Simulation results suggest that the BFOA-LQR controller can be adopted to balance the Segway robot with minimal overshoot and oscillation frequency.
Modeling, Simulation, and Optimal Control for Two-Wheeled Self-Balancing Robot IJECEIAES
ย
Two-wheeled self-balancing robot is a popular model in control system experiments which is more widely known as inverted pendulum and cart model. This is a multi-input and multi-output system which is theoretical and has been applied in many systems in daily use. Anyway, most research just focus on balancing this model through try-on experiments or by using simple form of mathematical model. There were still few researches that focus on complete mathematic modeling and designing a mathematical model based controller for such system. This paper analyzed mathematical model of the system. Then, the authors successfully applied a Linear Quadratic Regulator (LQR) controller for this system. This controller was tested with different case of system condition. Controlling results was proved to work well and tested on different case of system condition through simulation on matlab/Simulink program.
Two wheeled self balancing robot for autonomous navigationIAEME Publication
ย
This document summarizes a research paper on the design and testing of a two-wheeled self-balancing robot capable of autonomous navigation. The robot balances using a PID control loop applied to data from an inertial measurement unit. A complementary filter fuses gyroscope and accelerometer readings to estimate the robot's tilt angle in real-time. Autonomous navigation is achieved using an ultrasonic distance sensor and image processing system to detect obstacles and determine the robot's path. The stability of the balancing system is analyzed using real-time data plotting in MATLAB, allowing tuning of the PID controller constants.
Modeling, Simulation, and Optimal Control for Two-Wheeled Self-Balancing Robot IJECEIAES
ย
Two-wheeled self-balancing robot is a popular model in control system experiments which is more widely known as inverted pendulum and cart model. This is a multi-input and multi-output system which is theoretical and has been applied in many systems in daily use. Anyway, most research just focus on balancing this model through try-on experiments or by using simple form of mathematical model. There were still few researches that focus on complete mathematic modeling and designing a mathematical model based controller for such system. This paper analyzed mathematical model of the system. Then, the authors successfully applied a Linear Quadratic Regulator (LQR) controller for this system. This controller was tested with different case of system condition. Controlling results was proved to work well and tested on different case of system condition through simulation on matlab/Simulink program.
Two wheeled self balancing robot for autonomous navigationIAEME Publication
ย
This document summarizes a research paper on the design and testing of a two-wheeled self-balancing robot capable of autonomous navigation. The robot balances using a PID control loop applied to data from an inertial measurement unit. A complementary filter fuses gyroscope and accelerometer readings to estimate the robot's tilt angle in real-time. Autonomous navigation is achieved using an ultrasonic distance sensor and image processing system to detect obstacles and determine the robot's path. The stability of the balancing system is analyzed using real-time data plotting in MATLAB, allowing tuning of the PID controller constants.
This document summarizes a student project to build a self-balancing robot controlled by a mobile phone using Bluetooth. A group of 6 students from ITM Vocational University developed the robot under faculty guidance. The robot uses an Arduino, gyroscope, accelerometer, motor driver and DC motors. It balances itself using PID control and can be operated remotely from a mobile app connected via Bluetooth. The presentation covers the objectives, components, circuit diagrams, software, advantages and applications of the self-balancing robot.
Walking Control Algorithm of Biped Humanoid Robot on Even, Uneven and Incline...Saraj Sadanand
ย
This document describes a walking control algorithm that allows a biped humanoid robot to walk stably on even, uneven, and inclined surfaces. It first discusses static and dynamic walking methods. It then explains how the algorithm uses zero moment point (ZMP) and center of pressure (COP) to control balance during walking. The algorithm generates walking patterns and uses online controllers to maintain an upright posture and control angular momentum during landing on uneven surfaces through ankle torque control. This allows the robot to adapt its walking to different floor conditions.
The document discusses various kinematic problems in robotics including forward kinematics, inverse kinematics, and Denavit-Hartenberg notation. Forward kinematics determines the pose of the end-effector given the joint angles, while inverse kinematics determines the required joint angles to achieve a desired end-effector pose. Denavit-Hartenberg notation provides a systematic way to describe the geometry of robot links and joints. The document also covers numerical solutions to inverse kinematics for robots without closed-form solutions and kinematics of special robot types like under-actuated and redundant manipulators.
PUMA-560 Robot Manipulator Position Sliding Mode Control Methods Using MATLAB...Waqas Tariq
ย
This paper describes the MATLAB/SIMULINK realization, modeling and implementation of the PUMA 560 robot manipulator. This paper focuses on robot manipulator analysis and implementation and analyzed. This simulation models are developed as a part of a software laboratory to support and enhance graduate robotics courses, and MATLAB/SIMULINK courses at research and development company (SSP Co.) research center, Shiraz, Iran.
1. The document discusses different types of wheels used in mobile robots including fixed wheels, centered orientable wheels, off-centered orientable wheels, and Swedish wheels.
2. It also covers various locomotion methods for mobile wheeled robots including differential drive, tricycle drive, synchronous drive, and Ackerman steering.
3. Kinematics models are presented for different robot configurations to describe the relationship between the robot's motion and control inputs.
Design of fuzzzy pid controller for bldc motorMishal Hussain
ย
This document discusses the design of a fuzzy PID controller for brushless DC motors. It begins by explaining the working of BLDC motors and how their current direction is electronically controlled without a commutator. It then discusses the need for controllers to improve characteristics like rise time, overshoot, settling time and steady state error. While conventional PID controllers can control systems, they perform poorly for non-linear systems. Fuzzy logic control is introduced as a better method that uses linguistic variables and fuzzy rules. The document outlines the design of a fuzzy PID controller and shows through simulations that it reduces overshoot and gives more robust performance compared to a conventional PID controller.
4.2.1. thiแบฟt kแบฟ bแป ฤiแปu khiแปn trฦฐแปฃt cho robot 2 bแบญc tแปฑ do vร mรด phแปng trรชn ma...TรI LIแปU NGรNH MAY
ย
ฤแป xem full tร i liแปu Xin vui long liรชn hแป page ฤแป ฤฦฐแปฃc hแป trแปฃ
: https://www.facebook.com/thuvienluanvan01
HOแบถC
https://www.facebook.com/garmentspace/
https://www.facebook.com/thuvienluanvan01
https://www.facebook.com/thuvienluanvan01
tai lieu tong hop, thu vien luan van, luan van tong hop, do an chuyen nganh
1. The document discusses the state estimation, locomotion, kinematics, dynamics, and control of quadruped robots. It focuses on the ANYmal robot from ETH Zurich as a key example.
2. Key topics covered include the use of an extended Kalman filter for state estimation, the inverse kinematics and dynamics challenges of quadruped robots, and approaches for support consistent inverse kinematics and dynamics that respect contact constraints.
3. The document provides an overview of concepts for quadruped control, including kinematic control, impedance control, inverse dynamics control, and whole-body control through simultaneous optimization of posture, contact forces and joint torques.
Control system concepts by using matlabCharltonInao1
ย
This document introduces control system concepts and how they can be analyzed using MATLAB. It discusses open and closed loop systems, Laplace transforms, state variable approaches, and MATLAB commands to analyze systems. Examples are provided on determining transfer functions, computing step and frequency responses, plotting root loci and Bode diagrams, and performing time and frequency domain analyses. Block diagrams can be reduced and overall transfer functions obtained through series and parallel combinations.
1) An LQR controller with feedforward control and steady state error tracking was designed and simulated to control an inverted pendulum system.
2) The LQR controller stabilized the unstable system and achieved good performance for the pendulum angle and cart position with minimal overshoot and steady state error.
3) Simulation results demonstrated the robustness of the designed controller under system uncertainties, showing improved performance over existing H-infinity control methods.
Industrial robots were first developed in the 1950s and have since been used widely in factory automation. An industrial robot typically consists of a controller, robotic arm, end effector, drive system, and sensors. The controller acts as the robot's brain and allows its parts to operate together through programmed instructions. Robots provide benefits such as increased efficiency, higher product quality, improved worker safety, and longer working hours compared to humans. However, robots also have disadvantages like high initial capital costs, requiring expertise to program and operate, and some limitations in the tasks they can perform. Overall, robots can help improve manufacturing productivity if implemented as part of a well-integrated automated system.
Path tracking control of differential drive mobile robot based on chaotic-bi...IJECEIAES
ย
This summary provides the key details about the document in 3 sentences:
The document presents a new chaotic-billiards optimizer (C-BO) algorithm to optimize the parameters of a controller for a differential-drive mobile robot. The C-BO algorithm is used to tune the controller parameters to improve path tracking performance. Simulation results show that the C-BO algorithm achieves better path tracking accuracy compared to an ant colony optimization algorithm, with a steady state error of 0.6% versus 0.8%.
Intelligent swarm algorithms for optimizing nonlinear sliding mode controller...IJECEIAES
ย
This document describes research into using intelligent swarm algorithms to optimize the parameters of a nonlinear sliding mode controller for a robot manipulator. Specifically, particle swarm optimization and social spider optimization were used to determine optimal values for the parameters of an integral sliding mode controller designed to control a 6 degree-of-freedom PUMA robot manipulator. Simulation results showed that social spider optimization achieved the best fitness value and performance in minimizing error for the robot controller parameters.
This document summarizes a student project to build a self-balancing robot controlled by a mobile phone using Bluetooth. A group of 6 students from ITM Vocational University developed the robot under faculty guidance. The robot uses an Arduino, gyroscope, accelerometer, motor driver and DC motors. It balances itself using PID control and can be operated remotely from a mobile app connected via Bluetooth. The presentation covers the objectives, components, circuit diagrams, software, advantages and applications of the self-balancing robot.
Walking Control Algorithm of Biped Humanoid Robot on Even, Uneven and Incline...Saraj Sadanand
ย
This document describes a walking control algorithm that allows a biped humanoid robot to walk stably on even, uneven, and inclined surfaces. It first discusses static and dynamic walking methods. It then explains how the algorithm uses zero moment point (ZMP) and center of pressure (COP) to control balance during walking. The algorithm generates walking patterns and uses online controllers to maintain an upright posture and control angular momentum during landing on uneven surfaces through ankle torque control. This allows the robot to adapt its walking to different floor conditions.
The document discusses various kinematic problems in robotics including forward kinematics, inverse kinematics, and Denavit-Hartenberg notation. Forward kinematics determines the pose of the end-effector given the joint angles, while inverse kinematics determines the required joint angles to achieve a desired end-effector pose. Denavit-Hartenberg notation provides a systematic way to describe the geometry of robot links and joints. The document also covers numerical solutions to inverse kinematics for robots without closed-form solutions and kinematics of special robot types like under-actuated and redundant manipulators.
PUMA-560 Robot Manipulator Position Sliding Mode Control Methods Using MATLAB...Waqas Tariq
ย
This paper describes the MATLAB/SIMULINK realization, modeling and implementation of the PUMA 560 robot manipulator. This paper focuses on robot manipulator analysis and implementation and analyzed. This simulation models are developed as a part of a software laboratory to support and enhance graduate robotics courses, and MATLAB/SIMULINK courses at research and development company (SSP Co.) research center, Shiraz, Iran.
1. The document discusses different types of wheels used in mobile robots including fixed wheels, centered orientable wheels, off-centered orientable wheels, and Swedish wheels.
2. It also covers various locomotion methods for mobile wheeled robots including differential drive, tricycle drive, synchronous drive, and Ackerman steering.
3. Kinematics models are presented for different robot configurations to describe the relationship between the robot's motion and control inputs.
Design of fuzzzy pid controller for bldc motorMishal Hussain
ย
This document discusses the design of a fuzzy PID controller for brushless DC motors. It begins by explaining the working of BLDC motors and how their current direction is electronically controlled without a commutator. It then discusses the need for controllers to improve characteristics like rise time, overshoot, settling time and steady state error. While conventional PID controllers can control systems, they perform poorly for non-linear systems. Fuzzy logic control is introduced as a better method that uses linguistic variables and fuzzy rules. The document outlines the design of a fuzzy PID controller and shows through simulations that it reduces overshoot and gives more robust performance compared to a conventional PID controller.
4.2.1. thiแบฟt kแบฟ bแป ฤiแปu khiแปn trฦฐแปฃt cho robot 2 bแบญc tแปฑ do vร mรด phแปng trรชn ma...TรI LIแปU NGรNH MAY
ย
ฤแป xem full tร i liแปu Xin vui long liรชn hแป page ฤแป ฤฦฐแปฃc hแป trแปฃ
: https://www.facebook.com/thuvienluanvan01
HOแบถC
https://www.facebook.com/garmentspace/
https://www.facebook.com/thuvienluanvan01
https://www.facebook.com/thuvienluanvan01
tai lieu tong hop, thu vien luan van, luan van tong hop, do an chuyen nganh
1. The document discusses the state estimation, locomotion, kinematics, dynamics, and control of quadruped robots. It focuses on the ANYmal robot from ETH Zurich as a key example.
2. Key topics covered include the use of an extended Kalman filter for state estimation, the inverse kinematics and dynamics challenges of quadruped robots, and approaches for support consistent inverse kinematics and dynamics that respect contact constraints.
3. The document provides an overview of concepts for quadruped control, including kinematic control, impedance control, inverse dynamics control, and whole-body control through simultaneous optimization of posture, contact forces and joint torques.
Control system concepts by using matlabCharltonInao1
ย
This document introduces control system concepts and how they can be analyzed using MATLAB. It discusses open and closed loop systems, Laplace transforms, state variable approaches, and MATLAB commands to analyze systems. Examples are provided on determining transfer functions, computing step and frequency responses, plotting root loci and Bode diagrams, and performing time and frequency domain analyses. Block diagrams can be reduced and overall transfer functions obtained through series and parallel combinations.
1) An LQR controller with feedforward control and steady state error tracking was designed and simulated to control an inverted pendulum system.
2) The LQR controller stabilized the unstable system and achieved good performance for the pendulum angle and cart position with minimal overshoot and steady state error.
3) Simulation results demonstrated the robustness of the designed controller under system uncertainties, showing improved performance over existing H-infinity control methods.
Industrial robots were first developed in the 1950s and have since been used widely in factory automation. An industrial robot typically consists of a controller, robotic arm, end effector, drive system, and sensors. The controller acts as the robot's brain and allows its parts to operate together through programmed instructions. Robots provide benefits such as increased efficiency, higher product quality, improved worker safety, and longer working hours compared to humans. However, robots also have disadvantages like high initial capital costs, requiring expertise to program and operate, and some limitations in the tasks they can perform. Overall, robots can help improve manufacturing productivity if implemented as part of a well-integrated automated system.
Path tracking control of differential drive mobile robot based on chaotic-bi...IJECEIAES
ย
This summary provides the key details about the document in 3 sentences:
The document presents a new chaotic-billiards optimizer (C-BO) algorithm to optimize the parameters of a controller for a differential-drive mobile robot. The C-BO algorithm is used to tune the controller parameters to improve path tracking performance. Simulation results show that the C-BO algorithm achieves better path tracking accuracy compared to an ant colony optimization algorithm, with a steady state error of 0.6% versus 0.8%.
Intelligent swarm algorithms for optimizing nonlinear sliding mode controller...IJECEIAES
ย
This document describes research into using intelligent swarm algorithms to optimize the parameters of a nonlinear sliding mode controller for a robot manipulator. Specifically, particle swarm optimization and social spider optimization were used to determine optimal values for the parameters of an integral sliding mode controller designed to control a 6 degree-of-freedom PUMA robot manipulator. Simulation results showed that social spider optimization achieved the best fitness value and performance in minimizing error for the robot controller parameters.
IRJET- Design and Fabrication of PLC and SCADA based Robotic Arm for Material...IRJET Journal
ย
This document describes the design and fabrication of a PLC and SCADA-controlled robotic arm for material handling. The robotic arm uses pneumatic cylinders connected by joints to move along three axes (X, Y, and Z). A mechanical gripper is attached to the end of the arm to grip objects on a conveyor belt. The movements of the pneumatic cylinders and gripper are controlled by a PLC based on sensor inputs from the conveyor belt. The PLC and robotic arm are integrated with a SCADA system for centralized control and monitoring. The robotic arm is intended to automate repetitive picking and placing tasks to reduce labor costs compared to manual operations.
Fractional order PID for tracking control of a parallel robotic manipulator t...ISA Interchange
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This paper presents the tracking control for a robotic manipulator type delta employing fractional order PID controllers with computed torque control strategy. It is contrasted with an integer order PID controller with computed torque control strategy. The mechanical structure, kinematics and dynamic models of the delta robot are descripted. A SOLIDWORKS/MSC-ADAMS/MATLAB co-simulation model of the delta robot is built and employed for the stages of identi๏ฌcation, design, and validation of control strategies. Identi๏ฌcation of the dynamic model of the robot is performed using the least squares algorithm. A linearized model of the robotic system is obtained employing the computed torque control strategy resulting in a decoupled double integrating system. From the linearized model of the delta robot, fractional order PID and integer order PID controllers are designed, analyzing the dynamical behavior for many evaluation trajectories. Controllers robustness is evaluated against external disturbances employing performance indexes for the joint and spatial error, applied torque in the joints and trajectory tracking. Results show that fractional order PID with the computed torque control strategy has a robust performance and active disturbance rejection when it is applied to parallel robotic manipulators on tracking tasks.
Design and Implementation of a Self-Balancing Two-Wheeled Robot Driven by a F...IRJET Journal
ย
This document describes the design and implementation of a self-balancing two-wheeled robot controlled by a feed-forward backpropagation neural network. The robot uses an Arduino, gyroscope, accelerometer, and two DC motors. Two control approaches are tested: a PID controller and a feed-forward neural network trained using backpropagation. Testing found the neural network approach learned to balance with fewer oscillations and was more elegant than the PID controller. The neural network demonstrated the effectiveness of artificial intelligence for complex learning tasks.
This document describes the development of a pick and place robot using a programmable logic controller (PLC) as the controller. The robot has four degrees of freedom and is designed to accurately locate and grip objects in a customized workspace. The author details the mechanical and electrical design of the robot, including the 3D printed links and joints, PLC and motor control circuitry, and sensors. Simulation results are presented showing the robot can successfully operate within its load capacity to grip and move objects as intended.
A two-wheeled self-balancing robot (TWSBR) is an underactuated system that
is inherently nonlinear and unstable. While many control methods have been
introduced to enhance the performance, there is no unique solution when it comes to hardware implementation as the robotโs stability is highly dependent on accuracy of sensors and robustness of the electronic control systems. In
this study, a TWSBR that is controlled by an embedded NI myRIO-1900 board with LabVIEW-based control scheme is developed. We compare the performance between proportional-integral-derivative (PID) and linear quadratic regulator (LQR) schemes which are designed based on the TWSBRโs model that
is constructed from Newtonian principles. A hybrid PID-LQR scheme is then proposed to compensate for the individual componentsโ limitations. Experimental results demonstrate the PID is more effective at regulating the tilt angle of the robot in the presence of external disturbances, but it necessitates a higher velocity to sustain its equilibrium. The LQR on the other hand outperforms PID
in terms of maximum initial tilt angle. By combining both schemes, significant
improvements can be observed, such as an increase in maximum initial tilt angle
and a reduction in settling time.
Model Validation and Control of an In-Wheel DC Motor Prototype for Hybrid El...Scientific Review SR
ย
In this paper, a mathematical model and a controller for a DC motor are developed for the
construction of an in-wheel motor. In-wheel motors can be used in hybrid electric vehicles to provide traction
force of front or rear wheels. The model identification is achieved using a simple and low cost data acquisition
system. An Arduino Uno embedded board system is used to collect data from sensors to a computer and for
control purposes. Data processing is performed using Matlab/Simulink. Validations of the devel oped
mathematical model and controller performance are carried out by comparing simulation and experimental results.
The results obtained show that the mathematical model is accurate enough to assist in speed controller design and
implementation.
Mathematical modeling and kinematic analysis of 5 degrees of freedom serial l...IJECEIAES
ย
Modeling and kinematic analysis are crucial jobs in robotics that entail identifying the position of the robotโs joints in order to accomplish particular tasks. This article uses an algebraic approach to model the kinematics of a serial link, 5 degrees of freedom (DOF) manipulator. The analytical method is compared to an optimization strategy known as sequential least squares programming (SLSQP). Using an Intel RealSense 3D camera, the colored object is picked up and placed using vision-based technology, and the pixel location of the object is translated into robot coordinates. The LOBOT LX15D serial bus servo controller was used to transmit these coordinates to the robotic arm. Python3 programming language was used throughout the entire analysis. The findings demonstrated that both analytical and optimized inverse kinematic solutions correctly identified colored objects and positioned them in their appropriate goal points.
Comparative Analysis for NN-Based Adaptive Back-stepping Controller and Back-...IJERA Editor
ย
This work primarily addresses the design and implementation of a neural network based controller for the trajectory tracking of a differential drive mobile robot. The proposed control algorithm is an NN-based adaptive controller which tunes the gains of the back-stepping controller online according to the robot reference trajectory and its initial posture. In this method, a neural network is needed to learn the characteristics of the plant dynamics and make use of it to determine the future inputs that will minimize error performance index so as to compensate the back-stepping controller gains. The advantages and disadvantages of theproposed control algorithms will be discussed in each section with illustrations.Comprehensive system modeling including robot kinematics and dynamics modeling has been done. The dynamic modeling is done using Newtonian and Lagrangian methodologies for nonholonomic systems and the results are compared to verify the accuracy of each method. Simulation of the robot model and different controllers has been done using Matlab and Matlab Simulink.
Evolutionary Design of Mathematical tunable FPGA Based MIMO Fuzzy Estimator S...Waqas Tariq
ย
In this research, a Multi Input Multi Output (MIMO) position Field Programmable Gate Array (FPGA)-based fuzzy estimator sliding mode control (SMC) design with the estimation laws derived in Lyapunov sense and application to robotic manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in sliding mode controller, fuzzy inference methodology and Lyapunov based method, the controllers output has improved. The main target in this research is analyses and design of the position MIMO artificial Lyapunov FPGA-based controller for robot manipulator in order to solve uncertainty, external disturbance, nonlinear equivalent part, chattering phenomenon, time to market and controller size using FPGA. Robot manipulators are nonlinear, time variant and a number of parameters are uncertain therefore design robust and stable controller based on Lyapunov based is discussed in this research. Studies about classical sliding mode controller (SMC) show that: although this controller has acceptable performance with known dynamic parameters such as stability and robustness but there are two important disadvantages as below: chattering phenomenon and mathematical nonlinear dynamic equivalent controller part. The first challenge; nonlinear dynamic part; is applied by inference estimator method in sliding mode controller in order to solve the nonlinear problems in classical sliding mode controller. And the second challenge; chattering phenomenon; is removed by linear method. Asymptotic stability of the closed loop system is also proved in the sense of Lyapunov. In the last part it can find the implementation of MIMO fuzzy estimator sliding mode controller on FPGA; FPGA-based fuzzy estimator sliding mode controller has many advantages such as high speed, low cost, short time to market and small device size. One of the most important drawbacks is limited capacity of available cells which this research focuses to solve this challenge. FPGA can be used to design a controller in a single chip Integrated Circuit (IC). In this research the SMC is designed using Very High Description Language (VHDL) for implementation on FPGA device (XA3S1600E-Spartan-3E), with minimum chattering.
Induction motors are work-horse of the industry and major element in energy conversion. The replacement of the existing non-adjustable speed drives with the modern variable frequency drives would save considerable amount of electricity. A proper control scheme for variable frequency drives can enhance the efficiency and performance of the drive. This paper attempt to provide a rigorous review of various control schemes for the induction motor control and provides critical analysis and guidelines for the future research work. A detailed study of sensor based control schemes and sensor-less control schemes has been investigated. The operation, advantages, and limitations of the various control schemes are highlighted and different types of optimization techniques have been suggested to overcome the limitations of control techniques.
The document describes a solar-powered robotic vehicle called PENTRON that uses a single tiltable solar panel and smart microcontroller to optimally charge its batteries. It reduces weight and power consumption compared to previous models by using a single microcontroller rather than multiple ones, and having two wheels rather than four. The microcontroller monitors power usage and controls the solar panel to obtain maximum charging. It interprets sensor data to efficiently manage charging the two battery packs from the solar panel. The robotic vehicle uses various sensors and a wireless camera that relay environmental data to a PC using ZigBee technology for remote monitoring.
Wheeled robots are often utilized for various remote sensing and telerobotic applications because of their ability to navigate through dynamic environments, mostly under the partial control of a human operator. To make these robots capable to traverse through terrains of rough and uneven topography, their driving mechanisms and controllers must be very efficient at producing and controlling large mechanical power with great precision in real-time, however small the robot may be. This paper discusses an approach for designing a quad-wheeled robot, which is wirelessly controlled with a personal computer (PC) by medium-range radio frequency (RF) transceiver, to navigate through unpaved paths with little or no difficulty. An efficient servo-controlled Ackerman steering mechanism and a high-torque driving power-train were developed. The robotโs controller is programmed to receive and respond to RF control signals from the PC to perform the desired motions. The dynamics of the robotโs drivetrain is modeled and analyzed on MATLAB to predict its performances. The robot was tested on various topographies to determine its physical capabilities. Results show that the robot is capable of non-holonomically constrained motions on rough and uneven terrains.
IRJET- Design & Development of Two-Wheeled Self Balancing RobotIRJET Journal
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This document describes the design and development of a two-wheeled self-balancing robot. An inertial measurement unit (IMU) containing an accelerometer and gyroscope is used to measure the robot's tilt angle. A PID controller applies motor speed adjustments to correct any error between the desired setpoint and actual tilt angle, balancing the robot. The PID controller is able to balance the robot with some limitations. Simulation results are compared to the hardware performance. PID tuning is also performed to improve balancing. Key components include an Arduino, motor driver, motors, IMU, and Bluetooth module. The system architecture integrates these components to enable self-balancing.
Impact analysis of actuator torque degradation on the IRB 120 robot performan...IJECEIAES
ย
Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed speci๏ฌcally for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robotโs responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.
Elevation, pitch and travel axis stabilization of 3DOF helicopter with hybrid...IJECEIAES
ย
This research work introduces an efficient hybrid control methodology through combining the traditional proportional-integral-derivative (PID) controller and linear quadratic regulator (LQR) optimal controlher. The proposed hybrid control approach is adopted to design three degree of freedom (3DOF) stabilizing system for helicopter. The gain parameters of the classic PID controller are determined using the elements of the LQR feedback gain matrix. The dynamic behaviour of the LQR based PID controller, is modeled in state space form to enable utlizing state feedback controller technique. The performance of the proposed LQR based LQR controller is improved by using Genetic Algorithm optimization method which are adopted to obtain optimum values for LQR controller gain parameters. The LQR-PID hybrid controller is simulated using Matlab environment and its performance is evaluated based on rise time, settling time, overshoot and steady state error parameters to validate the proposed 3DOF helicopter balancing system. Based on GA tuning approach, the simulation results suggest that the hybrid LQR-PID controller can be effectively employed to stabilize the 3DOF helicopter system.
PUMA-560 Robot Manipulator Position Computed Torque Control Methods Using MAT...Waqas Tariq
ย
This document describes the implementation of a computed torque controller for controlling the position of a PUMA 560 robot manipulator using MATLAB/Simulink. It first presents the dynamic equations of motion for the PUMA 560 robot. It then provides details on computed torque control, including its mathematical formulation and how it was modeled in Simulink. Simulation results are presented to validate the controller's performance in tracking desired joint positions for the robot.
Modeling and Control of a Spherical Rolling Robot Using Model Reference Adapt...IRJET Journal
ย
The document describes modeling and control of a spherical rolling robot using model reference adaptive control (MRAC). It presents the mathematical model developed for the robot based on its nonholonomic constraints. MRAC is used to control the robot by adjusting controller parameters to minimize the error between the robot's actual output and the output of a reference model for ideal behavior. Simulation results show the proposed MRAC scheme eliminates steady state error and improves transient response without requiring knowledge of the robot's dynamic equations.
African vulture optimizer algorithm based vector control induction motor driv...IJECEIAES
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This study describes a new optimization approach for three-phase induction motor speed drive to minimize the integral square error for speed controller and improve the dynamic speed performance. The new proposed algorithm, African vulture optimizer algorithm (AVOA) optimizes internal controller parameters of a fuzzy like proportional differential (PD) speed controller. The AVOA is notable for its ease of implementation, minimal number of design parameters, high convergence speed, and low computing burden. This study compares fuzzy-like PD speed controllers optimized with AVOA to adaptive fuzzy logic speed regulators, fuzzy-like PD optimized with genetic algorithm (GA), and proportional integral (PI) speed regulators optimized with AVOA to provide speed control for an induction motor drive system. The drive system is simulated using MATLAB/Simulink and laboratory prototype is implemented using DSP-DS1104 board. The results demonstrate that the suggested fuzzy-like PD speed controller optimized with AVOA, with a speed steady state error performance of 0.5% compared to the adaptive fuzzy logic speed regulatorโs 0.7%, is the optimum alternative for speed controller. The results clarify the effectiveness of the controllers based on fuzzy like PD speed controller optimized with AVOA for each performance index as it provides lower overshoot, lowers rising time, and high dynamic response.
Similar to Balancing a Segway robot using LQR controller based on genetic and bacteria foraging optimization algorithms (20)
Amazon products reviews classification based on machine learning, deep learni...TELKOMNIKA JOURNAL
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In recent times, the trend of online shopping through e-commerce stores and websites has grown to a huge extent. Whenever a product is purchased on an e-commerce platform, people leave their reviews about the product. These reviews are very helpful for the store owners and the productโs manufacturers for the betterment of their work process as well as product quality. An automated system is proposed in this work that operates on two datasets D1 and D2 obtained from Amazon. After certain preprocessing steps, N-gram and word embedding-based features are extracted using term frequency-inverse document frequency (TF-IDF), bag of words (BoW) and global vectors (GloVe), and Word2vec, respectively. Four machine learning (ML) models support vector machines (SVM), logistic regression (RF), logistic regression (LR), multinomial Naรฏve Bayes (MNB), two deep learning (DL) models convolutional neural network (CNN), long-short term memory (LSTM), and standalone bidirectional encoder representations (BERT) are used to classify reviews as either positive or negative. The results obtained by the standard ML, DL models and BERT are evaluated using certain performance evaluation measures. BERT turns out to be the best-performing model in the case of D1 with an accuracy of 90% on features derived by word embedding models while the CNN provides the best accuracy of 97% upon word embedding features in the case of D2. The proposed model shows better overall performance on D2 as compared to D1.
Design, simulation, and analysis of microstrip patch antenna for wireless app...TELKOMNIKA JOURNAL
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In this study, a microstrip patch antenna that works at 3.6 GHz was built and tested to see how well it works. In this work, Rogers RT/Duroid 5880 has been used as the substrate material, with a dielectric permittivity of 2.2 and a thickness of 0.3451 mm; it serves as the base for the examined antenna. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. The goal of this study was to get a more extensive transmission capacity, a lower voltage standing wave ratio (VSWR), and a lower return loss, but the main goal was to get a higher gain, directivity, and efficiency. After simulation, the return loss, gain, directivity, bandwidth, and efficiency of the supplied antenna are found to be -17.626 dB, 9.671 dBi, 9.924 dBi, 0.2 GHz, and 97.45%, respectively. Besides, the recreation uncovered that the transfer speed side-lobe level at phi was much better than those of the earlier works, at -28.8 dB, respectively. Thus, it makes a solid contender for remote innovation and more robust communication.
Design and simulation an optimal enhanced PI controller for congestion avoida...TELKOMNIKA JOURNAL
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This document describes using a snake optimization algorithm to tune the gains of an enhanced proportional-integral controller for congestion avoidance in a TCP/AQM system. The controller aims to maintain a stable and desired queue size without noise or transmission problems. A linearized model of the TCP/AQM system is presented. An enhanced PI controller combining nonlinear gain and original PI gains is proposed. The snake optimization algorithm is then used to tune the parameters of the enhanced PI controller to achieve optimal system performance and response. Simulation results are discussed showing the proposed controller provides a stable and robust behavior for congestion control.
Improving the detection of intrusion in vehicular ad-hoc networks with modifi...TELKOMNIKA JOURNAL
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Vehicular ad-hoc networks (VANETs) are wireless-equipped vehicles that form networks along the road. The security of this network has been a major challenge. The identity-based cryptosystem (IBC) previously used to secure the networks suffers from membership authentication security features. This paper focuses on improving the detection of intruders in VANETs with a modified identity-based cryptosystem (MIBC). The MIBC is developed using a non-singular elliptic curve with Lagrange interpolation. The public key of vehicles and roadside units on the network are derived from number plates and location identification numbers, respectively. Pseudo-identities are used to mask the real identity of users to preserve their privacy. The membership authentication mechanism ensures that only valid and authenticated members of the network are allowed to join the network. The performance of the MIBC is evaluated using intrusion detection ratio (IDR) and computation time (CT) and then validated with the existing IBC. The result obtained shows that the MIBC recorded an IDR of 99.3% against 94.3% obtained for the existing identity-based cryptosystem (EIBC) for 140 unregistered vehicles attempting to intrude on the network. The MIBC shows lower CT values of 1.17 ms against 1.70 ms for EIBC. The MIBC can be used to improve the security of VANETs.
Conceptual model of internet banking adoption with perceived risk and trust f...TELKOMNIKA JOURNAL
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Understanding the primary factors of internet banking (IB) acceptance is critical for both banks and users; nevertheless, our knowledge of the role of usersโ perceived risk and trust in IB adoption is limited. As a result, we develop a conceptual model by incorporating perceived risk and trust into the technology acceptance model (TAM) theory toward the IB. The proper research emphasized that the most essential component in explaining IB adoption behavior is behavioral intention to use IB adoption. TAM is helpful for figuring out how elements that affect IB adoption are connected to one another. According to previous literature on IB and the use of such technology in Iraq, one has to choose a theoretical foundation that may justify the acceptance of IB from the customerโs perspective. The conceptual model was therefore constructed using the TAM as a foundation. Furthermore, perceived risk and trust were added to the TAM dimensions as external factors. The key objective of this work was to extend the TAM to construct a conceptual model for IB adoption and to get sufficient theoretical support from the existing literature for the essential elements and their relationships in order to unearth new insights about factors responsible for IB adoption.
Efficient combined fuzzy logic and LMS algorithm for smart antennaTELKOMNIKA JOURNAL
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The smart antennas are broadly used in wireless communication. The least mean square (LMS) algorithm is a procedure that is concerned in controlling the smart antenna pattern to accommodate specified requirements such as steering the beam toward the desired signal, in addition to placing the deep nulls in the direction of unwanted signals. The conventional LMS (C-LMS) has some drawbacks like slow convergence speed besides high steady state fluctuation error. To overcome these shortcomings, the present paper adopts an adaptive fuzzy control step size least mean square (FC-LMS) algorithm to adjust its step size. Computer simulation outcomes illustrate that the given model has fast convergence rate as well as low mean square error steady state.
Design and implementation of a LoRa-based system for warning of forest fireTELKOMNIKA JOURNAL
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This paper presents the design and implementation of a forest fire monitoring and warning system based on long range (LoRa) technology, a novel ultra-low power consumption and long-range wireless communication technology for remote sensing applications. The proposed system includes a wireless sensor network that records environmental parameters such as temperature, humidity, wind speed, and carbon dioxide (CO2) concentration in the air, as well as taking infrared photos.The data collected at each sensor node will be transmitted to the gateway via LoRa wireless transmission. Data will be collected, processed, and uploaded to a cloud database at the gateway. An Android smartphone application that allows anyone to easily view the recorded data has been developed. When a fire is detected, the system will sound a siren and send a warning message to the responsible personnel, instructing them to take appropriate action. Experiments in Tram Chim Park, Vietnam, have been conducted to verify and evaluate the operation of the system.
Wavelet-based sensing technique in cognitive radio networkTELKOMNIKA JOURNAL
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Cognitive radio is a smart radio that can change its transmitter parameter based on interaction with the environment in which it operates. The demand for frequency spectrum is growing due to a big data issue as many Internet of Things (IoT) devices are in the network. Based on previous research, most frequency spectrum was used, but some spectrums were not used, called spectrum hole. Energy detection is one of the spectrum sensing methods that has been frequently used since it is easy to use and does not require license users to have any prior signal understanding. But this technique is incapable of detecting at low signal-to-noise ratio (SNR) levels. Therefore, the wavelet-based sensing is proposed to overcome this issue and detect spectrum holes. The main objective of this work is to evaluate the performance of wavelet-based sensing and compare it with the energy detection technique. The findings show that the percentage of detection in wavelet-based sensing is 83% higher than energy detection performance. This result indicates that the wavelet-based sensing has higher precision in detection and the interference towards primary user can be decreased.
A novel compact dual-band bandstop filter with enhanced rejection bandsTELKOMNIKA JOURNAL
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In this paper, we present the design of a new wide dual-band bandstop filter (DBBSF) using nonuniform transmission lines. The method used to design this filter is to replace conventional uniform transmission lines with nonuniform lines governed by a truncated Fourier series. Based on how impedances are profiled in the proposed DBBSF structure, the fractional bandwidths of the two 10 dB-down rejection bands are widened to 39.72% and 52.63%, respectively, and the physical size has been reduced compared to that of the filter with the uniform transmission lines. The results of the electromagnetic (EM) simulation support the obtained analytical response and show an improved frequency behavior.
Deep learning approach to DDoS attack with imbalanced data at the application...TELKOMNIKA JOURNAL
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A distributed denial of service (DDoS) attack is where one or more computers attack or target a server computer, by flooding internet traffic to the server. As a result, the server cannot be accessed by legitimate users. A result of this attack causes enormous losses for a company because it can reduce the level of user trust, and reduce the companyโs reputation to lose customers due to downtime. One of the services at the application layer that can be accessed by users is a web-based lightweight directory access protocol (LDAP) service that can provide safe and easy services to access directory applications. We used a deep learning approach to detect DDoS attacks on the CICDDoS 2019 dataset on a complex computer network at the application layer to get fast and accurate results for dealing with unbalanced data. Based on the results obtained, it is observed that DDoS attack detection using a deep learning approach on imbalanced data performs better when implemented using synthetic minority oversampling technique (SMOTE) method for binary classes. On the other hand, the proposed deep learning approach performs better for detecting DDoS attacks in multiclass when implemented using the adaptive synthetic (ADASYN) method.
The appearance of uncertainties and disturbances often effects the characteristics of either linear or nonlinear systems. Plus, the stabilization process may be deteriorated thus incurring a catastrophic effect to the system performance. As such, this manuscript addresses the concept of matching condition for the systems that are suffering from miss-match uncertainties and exogeneous disturbances. The perturbation towards the system at hand is assumed to be known and unbounded. To reach this outcome, uncertainties and their classifications are reviewed thoroughly. The structural matching condition is proposed and tabulated in the proposition 1. Two types of mathematical expressions are presented to distinguish the system with matched uncertainty and the system with miss-matched uncertainty. Lastly, two-dimensional numerical expressions are provided to practice the proposed proposition. The outcome shows that matching condition has the ability to change the system to a design-friendly model for asymptotic stabilization.
Implementation of FinFET technology based low power 4ร4 Wallace tree multipli...TELKOMNIKA JOURNAL
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Many systems, including digital signal processors, finite impulse response (FIR) filters, application-specific integrated circuits, and microprocessors, use multipliers. The demand for low power multipliers is gradually rising day by day in the current technological trend. In this study, we describe a 4ร4 Wallace multiplier based on a carry select adder (CSA) that uses less power and has a better power delay product than existing multipliers. HSPICE tool at 16 nm technology is used to simulate the results. In comparison to the traditional CSA-based multiplier, which has a power consumption of 1.7 ยตW and power delay product (PDP) of 57.3 fJ, the results demonstrate that the Wallace multiplier design employing CSA with first zero finding logic (FZF) logic has the lowest power consumption of 1.4 ยตW and PDP of 27.5 fJ.
Evaluation of the weighted-overlap add model with massive MIMO in a 5G systemTELKOMNIKA JOURNAL
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The flaw in 5G orthogonal frequency division multiplexing (OFDM) becomes apparent in high-speed situations. Because the doppler effect causes frequency shifts, the orthogonality of OFDM subcarriers is broken, lowering both their bit error rate (BER) and throughput output. As part of this research, we use a novel design that combines massive multiple input multiple output (MIMO) and weighted overlap and add (WOLA) to improve the performance of 5G systems. To determine which design is superior, throughput and BER are calculated for both the proposed design and OFDM. The results of the improved system show a massive improvement in performance ver the conventional system and significant improvements with massive MIMO, including the best throughput and BER. When compared to conventional systems, the improved system has a throughput that is around 22% higher and the best performance in terms of BER, but it still has around 25% less error than OFDM.
Reflector antenna design in different frequencies using frequency selective s...TELKOMNIKA JOURNAL
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In this study, it is aimed to obtain two different asymmetric radiation patterns obtained from antennas in the shape of the cross-section of a parabolic reflector (fan blade type antennas) and antennas with cosecant-square radiation characteristics at two different frequencies from a single antenna. For this purpose, firstly, a fan blade type antenna design will be made, and then the reflective surface of this antenna will be completed to the shape of the reflective surface of the antenna with the cosecant-square radiation characteristic with the frequency selective surface designed to provide the characteristics suitable for the purpose. The frequency selective surface designed and it provides the perfect transmission as possible at 4 GHz operating frequency, while it will act as a band-quenching filter for electromagnetic waves at 5 GHz operating frequency and will be a reflective surface. Thanks to this frequency selective surface to be used as a reflective surface in the antenna, a fan blade type radiation characteristic at 4 GHz operating frequency will be obtained, while a cosecant-square radiation characteristic at 5 GHz operating frequency will be obtained.
Reagentless iron detection in water based on unclad fiber optical sensorTELKOMNIKA JOURNAL
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A simple and low-cost fiber based optical sensor for iron detection is demonstrated in this paper. The sensor head consist of an unclad optical fiber with the unclad length of 1 cm and it has a straight structure. Results obtained shows a linear relationship between the output light intensity and iron concentration, illustrating the functionality of this iron optical sensor. Based on the experimental results, the sensitivity and linearity are achieved at 0.0328/ppm and 0.9824 respectively at the wavelength of 690 nm. With the same wavelength, other performance parameters are also studied. Resolution and limit of detection (LOD) are found to be 0.3049 ppm and 0.0755 ppm correspondingly. This iron sensor is advantageous in that it does not require any reagent for detection, enabling it to be simpler and cost-effective in the implementation of the iron sensing.
Impact of CuS counter electrode calcination temperature on quantum dot sensit...TELKOMNIKA JOURNAL
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In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 ยฐC, 120 ยฐC, 150 ยฐC, and 180 ยฐC under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 ยฐC. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 ยฐC, which lowers resistance while increasing electron lifetime.
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 ยฐC, 120 ยฐC, 150 ยฐC, and 180 ยฐC under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 ยฐC. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 ยฐC, which lowers resistance while increasing electron lifetime.
A progressive learning for structural tolerance online sequential extreme lea...TELKOMNIKA JOURNAL
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This article discusses the progressive learning for structural tolerance online sequential extreme learning machine (PSTOS-ELM). PSTOS-ELM can save robust accuracy while updating the new data and the new class data on the online training situation. The robustness accuracy arises from using the householder block exact QR decomposition recursive least squares (HBQRD-RLS) of the PSTOS-ELM. This method is suitable for applications that have data streaming and often have new class data. Our experiment compares the PSTOS-ELM accuracy and accuracy robustness while data is updating with the batch-extreme learning machine (ELM) and structural tolerance online sequential extreme learning machine (STOS-ELM) that both must retrain the data in a new class data case. The experimental results show that PSTOS-ELM has accuracy and robustness comparable to ELM and STOS-ELM while also can update new class data immediately.
Electroencephalography-based brain-computer interface using neural networksTELKOMNIKA JOURNAL
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This study aimed to develop a brain-computer interface that can control an electric wheelchair using electroencephalography (EEG) signals. First, we used the Mind Wave Mobile 2 device to capture raw EEG signals from the surface of the scalp. The signals were transformed into the frequency domain using fast Fourier transform (FFT) and filtered to monitor changes in attention and relaxation. Next, we performed time and frequency domain analyses to identify features for five eye gestures: opened, closed, blink per second, double blink, and lookup. The base state was the opened-eyes gesture, and we compared the features of the remaining four action gestures to the base state to identify potential gestures. We then built a multilayer neural network to classify these features into five signals that control the wheelchairโs movement. Finally, we designed an experimental wheelchair system to test the effectiveness of the proposed approach. The results demonstrate that the EEG classification was highly accurate and computationally efficient. Moreover, the average performance of the brain-controlled wheelchair system was over 75% across different individuals, which suggests the feasibility of this approach.
Adaptive segmentation algorithm based on level set model in medical imagingTELKOMNIKA JOURNAL
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For image segmentation, level set models are frequently employed. It offer best solution to overcome the main limitations of deformable parametric models. However, the challenge when applying those models in medical images stills deal with removing blurs in image edges which directly affects the edge indicator function, leads to not adaptively segmenting images and causes a wrong analysis of pathologies wich prevents to conclude a correct diagnosis. To overcome such issues, an effective process is suggested by simultaneously modelling and solving systemsโ two-dimensional partial differential equations (PDE). The first PDE equation allows restoration using Eulerโs equation similar to an anisotropic smoothing based on a regularized Perona and Malik filter that eliminates noise while preserving edge information in accordance with detected contours in the second equation that segments the image based on the first equation solutions. This approach allows developing a new algorithm which overcome the studied model drawbacks. Results of the proposed method give clear segments that can be applied to any application. Experiments on many medical images in particular blurry images with high information losses, demonstrate that the developed approach produces superior segmentation results in terms of quantity and quality compared to other models already presented in previeous works.
Automatic channel selection using shuffled frog leaping algorithm for EEG bas...TELKOMNIKA JOURNAL
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Drug addiction is a complex neurobiological disorder that necessitates comprehensive treatment of both the body and mind. It is categorized as a brain disorder due to its impact on the brain. Various methods such as electroencephalography (EEG), functional magnetic resonance imaging (FMRI), and magnetoencephalography (MEG) can capture brain activities and structures. EEG signals provide valuable insights into neurological disorders, including drug addiction. Accurate classification of drug addiction from EEG signals relies on appropriate features and channel selection. Choosing the right EEG channels is essential to reduce computational costs and mitigate the risk of overfitting associated with using all available channels. To address the challenge of optimal channel selection in addiction detection from EEG signals, this work employs the shuffled frog leaping algorithm (SFLA). SFLA facilitates the selection of appropriate channels, leading to improved accuracy. Wavelet features extracted from the selected input channel signals are then analyzed using various machine learning classifiers to detect addiction. Experimental results indicate that after selecting features from the appropriate channels, classification accuracy significantly increased across all classifiers. Particularly, the multi-layer perceptron (MLP) classifier combined with SFLA demonstrated a remarkable accuracy improvement of 15.78% while reducing time complexity.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
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Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
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K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
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Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
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International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
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Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Embedded machine learning-based road conditions and driving behavior monitoring
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Balancing a Segway robot using LQR controller based on genetic and bacteria foraging optimization algorithms
1. TELKOMNIKA Telecommunication, Computing, Electronics and Control
Vol. 18, No. 5, October 2020, pp. 2642~2653
ISSN: 1693-6930, accredited First Grade by Kemenristekdikti, Decree No: 21/E/KPT/2018
DOI: 10.12928/TELKOMNIKA.v18i5.14717 ๏ฒ 2642
Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA
Balancing a Segway robot using LQR controller based on
genetic and bacteria foraging optimization algorithms
Ibrahim K. Mohammed, Abdulla I. Abdulla
Systems and Control Engineering Department, College of Electronics Engineering, Ninevah University, Iraq
Article Info ABSTRACT
Article history:
Received Nov 29, 2019
Revised Feb 11, 2020
Accepted Mar 23, 2020
A two-wheeled single seat Segway robot is a special kind of wheeled mobile
robot, using it as a human transporter system needs applying a robust control
system to overcome its inherent unstable problem. The mathematical model of
the system dynamics is derived and then state space formulation for the system
is presented to enable design state feedback controller scheme. In this research,
an optimal control system based on linear quadratic regulator (LQR) technique
is proposed to stabilize the mobile robot. The LQR controller is designed to
control the position and yaw rotation of the two-wheeled vehicle. The proposed
balancing robot system is validated by simulating the LQR using Matlab
software. Two tuning methods, genetic algorithm (GA) and bacteria foraging
optimization algorithm (BFOA) are used to obtain optimal values for controller
parameters. A comparison between the performance of both controllers
GA-LQR and BFO-LQR is achieved based on the standard control criteria
which includes rise time, maximum overshoot, settling time and control input
of the system. Simulation results suggest that the BFOA-LQR controller
can be adopted to balance the Segway robot with minimal overshoot and
oscillation frequency.
Keywords:
Bacteria foraging optimization
algorithm
Genetic algorithm
LQR controller
Segway robot
Yaw rotation
This is an open access article under the CC BY-SA license.
Corresponding Author:
Ibrahim K. Mohammed,
Systems and Control Engineering Department,
College of Electronics Engineering,
Ninevah University,
Mosul, Iraq.
Email: ibrahim.mohammed@uoninevah.edu.iq
1. INTRODUCTION
The Segway robot is an electric, two-wheeled self-balancing human transporter with a computer-
controlled gyroscopic stabilization and control system. This new vehicle is a complex and hybrid machine that
requires engineering competence in many fields; vehicle dynamics, automatic control, battery technology,
power electronics, software engineering, microcomputer programming, network and communication
engineering. The two-wheeled robot was revealed by Dean Kamen in 2001 to replace the car or buggies which
were more polluting [1]. The personal transporter has the wide applications in the military and civilian field due
to its simple construction, high energy using rate, stable movement and ability to adapt with surrounding
environmental conditions. However, the single-seat robot faces many challenges related to nonlinearity, high
order variables, strong coupling and inherent unstable dynamics of the system. Therefore, balance problem and
development of this type of vehicle is a hot research topic of interest to many robotics laboratories around
the world. Segway is a known two-wheeled single-seat mobile robot which has been utilized as a commercial
personal transportation vehicle. In the Segway robotic system a collection of tiltsensors and five gyroscopes are
2. TELKOMNIKA Telecommun Comput El Control ๏ฒ
Balancing a Segway robot using LQR controller based on genetic andโฆ (Ibrahim K. Mohammed)
2643
used to remain the human user in the straight position [2]. Moreover, [3] use two teams, human transporter
platform (HT) and robot mobility platform (RMP), to created a new mobile robot, called Segway Soccer.
The walking robotic system is used to examine the coordination of dynamically formed, mixed personal-mobile
robot teams within the domain of a team function that requires making a decision and response.
An initial model of a digitally controlled mobile robot has been constructed in [4]. In the presented
prototype, which is based on the inverted pendulum, the human rider is simulated by attaching weights to
the scheme. A linear state feedback controller is used to stabilize the proposed personal mobile robot based on
sensory information from motor encoders and a gyroscope. A new two-wheeled inverted pendulum mobile
robot is presented by [5]. A control system based on pole placement technique is designed to stabilize the rider
in an upright position. It is worth considering that, there are another models for two-wheeled self-balancing
human vehicles invented by robotic engineers. In 2003, David P. A. built the Nbot balancing robot used
a human transporter provided by a linear controller used to stabilize the system using information from motor
encoder and the inertial sensor. Furthermore, [6] has successfully fabricated a new model of robot called
Legway based on Mindstorms robotics kit. A linear controller is used to stabilize the electric vehicle based
information of the tilt angle obtained from two electro-optical proximity detector (EOPD) sensors. However,
fine tuning for the controller parameters is required to achieve a peter performance. Hussien et al. [7] introduced
another model for two-wheeled mobile robot. Nonlinear control system based on model reference adaptive
control (MRAC) using Lpayunovs stability theorem is employed to balance the proposed single-seat electric
vehicle. Simulation and experimental results are presented to validate tracking performance of the proposed
robot actuation system. However, the performance of the robot control system is based on the controller
coefficients, which are chosen arbitrary, therefore, for peter performance an optimization algorithm should be
used. All the proposed controllers used to stabilize the mobile robots are not optimized using optimization
methods, the gain parameters are obtained using trial and error procedure. In order to achieve a stable actuation
performance for mobile robot system a proper controller technique based on tuning algorithm should be used.
The linear quadratic regulator (LQR) is among most popular linear state feedback controllers implemented in
field of industrial applications. The implementation of the LQRcontroller can be noticed by research works
published by [4, 8-11].
In this study, the LQR controller is adopted to implement the control system used to balance
the two-round human vehicle as it seeks basically a trade off between the best control performance and
minimum power input [12, 13]. However, using this controller approach includes many problems and
disadvantages such as relying on the designer experience and skill and the trial and error procedure in
the determine of the controller weighting matrices ๐ and ๐ . Therefore, there is a enormous concern by
robotic engineers in computer-aided optimization algorithms that can be considered to obtain the global
optimum solution of ๐ and ๐ matrices..
There are many optimization approaches that have been adopted by control engineers to obtain
optimum values for elements of LQR matrices, such as a particle swarm inspired evolutionary algorithm
(PS-EA), particle swarm optimization (PSO), genetic algorithm (GA) [14], combination of simulated
annealing (SA) and GA [15], differential evaluation (DE) [16] and ant colony optimization (ACO) [17].
These intelligent optimization tools make the LQR controller system very robust, and insensitive to noisy
and/or missing data. Bacteria foraging optimization algorithm (BFOA) is a new tuning algorithm that can be
applied to optimize the cost function of several problems in different application fields. The BFOA is
a combinatorial optimization algorithm which applied to achieve the best global solution for the proposed
LQR controller. It is worth considering that there is a significant improvement inthe control response of
the LQR controller is achieved by using these tuning algorithms, however, the research work is still open to
explore for further controller improvements and developments. In this research, two tuning algorithms, GA
and BFOA are utilized to improve the behavior of the LQR controller.
The remainder of the paper is organised as follows: section 2 presents modelling and dynamics of
the proposed two-wheeled self-balancing human robot. In section 3, the technique of the controller system is
introduced. Section 4, presents optimization methods of LQR controller. Section 5 and section 6 introduce
controller design and simulation results of GA-LQR and section 7 introduce BFOA-LQR controllers for
the robot system respectively. Conclusions and future work are presented in section 8.
2. SYSTEM MODELING
The performance of a walking robot depends on the reliability of the system modeling and
robustness of the controller design. The structure of the two-wheeled Segway personal robot composes
mainly of an electrical sub system and mechanical subsystem. Figure 1 demonstrates graphic model of
the Segway robot. In this section, the motion equation of the inverted pendulum is derived and the dynamic
model of the motors is formulated. The motor model is then utilized in formulation the dynamic model of
3. ๏ฒ ISSN: 1693-6930
TELKOMNIKA Telecommun Comput El Control, Vol. 18, No. 5, October 2020: 2642 - 2653
2644
the personal robot scheme to give a functional relationship between applied voltage to the DC motors and
adjusting magnetic torque required to stabilize the human mobile robot.
2.1. Electrical subsystem modeling
The main part of the electric sub system is the DC motors, which are used to rotate the left and right
wheel of the robot. The electric circuit of the DC motor is shown in Figure 2. Applying voltage ๐๐ (๐) to
the motor terminals generates a current ๐(๐ก) (๐ด) in the motor armature. The excited motor produces a torque
(๐๐) governed by the following relationship.
๐ถ = ๐พ ๐ ๐ (1)
where ๐พ ๐ is torque constant (๐๐/๐ด). The back electromotive (emf) voltage ๐๐ (๐) produced in
the motor coil can be approximated as a linear function of motor angular velocity ๐ฬ (๐๐๐/๐ ), as follows:
๐๐ = ๐พ๐ ๐ฬ (2)
where ๐พ๐ is torque constant (๐๐ /๐๐๐). Applying Kirchoffโs voltage law to the motor circuit shown in
Figure 2 yields the following expression:
Va = Ri + L
di
dt
+ Ve (3)
It is worth considering that the dynamic of the mechanical system is considered slow compared to that of
electrical system, therefore, the current transients of the system can be omitted. Hence, solving (3) for
the current yields:
๐ข =
๐๐โ๐๐
๐
(4)
based on (2), (4) can be written as follows:
i =
Va
R
โ
Ke
R
ฮธฬ (5)
substituting (5) in (1) gives an expression for the torque produced by DC motor:
C =
Km
R
Va โ
KmKe
R
ฮธฬ (6)
Figure 1. Model of the two-wheeled robot [18] Figure 2. Electric model circuit of DC motor
2.2. Mechanical subsystem modeling
It consists of chassis, which behaviors as inverted pendulum, and the left and right wheels.
In this study, the parameter of mass, radius and moment of inertia of the two wheels are assumed the same.
Based on this assumption the dynamic modeling of the right wheel is the same as that of the left wheel.
In this research, formulation of the right wheel model is considered in detail. It is worth considering that
the modeling strategy of the mechanical robot subsystem is based on an idea that the dynamics of
4. TELKOMNIKA Telecommun Comput El Control ๏ฒ
Balancing a Segway robot using LQR controller based on genetic andโฆ (Ibrahim K. Mohammed)
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the inverted pendulum and wheels are modeled separately at the beginning, and then equations of motion
which completely describe the dynamic behavior of the system are derived [19].
2.2.1. Wheel model
Figure 3 presents the free body diagram of the left and right wheels for the mobile Segway transport
system. Using second Newtonโs law of motion, the sum of the external forces ๐น(๐) exerted on the wheel,
which governs its translation motion in the horizontal x-direction is given by [20].
โ Fx = Mwa (7)
Mwxฬ = Hf โ H (8)
Figure 3. Free body diagram of the robot wheels
where ๐ ๐ค(๐พ๐) is the wheel mass of the robot, a is the gravity acceleration (๐/๐ 2
) and๐ป๐is the friction
force between ground and wheels(๐). While the rotational motion ๐๐ of the wheel is given by: go
โ Mo = Iwฮธฬw (9)
Iwฮธฬw = C โ Hfr (10)
where ๐ผ ๐ค (๐พ๐๐2
) and ๐ฬ ๐ค (๐/๐ 2
) are moment of inertia and acceleration of the wheels respectively, and r
is the radius of wheel (๐). Based on (6), the above equation becomes:
Iwฮธฬw =
Km
R
Va โ
KmKe
R
ฮธฬw โ Hfr (11)
Hf =
Km
Rr
Va โ
KmKe
Rr
ฮธฬw โ
Iw
r
ฮธฬ (12)
where ๐ฬ ๐คis the angular velocity of wheel (๐/๐ ). Substituting (12) into (8) yields (13) and (14) for the left
and right wheels respectively.
Mwxฬ =
Km
Rr
Va โ
KmKe
Rr
ฮธฬw โ
Iw
r
ฮธฬw โ HL (13)
Mwxฬ =
Km
Rr
Va โ
KmKe
Rr
ฮธฬw โ
Iw
r
ฮธฬw โ HR (14)
Because the center of the robot wheel is acted by the linear motion, the angular rotation of the wheel can be
transformed into linear motion by the following simple transformation, ๐ฬ ๐ค ๐ = ๐ฅฬ โ ๐ฬ = ๐ฅฬ/ ๐,
๐ฬ ๐ค ๐ = ๐ฅฬ โ ๐ฬ = ๐ฅฬ/ ๐. By the linear transformation, (13) and (14) become as follows:
Mwxฬ =
Km
Rr
Va โ
KmKe
Rr2
xฬw โ
Iw
r2
xฬ โ HL (15)
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Mwxฬ =
Km
Rr
Va โ
KmKe
Rr2
xฬw โ
Iw
r2
xฬ โ HR (16)
Adding (15) and (16) together yields the following expression,
2(๐ ๐ค +
๐ผ ๐ค
๐2)๐ฅฬ = 2
๐พ ๐
๐ ๐
๐๐ โ 2
๐พ ๐ ๐พ ๐
๐ ๐2 ๐ฅฬ ๐ค โ (๐ป๐ฟ + ๐ป ๐ ) (17)
2.2.2. Chassis model
The chassis of the mobile robot can be modeled as an inverted pendulum, Figure 4 presents the free
body diagram of the chassis. Again, based on Newtonโs law of motion, the sum of forces acting on
the chassis in the horizontal x-direction is given by [20]:
โ Fx = Mpxฬ (18)
Mpxฬ = HL + HR โ Mplฮธpฬ cos ฮธp + Mplฮธฬ2
p sin ฮธp (19)
where ๐ ๐ is the wheel mass of the robot (๐พ๐) and ๐ ๐ is the rotational angle of the chassis (๐๐๐). The above
equation is rearranged as follows:
HL + HR = Mpxฬ + Mplฮธฬp cos ฮธp โ Mplฮธฬ2
p sin ฮธp (20)
The sum of perpendicular forces acting on the pendulum is:
โ Fp = Mpxฬ cos ฮธp (21)
(๐ป๐ฟ + ๐ป ๐ ) ๐๐๐ ๐ ๐ + (๐๐ฟ + ๐๐ ) ๐ ๐๐ ๐ ๐ โ ๐ ๐ ๐ ๐ ๐๐ ๐ ๐ โ ๐ ๐ ๐๐ฬ ๐ฬ = ๐ ๐ ๐ฅฬ ๐๐๐ ๐ ๐ (22)
where ๐๐ฟand ๐๐ are the reaction forces between left and right wheel and chassis (๐) respectively and ๐ฬ ๐ is
chassis angular acceleration(๐/๐ 2
), sum of moments around the center of pendulum mass is given by:
โ Mo = Ipฮธฬp (23)
Ipฮธฬp = โ(HL + HR)l cos ฮธp โ (PL + PR)l sin ฮธp โ (CL + CR) (24)
where ๐ถ๐ฟ and ๐ถ ๐ are the motor torque applied to left and right wheels respectively (๐๐) the motor torque
exerted on the pendulum applied as defined in (6) and after linear transformation,
CL + CR = 2
Km
R
Va โ 2
KmKe
R
xฬ
r
(25)
substituting (25) into (24) yields,
Ipฮธฬp โ 2
KmKe
R
xฬ
r
+ 2
Km
R
Va = โ(HL + HR)l cos ฮธp (PL + PR)l sin ฮธp (26)
substitute (26) in (22) after multiply (22) by(โ๐) yields:
Ipฮธฬp โ 2
KmKe
R
xฬ
r
+ 2
Km
R
Va + Mpgl sin ฮธp + Mpl2
ฮธฬpฬ = โMplxฬ cos ฮธp (27)
Sum of moments around the center of pendulum mass is given:
โMplxฬ cos ฮธp = (Ip + Mpl2
)ฮธฬp โ 2
KmKe
Rr2 xฬ + 2
Km
Rr
Va + Mpgl sin ฮธp (28)
to eliminate the term (๐ป๐ฟ + ๐ป ๐ ) from the motor dynamic (20) is substituted in (17).
2
Km
Rr
Va = (2Mw +
Iw
r2 + Mp)xฬ + 2
KmKe
Rr2 xฬ + Mplฮธฬp cos ฮธp โ Mplฮธฬ2
pฬ sin ฮธp (29)
6. TELKOMNIKA Telecommun Comput El Control ๏ฒ
Balancing a Segway robot using LQR controller based on genetic andโฆ (Ibrahim K. Mohammed)
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for purpose of design a linear control system, the system dynamic (28) and (29) are linearized about
an operating point based on the assumption ๐ ๐ค = ๐ + ๐ where ๏ช denotes an angle measured from
the vertical upward direction. Therefore, ๐ ๐๐ ๐ ๐ = โ๐, ๐๐๐ ๐ ๐ = โ1 and (๐๐ ๐/๐๐ก)2
= 0 for purpose of state
space representation, the dynamic (28) and (29) are rewritten as follows:
ฯฬ =
MpI
(Ip+MpI2)
xฬ +
2KmKe
Rr(Ip+MpI2)
xฬ +
MpgI
Rr(Ip+MpI2)
ฯ โ
2Km
(Ip+MpI2)
Va (30)
xฬ =
2Km
RrKw
Va โ
2KmKe
Rr2Kw
xฬ +
MpI
Rr2Kw
ฯฬ (31)
where ๐พ ๐ค = 2๐ ๐ค + 2๐ผ ๐ค/๐2
. After a series of algebraic manipulation, the state equation becomes:
[
๐ฅฬ
๐ฅฬ
๐ฬ
๐ฬ
] =
[
0 1 0
0
๐พ1(๐ ๐ ๐ผ๐โ๐ผ ๐โ๐ ๐ ๐ผ2)
๐ ๐2 ๐ผ
๐2
๐ ๐๐ผ2
๐ผ
0 0 0
0
๐พ1(๐๐ฝโ๐ ๐ ๐ผ)
๐ ๐2 ๐ผ
๐ ๐ ๐๐ผ๐ฝ
๐ผ
0
0
1
0
] [
๐ฅ
๐ฅฬ
๐
๐ฬ
] +
[
0
2๐พ ๐(๐ผ ๐+๐ ๐ ๐ผ2โ๐ ๐ ๐ผ๐)
๐ ๐๐ผ
0
2๐พ ๐(๐ ๐ ๐ผโ๐ฝ)
๐ ๐๐ผ ]
๐๐ (32)
where, ๐พ1 = 2๐พ ๐ ๐พ๐, ๐ฝ = 2๐ ๐ค +
2๐ผ ๐ค
๐2 + ๐ ๐ and ๐ผ = [๐ผ ๐ ๐ฝ + 2๐ ๐ ๐ผ2
(๐ ๐ค +
๐ผ ๐ค
๐2)]
.
It is worth considering that
the system modeling is based on the supposition that both wheels of the walking robot are assumed in state of
contact with the ground and without sliding. Cornering forces produced by vehicle wheels during cornering
are also considered negligible [19].
Figure 4. Free body diagram of the chassis
3. CONTROLLER TECHNIQUE
In this research, LQR technique is utilized to implement the proposed robot control system. LQR is
a common controller approach used effectively in the control applications of the movement systems. Figure 5
shows block diagram of the Segway robot control system based on LQR controller. The state and output
matrix equations describing the Segway robot equations of motion are given by:
๐ฬ(๐ก) = ๐ด๐(๐ก) + ๐ต๐ข(๐ก) (33)
๐ฆ(๐ก) = ๐ถ๐(๐ก) + ๐ต๐ข(๐ก) (34)
where ๐ด(๐๐ฅ๐), ๐ต(๐๐ฅ๐), ๐ถ(๐๐ฅ๐), ๐ท(๐๐ฅ๐) are the system, input, output and feed forward matrix respectively.
In this approach, the input vector:
๐ข(๐ก) = โ๐พ๐(๐ก) (35)
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where๐พ = [๐พ1 ๐พ2 ๐พ3 ๐พ4] is an optimal feedback gain matrix of the controller used to track the input
command while the following performance index:
๐ฝ = โซ (๐ ๐
(๐ก)๐(๐ก)๐(๐ก) + ๐ข ๐
(๐ก)๐ (๐ก)๐ข(๐ก))๐๐ก
โ
0
(36)
where ๐(๐ก) and๐ (๐ก) are weighting state and input matrices respectively. The feedback gain matrix K can be
determined by using the following:
๐พ = ๐ โ1
๐ต ๐
๐ (37)
where P denotes the solution of the following Riccati:
๐ด ๐
๐ + ๐๐ด โ ๐๐ต๐ โ1
๐ต ๐
๐ + ๐ = 0 (38)
The controller weighting matrices should be tuned properly in order to minimize the following performance
index )(J :
๐ฝ = โซ (๐11 ๐ฅ1
2
+ ๐22 ๐ฅ2
2
+ ๐33 ๐ฅ3
2
+ ๐44 ๐ฅ4
2
+ ๐ ๐ข2
)๐๐ก
โ
0
(39)
where ๐11, ๐22, ๐33 and 44q represent the weighting elements of position, speed, angle and angular velocity of
the proposed robot system respectively. It is worth considering that by using controller weighting matrices
๐(๐ก) and ๐ (๐ก) which govern the behavior of the robot system states and control effort respectively,
the optimal LQR gain matrix ๐พ is computed based on the Matlab command โ lqr โ.
Figure 5. Segway robot control system using LQR controller
4. LQR OPTIMIZATION METHODS
In this research, two optimization algorithms, GA and BFOA, are used to tune the ๐(๐ก) and ๐ (๐ก)
matrices of the LQR controller, which are adopted to calculate the gain matrix required to balance
the Segway system. Based on optimized gain matrix ๐พ a good output time response with minimal of rise time
(๐ก ๐), settling time(๐ก ๐ ), maximum overshoot (๐๐) and steady state error(๐๐ ๐ ) can be investigated.
4.1. Genetic algorithm
GA is an optimization technique used to find global solution for more control problems. Based on
the mechanisms of natural selection. In this optimization approach, the solution space is selected by
generating a population of candidate individuals to find optimum values for the problem. The procedure of
GA optimization method includes three basic steps, namely selection, crossover and mutation. By applying
these stages new individuals can be created, which, could be better than their parents. Based on the fitness
function of the system, the GA steps are repeated for many generations and eventually stop at generating
candidate individual elements that can represent the best solution for the application problem [14]. Figure 6
shows the graphical illustration of the GA loop.
The definition of the GA steps is as follows Abdulla [14]: Random initial population - Choose
individuals for mating - Mate the population to generate progeny - Mutate progeny - New individuals
inserted into population - Are criteria satisfied? - End of solution searching. Each chromosome represented
by five real value cells that correspond to the LQR controller weighting matrices ๐(๐ก) and ๐ (๐ก) as shown in
Figure 7. The chromosome elements ๐11, ๐22, ๐33, ๐44 and R should be adjusted properly by optimum
positive numbers in order to achieve best control performance.
8. TELKOMNIKA Telecommun Comput El Control ๏ฒ
Balancing a Segway robot using LQR controller based on genetic andโฆ (Ibrahim K. Mohammed)
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Figure 6. Genetic algorithm loop Figure 7. Chromosome definition
4.2. BFO algorithm
The bacteria foraging behavior is a computational model, which, has attracted more attention as it is
a rich source of potential engineering applications. BFO is a simple and powerful population-based numerical
optimization algorithm that has been introduced by Passino in 2002 [21]. The BFO algorithm has been
gaining a considerable interest in researchers due to its efficiency in solving and optimizing more engineering
problems in several application domains, such as optimal control [22], harmonic estimation [23] and
transmission loss reduction [24]. The strategy of bacteria selection for the BFO algorithm bases on an idea
that the bacteria with poor foraging is eliminated and following up those bacteria which have successful
foraging to maximize energy obtained per unit time [21]. It is worth considering that, in this new
optimization algorithm a social foraging approach of the E-coli bacteria can be applied successfully to solve
multi-optimal function optimization problem. The E-coli bacteria can move in two ways namely, swimming
and tumbling. Figure 8 shows the swim and tumble movement of a bacterium.
Figure 8. movement modes of a bacterium
4.3. BFO foraging strategy [25]
โ Chemotaxis: This process is related to movement of bacterium during search for food. The E-coli bacteria
can move in two ways namely, swimming and tumbling, and they are able to alternate between these two
movement styles for the whole of their lifetime. In the swimming mode, the bacteria walk in a certain
direction for gathering food, while in the tumbling mode, they move with random directions.
โ Swarming: The swarming action means the bacteria with a good fitness value, try to attract others to form
groups, so that they all can arrive at the desired location. These groups of E-coli cells arrange themselves,
in which, they can move as concentric patterns for food searching.
โ Reproduction: In this stage, all the bacteria population are classified based on health status.
The healthier bacteria, which, have had sufficient nutrients will be reproduced, while the less healthy
bacteria will die. The surviving bacteria will split into an identical replica of itself placed in the same
locations with a that number equals to the number of the dead ones.
โ Elimination and Dispersal: During this evolutionary step, gradual or sudden events or attacks in
the local living environment of the bacteria, may occur due to significant rising of the temperature caused
by occupancy of a high density of bacteria for a specific area. This high temperature may kill a group of
bacteria and dispersal of others into some new locations.
5. ROBOT CONTROL SYSTEM DESIGN
In this research, an optimal control system for the Segway robot is designed using the state feedback
LQR controller. The gain parameters of the controller are tuned effectively, using optimization algorithms,
GA and BFOA. The proposed controller design is validated using Matlab programming. Based on step input,
the control system is designed for the following requirements: rise time less than 10 (ms), settling time less
than 30 (ms), maximum overshoot percentage less than 5%. The fitness function of the robot control system
is as follows:
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๐น = ๐. ๐ก ๐, ๐ก ๐๐๐๐ฅ + ๐. ๐ก ๐ , ๐ก ๐ ๐๐๐ฅ + ๐. ๐, ๐๐ (40)
where ๐ is the closed-loop transfer function of the Segway robot scheme ๐ก ๐ is the rise time (s), ๐ก ๐๐๐๐ฅ is
the maximum rise time (s), ๐ก ๐ is the settling time (s), ๐ก ๐ ๐๐๐ฅ is the maximum settling time (s), ๐ is
the overshoot value of the output response and ๐๐ is the maximum over shoot value. This function is
considered in optimization process of the controller gain matrix using GA and BFO tuning algorithms.
6. GA-LQR CONTROLLER DESIGN AND RESULTS
The block diagram of the Segway control system using GA-LQR controller is shown in Figure 9.
Based on the system parameters (๐ =1.6๐บ, ๐ฟ =1.2๐๐ป, ๐ =0.16๐, ๐ ๐ค =0.02๐พ๐, ๐ ๐ =0.52๐พ๐,
๐ผ ๐ค =0.0032๐พ๐๐2
, ๐ผ ๐ =0.0038 ๐พ๐๐2
) the state and output equation are given in (41) and (42) respectively.
The global optimal solution for the LQR controller problem is achieved using genetic algorithm
programming. This solution includes determine optimum values for the weighting matrices elements, which,
are given below. Based on the optimized weighting matrices, the LQR gain matrix K was computed using
the Matlab command โ๐๐๐โ as follows:๐ = ๐๐๐๐๐๐(๐11, ๐22, ๐33, ๐44) where ๐11 = 8.969., ๐22 =0.308,
๐33 =0.121, ๐44 =0.0085, ๐ =2.123*10โ5
and ๐พ = [-6.4988 -3.8592 -5.1982 -0.7348].
[
๐ฅฬ
๐ฅฬ
๐ฬ
๐ฬ
] = [
0 1 0 0
0 โ0.0316 0.3817 0
0 0 0 1
0 0.3927 49.5531 0
] [
๐ฅ
๐ฅฬ
๐
๐ฬ
] + [
0
0.05746
0
โ0.7141
] ๐๐ (41)
๐ฆ = [
1 0 0 0
0 0 1 0
] [
๐ฅ
๐ฅฬ
๐
๐ฬ
] + [
0
0
] ๐ข (42)
The response of the system output ๐ฅ๐ฅ(๐ก) and ๐ฅ๐(๐ก) using the above optimized feedback gain
matrix is shown in Figure 10. Figure 11 presents the input signal of the Segway system. It is clear from
Figures 10 and 11 that the tuned controller utilizing the GA tuning method can effectively perform a fast and
stable response under an acceptable input effort. Based on Figure 10, the output states ๐ฅ๐ฅ(๐ก) and ๐ฅ๐(๐ก)
tracked the demand input trajectories without overshoot, rise time and settling time of approximately 80 ms
and 95 ms respectively and approximately zero steady state error. Figure 12 presents converging of the LQR
weighting matrices through iterations based on GA tuning method.
Figure 9. Block diagram of Segway controller GA-LQR
10. TELKOMNIKA Telecommun Comput El Control ๏ฒ
Balancing a Segway robot using LQR controller based on genetic andโฆ (Ibrahim K. Mohammed)
2651
Figure 10. System response using
GA-LQR controller
Figure 11. System input based
on GA-LQR controller
(a) (b)
(c) (d)
(e)
Figure 12. Generation elements of ๐(๐ก) and ๐ (๐ก) matrices for GA-LQR controller; (a) ๐11 element,
(b) ๐22 element, (c) q33 element, (d) ๐44 element, and (e) ๐ element
7. BFO-LQR CONTROLLER DESIGN AND RESULTS
The design of LQR controller based on BFOA method is analogous to that of the GA-LQR control
system as previously presented in Figure 9. The optimized LQR matrices ๐(๐ก) and ๐ (๐ก) and controller gain
matrix using BFO algorithm are as follows: ๐ = ๐๐๐๐๐๐(๐11, ๐22, ๐33, ๐44) where ๐11 =289.104,
๐22 =-5.15*10โ5
,๐33 =-5*10โ5
, 44q = -5.1*10โ5
๐ =0.00028 and ๐พ = [-1022 -260.2 886.72 77.7].
The time response of the robot states ๐ฅ๐ฅ(๐ก), ๐ฅ๐(๐ก) using BFOA-LQR controller is shown in
Figure 13. Figure 14 shows the control effort required to stabilize the Segway robot system. Regarding
the optimization of the controller, Figure 15 introduces converging elements of weighting matrices of
the LQR controller through iterations based on BFOA tuning algorithm. By comparing the behavior of
the robot system shown in Figures 10, 11, 13 and 14. It should be noted that the BFOA-LQR controller can
achieve more stable and faster response through following the desired trajectories effectively. Table 1 shows
comparison results between the GA-LQR controller and BFOA-LQR controller based on control criteria
parameters. Based on Table 1, the BFOA-LQR controller enabled the walking robot to follow the demand
trajectories effectively.
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Figure 13. Robot response using BFOA-LQR Figure 14. Control effort of robot system
(a) (b)
(c) (d)
(e)
Figure 15. Generation elements of ๐(๐ก) and ๐ (๐ก) matrices for BFO-LQR controller; (a) ๐11 element,
(b) ๐22 element, (c) q33 element(c) q33 element, (c) q33 element,
(d) ๐44 element, and (e) ๐ element (continue)
Table 1. Performance parameters of the Segway using GA-LQR and BFOA-LQR controller
Cont. Type System Output
Control Criteria Parameter
Rise Time Settling Time Max. Overshoot Control Input
GA-LQR Position 1.25 s 1 s 5 % 1.3 V
Yaw Angle 1.8 s 10 ms 120 %
BFOA-LQR Position 0.5 s 0.33 s 0 % 1.4 V
Yaw Angle 0.85 s 4 ms 130 %
8. CONCLUSIONS
In this research, an optimal linear control system was adopted to balance a Segway two-wheeled
mobile robot. The dynamics of the robot system is modeled in state space form in order to design a state
feedback stabilizing controller for the Seqway robot system. A LQR controller was proposed to stabilize
the Segway robot in upright position. The controller is optimized using two tuning algorithms, GA and BFO.
12. TELKOMNIKA Telecommun Comput El Control ๏ฒ
Balancing a Segway robot using LQR controller based on genetic andโฆ (Ibrahim K. Mohammed)
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An active stabilizing scheme for the Segway robot system has been implemented successfully using
GA-LQR controller and BFOA-LQR controller. Simulation results of the controllers are introduced and then
compared based on standard stabilizing parameters. The comparison revealed that the BFOA-LQR controller
can be adopted to implement faster and a more stable balancing system for the Segway vehicle.
REFERENCES
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