This summarizes a document describing a path following control method for experimental car-like robots. It presents a modified proportional control approach that takes a linear combination of proportional gains over cross-track error and heading error as feedback. This method was experimentally tested on a 1/10 scale RC car navigating various paths indoors using real-time motion capture for state feedback. Simulation and experiments showed the combined error approach provided stable control for navigating paths, unlike methods using only one error term, and was able to handle the non-holonomic constraints of the car's motion.
Comparative Analysis for NN-Based Adaptive Back-stepping Controller and Back-...IJERA Editor
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.
Comparison of active and semi active suspension systems using robust controllerMustefa Jibril
1) The document compares active and semi-active suspension systems for a quarter car model using robust H-infinity control.
2) Mathematical models are developed and simulations are run with random and sine road disturbances to evaluate body travel, acceleration, and suspension deflection.
3) The results show that the active suspension system with H-infinity controller is most effective at decreasing body acceleration and maintaining suspension deflection matching the road profile, proving its advantages over the semi-active system.
Velocity control of ROV using modified integral SMC with optimization tuning ...TELKOMNIKA JOURNAL
This document presents a study on velocity control of a Remotely Operated Vehicle (ROV) using a modified integral sliding mode control (SMC) with parameter optimization tuning based on Lyapunov analysis. The study proposes using a modified integral SMC to compensate for errors in the ROV by designing different control inputs for each of the five degrees of freedom motions. Particle swarm optimization is used to optimize the adjustment of four SMC parameters (γ, λ, α, β) for each degree of freedom, resulting in twenty tuned parameters total. Simulation results are presented to evaluate the effectiveness of the modified integral SMC compared to nonlinear control methods, and stability of the control law is proved mathematically using Lyapun
Methods of robot programming
Leadthrough programming methods
A robot program as a path in space
Motion interpolation
WAIT, SIGNAL and DELAY commands
Branching
Comparison of neural network narma l2 model reference and predictive controll...Mustefa Jibril
The document compares NARMA-L2, model reference, and predictive controllers for a nonlinear quarter car active suspension system. It begins by developing the mathematical model of the suspension system and hydraulic actuator. It then describes the bump and sine pavement road profiles used as inputs. The controller designs are presented, including the NARMA-L2 neural network architecture, model reference design using two neural networks, and predictive design training a neural network to model the plant dynamics. Simulation results show the body travel, acceleration, and suspension deflection outputs for each controller under bump and sine road disturbances. The NARMA-L2 controller performed best in minimizing body travel and acceleration.
Evolutionary Design of Mathematical tunable FPGA Based MIMO Fuzzy Estimator S...Waqas Tariq
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.
Design Novel Nonlinear Controller Applied to Robot Manipulator: Design New Fe...Waqas Tariq
This document describes a novel adaptive feedback linearization fuzzy controller for robot manipulators. It begins by discussing limitations of traditional feedback linearization controllers, such as sensitivity to parameter uncertainty. It then proposes designing a feedback linearization fuzzy controller to address this issue. The key steps are: 1) designing the fuzzy controller, including fuzzifying inputs/outputs and developing a rule base, 2) developing an adaptive feedback linearization fuzzy controller by adding an adaptive law to tune fuzzy rule parameters online and improve disturbance rejection. The goal is to develop a robust position controller for robot manipulators that maintains acceptable performance despite nonlinearities and uncertainty.
A Longitudinal Control Algorithm for Smart Cruise Control with Virtual Parame...ijceronline
This paper presents a longitudinal control algorithm for a smart cruise control with virtual parameters in multiple transitions by a driver and traffic conditions. The object is to achieve driver’s comfort and smooth transition with collision prevention for safety in various driving situations. The proposed algorithm consists of an in-path target selection, a generation of virtual parameters, and longitudinal controller for smart cruise control. The in-path target selection algorithm selects an important target which moves on the driving direction of subject vehicle. In addition, it provides the information in order to drive a subject vehicle smoothly and improve safety in various traffic transitions. Finally, smart cruise control controller with virtual parameters computes the desired acceleration. In order to reduce effects of discontinuous changes caused by traffic conditions or drivers such as time gap, set speed, and automation switching, the virtual parameters are applied to longitudinal control algorithm for smart cruise control. The performance and safety benefits of the proposed smart cruise control system are investigated via simulations using real vehicle driving data
Comparative Analysis for NN-Based Adaptive Back-stepping Controller and Back-...IJERA Editor
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.
Comparison of active and semi active suspension systems using robust controllerMustefa Jibril
1) The document compares active and semi-active suspension systems for a quarter car model using robust H-infinity control.
2) Mathematical models are developed and simulations are run with random and sine road disturbances to evaluate body travel, acceleration, and suspension deflection.
3) The results show that the active suspension system with H-infinity controller is most effective at decreasing body acceleration and maintaining suspension deflection matching the road profile, proving its advantages over the semi-active system.
Velocity control of ROV using modified integral SMC with optimization tuning ...TELKOMNIKA JOURNAL
This document presents a study on velocity control of a Remotely Operated Vehicle (ROV) using a modified integral sliding mode control (SMC) with parameter optimization tuning based on Lyapunov analysis. The study proposes using a modified integral SMC to compensate for errors in the ROV by designing different control inputs for each of the five degrees of freedom motions. Particle swarm optimization is used to optimize the adjustment of four SMC parameters (γ, λ, α, β) for each degree of freedom, resulting in twenty tuned parameters total. Simulation results are presented to evaluate the effectiveness of the modified integral SMC compared to nonlinear control methods, and stability of the control law is proved mathematically using Lyapun
Methods of robot programming
Leadthrough programming methods
A robot program as a path in space
Motion interpolation
WAIT, SIGNAL and DELAY commands
Branching
Comparison of neural network narma l2 model reference and predictive controll...Mustefa Jibril
The document compares NARMA-L2, model reference, and predictive controllers for a nonlinear quarter car active suspension system. It begins by developing the mathematical model of the suspension system and hydraulic actuator. It then describes the bump and sine pavement road profiles used as inputs. The controller designs are presented, including the NARMA-L2 neural network architecture, model reference design using two neural networks, and predictive design training a neural network to model the plant dynamics. Simulation results show the body travel, acceleration, and suspension deflection outputs for each controller under bump and sine road disturbances. The NARMA-L2 controller performed best in minimizing body travel and acceleration.
Evolutionary Design of Mathematical tunable FPGA Based MIMO Fuzzy Estimator S...Waqas Tariq
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.
Design Novel Nonlinear Controller Applied to Robot Manipulator: Design New Fe...Waqas Tariq
This document describes a novel adaptive feedback linearization fuzzy controller for robot manipulators. It begins by discussing limitations of traditional feedback linearization controllers, such as sensitivity to parameter uncertainty. It then proposes designing a feedback linearization fuzzy controller to address this issue. The key steps are: 1) designing the fuzzy controller, including fuzzifying inputs/outputs and developing a rule base, 2) developing an adaptive feedback linearization fuzzy controller by adding an adaptive law to tune fuzzy rule parameters online and improve disturbance rejection. The goal is to develop a robust position controller for robot manipulators that maintains acceptable performance despite nonlinearities and uncertainty.
A Longitudinal Control Algorithm for Smart Cruise Control with Virtual Parame...ijceronline
This paper presents a longitudinal control algorithm for a smart cruise control with virtual parameters in multiple transitions by a driver and traffic conditions. The object is to achieve driver’s comfort and smooth transition with collision prevention for safety in various driving situations. The proposed algorithm consists of an in-path target selection, a generation of virtual parameters, and longitudinal controller for smart cruise control. The in-path target selection algorithm selects an important target which moves on the driving direction of subject vehicle. In addition, it provides the information in order to drive a subject vehicle smoothly and improve safety in various traffic transitions. Finally, smart cruise control controller with virtual parameters computes the desired acceleration. In order to reduce effects of discontinuous changes caused by traffic conditions or drivers such as time gap, set speed, and automation switching, the virtual parameters are applied to longitudinal control algorithm for smart cruise control. The performance and safety benefits of the proposed smart cruise control system are investigated via simulations using real vehicle driving data
Fractional order PID for tracking control of a parallel robotic manipulator t...ISA Interchange
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 identification, design, and validation of control strategies. Identification 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.
The document discusses driverless, unattended metro systems as a solution that can satisfy the needs of both transit operators and passengers. It notes key operator needs like system availability, reliability, and cost savings, as well as passenger needs like short wait times, comfort, and safety. A driverless metro without on-board personnel is presented as a solution that meets all of these needs by allowing flexible operation, adjustable capacity, and lower maintenance costs while maintaining high performance, availability, and reliability. Examples are given of existing driverless metro lines in Copenhagen and their high levels of service availability over several years.
Methodology of Mathematical error-Based Tuning Sliding Mode ControllerCSCJournals
Design a nonlinear controller for second order nonlinear uncertain dynamical systems is one of the most important challenging works. This paper focuses on the design of a chattering free mathematical error-based tuning sliding mode controller (MTSMC) for highly nonlinear dynamic robot manipulator, in presence of uncertainties. In order to provide high performance nonlinear methodology, sliding mode controller is selected. Pure sliding mode controller can be used to control of partly known nonlinear dynamic parameters of robot manipulator. Conversely, pure sliding mode controller is used in many applications; it has an important drawback namely; chattering phenomenon which it can causes some problems such as saturation and heat the mechanical parts of robot manipulators or drivers. In order to reduce the chattering this research is used the switching function in presence of mathematical error-based method instead of switching function method in pure sliding mode controller. The results demonstrate that the sliding mode controller with switching function is a model-based controllers which works well in certain and partly uncertain system. Pure sliding mode controller has difficulty in handling unstructured model uncertainties. To solve this problem applied mathematical model-free tuning method to sliding mode controller for adjusting the sliding surface gain (ë ). Since the sliding surface gain (ë) is adjusted by mathematical model free-based tuning method, it is nonlinear and continuous. In this research new ë is obtained by the previous ë multiple sliding surface slopes updating factor (á). Chattering free mathematical error-based tuning sliding mode controller is stable controller which eliminates the chattering phenomenon without to use the boundary layer saturation function. Lyapunov stability is proved in mathematical error-based tuning sliding mode controller with switching (sign) function. This controller has acceptable performance in presence of uncertainty (e.g., overshoot=0%, rise time=0.8 second, steady state error = 1e-9 and RMS error=1.8e-12).
This document discusses different control methods for vehicle lateral control, including classical control theory, modern control theory, fuzzy logic, sliding mode control, and neural networks. It develops a 2DOF bicycle model of a vehicle and uses pole placement control to design a lateral controller. Simulation results show the vehicle can track a reference input but with large overshoots in yaw rate and velocity. An improved controller is designed with slower response but smaller state variable fluctuations. Future work involves implementing the controller with an observer and designing longitudinal control.
Navigation and Trajectory Control for Autonomous Robot/Vehicle (mechatronics)Mithun Chowdhury
The document is a presentation about navigation and trajectory control for autonomous vehicles. It was presented by two students from the University of Trento in Italy.
The presentation introduces mobile robot design considerations including the interrelation between tasks, environments, kinematic models, path/trajectory planning, and high-level and low-level control. It explains that the robot task and environment must be identified first and the kinematic model selected based on this. Path planning is then needed to generate admissible trajectories that satisfy the kinematic constraints. High-level control executes tasks and trajectories while low-level control handles velocity commands.
It also explains concepts like holonomic and non-holonomic constraints, accessibility spaces, and maneuvers
Observer-based controller design and simulation for an active suspension systemTom Hemans
This document summarizes a study that designed and simulated an observer-based controller for an active suspension system. A quarter car model was created in Simulink to represent the active suspension. An observer-based controller using a Kalman filter was designed to estimate unmeasurable states and regulate the system response. Simulation results showed that the weighted RMS acceleration of the car body was reduced by 10.9% when traveling over a rough road, demonstrating the advantages of applying a Kalman filter to an active suspension system.
This document summarizes investigations into a fuzzy logic controller for a sensorless switched reluctance motor drive. It begins by introducing switched reluctance motors and their nonlinear characteristics. It then describes designing a fuzzy logic controller to estimate rotor position with minimum steady state error and good dynamic response. The controller implementation and numerical simulation results using Matlab/Simulink are presented. Simulation results at different speeds and loads demonstrate the controller's steady state performance and ability to respond robustly under different conditions. The conclusions are that the fuzzy logic controller enables effective operation of the switched reluctance motor drive with only small errors in all tested scenarios.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This document discusses using PI and PID controllers to control the vibration of a bus suspension system. It presents a quarter-bus model to simplify the suspension system to a single mass-spring-damper system. The open-loop response shows oscillations with a large settling time. To address this, closed-loop control with PI and PID controllers is proposed. The controllers use proportional, integral and derivative terms to increase response speed and eliminate steady state error from disturbances. Simulation results in MATLAB/Simulink will analyze and improve the bus suspension system response.
The developed control methodology can be used to build more efficient intelligent and precision mechatronic systems. Three degrees of freedom robot arm is controlled by adaptive sliding mode fuzzy algorithm fuzzy sliding mode controller (SMFAFSMC). This plant has 3 revolute joints allowing the corresponding links to move horizontally. Control of robotic manipulator is very important in field of robotic, because robotic manipulators are Multi-Input Multi-Output (MIMO), nonlinear and most of dynamic parameters are uncertainty. Design strong mathematical tools used in new control methodologies to design adaptive nonlinear robust controller with acceptable performance in this controller is the main challenge. Sliding mode methodology is a nonlinear robust controller which can be used in uncertainty nonlinear systems, but pure sliding mode controller has chattering phenomenon and nonlinear equivalent part in uncertain system therefore the first step is focused on eliminate the chattering and in second step controller is improved with regard to uncertainties. Sliding function is one of the most important challenging in artificial sliding mode algorithm which this problem in order to solved by on-line tuning method. This paper focuses on adjusting the sliding surface slope in fuzzy sliding mode controller by sliding mode fuzzy algorithm.
IRJET- A Performance of Hybrid Control in Nonlinear Dynamic Multirotor UAVIRJET Journal
This document summarizes a research paper that models and evaluates control techniques for multirotor unmanned aerial vehicles (UAVs). It begins with an abstract that outlines the paper's contributions: developing an accurate mathematical model of a multirotor UAV using Newton-Euler dynamics, developing nonlinear control algorithms based on this model, and comparing the performance of backstepping control, sliding mode control, and fuzzy logic control through simulation. The document then provides details of the multirotor dynamic model and each control approach, evaluating their ability to stabilize the system and reject disturbances. It concludes that hybrid control systems combining advantages of different methods should be considered.
FRACTIONAL-ORDER PROPORTIONALINTEGRAL (FOPI) CONTROLLER FOR MECANUM-WHEELED R...IAEME Publication
This study presents experimental implementation of fractional-order proportionalintegral
(FOPI) controller on a Mecanum-wheeled robot (MWR), which is a system with
nonlinearities and uncertainties, in performing tracking of a complex path i.e. ∞-shaped
path. The FOPI controller is almost as simpler as proportional-integral (PI) controller
and has supplementary advantage over PI controller due to its fractional integral. The
tracking performances of both the controllers are compared and evaluated in terms of
integral of absolute error (IAE), integral of squared error (ISE) and root-mean-square of
error (RMSE). Experimental result shows that the FOPI controller exhibits iso-damping
properties and successfully attains tracking with reduced error. Also, in this paper,
discretization of FOPI controller by using zero-order hold (ZOH) is discussed and
presented for the purpose of programming implementation on microcontroller board.
Besides that, graphical visualization of FOPI controller is presented to provide an insight
and intuitive understanding on the characteristic of the controller
This document compares the switching behaviors of field oriented control (FOC) and direct torque control (DTC) for induction motors. Experimental tests using a dSpace 1103 controller board show that under no load conditions, FOC produces less torque ripple than DTC. However, the switching frequency of the inverter for a FOC controlled motor is about 75% higher than for a DTC controlled motor. Therefore, DTC may be preferable when fast dynamic performance is critical, while FOC provides better torque quality.
For Induction motor is a system that works at their speed, nevertheless there are applications at which the speed operations are needed. The control of range of speed of induction motor techniques is available. The robust control is used with induction motor and the performance of the system with the controller will be improved. The mathematical model to the controller, which were coded in MATLAB. The modeling and controller will be shown by the conditions of robustness of be less than one.
Vehicle Dynamics and Drive Control for Adaptive Cruise VehiclesIRJET Journal
This document describes an adaptive cruise control system that uses hierarchical control architecture and PID/feedback controllers to maintain a desired distance and speed relative to a preceding vehicle.
The system uses a lower-level controller to compensate for nonlinear vehicle dynamics and track desired acceleration commands from an upper-level controller. The lower-level controller switches between a PID throttle controller and a feedback brake controller. Computer simulations validate that this hierarchical control approach enables the vehicle to accurately track the speed of the preceding vehicle and maintain the desired inter-vehicle distance.
Neural network based controllers design for nonlinear quarter car active susp...Mustefa Jibril
This document describes the design and simulation of a neural network controller for a nonlinear quarter car active suspension system. It presents the mathematical modeling of the suspension system and hydraulic actuator. Three controller designs are proposed - NARMA-L2, model reference, and predictive controllers. The controllers are designed and simulated in MATLAB/Simulink. The results show that the NARMA-L2 controller improved the car's performance in terms of ride comfort and road handling by the active suspension system.
This document discusses dilemma zone response at signalized intersections and presents a model for analyzing dilemma zone incursions using video image processing. It aims to determine if video image processing can be used to reduce clearance interval conflicts without reducing traffic signal efficiency. The document provides background on clearance intervals and dilemma zones. It then describes developing a model to classify vehicles approaching yellow and all-red intervals, calculate stopping distances, and compare these to distances from the stop line to identify potential dilemma zone incursions. The model results would help monitor driver responses and develop an algorithm to only consider situations where drivers attempted to stop.
MODELING AND DESIGN OF CRUISE CONTROL SYSTEM WITH FEEDFORWARD FOR ALL TERRIAN...csandit
This paper presents PID controller with feed-forward control. The cruise control system is one
of the most enduringly popular and important models for control system engineering. The
system is widely used because it is very simple to understand and yet the control techniques
cover many important classical and modern design methods. In this paper, the mathematical
modeling for PID with feed-forward controller is proposed for nonlinear model with
disturbance effect. Feed-forward controller is proposed in this study in order to eliminate the
gravitational and wind disturbance effect. Simulation will be carried out . Finally, a C++
program written and feed to the microcontroller type AMR on our robot
This summary provides the key details about the document in 3 sentences:
The document describes the design and implementation of a speedometer and speed controller for radio-controlled cars using inexpensive Hall effect sensors to measure speed. It details how the speedometer was validated using a motion capture system and how a PID controller was implemented to regulate the car's speed at a desired level based on feedback from the speedometer. Experimental results showed the speedometer measurements matched the motion capture system and the PID controller was able to regulate the car's speed accurately based on validation tests under no-load conditions.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Comparison of active and semi active suspension systems using robust controllerMustefa Jibril
1. The document compares active and semi-active suspension systems using robust H-infinity controllers. Mathematical models of quarter car active and semi-active suspension systems are developed.
2. Simulation results show that the active suspension system with H-infinity controller decreases body acceleration and maintains suspension deflection and body travel outputs, proving its effectiveness over the semi-active system.
3. Numerical results confirm that the active suspension system provides minimum body travel and acceleration amplitudes, while matching the suspension deflection to the road profile, achieving the control targets.
Fractional order PID for tracking control of a parallel robotic manipulator t...ISA Interchange
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 identification, design, and validation of control strategies. Identification 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.
The document discusses driverless, unattended metro systems as a solution that can satisfy the needs of both transit operators and passengers. It notes key operator needs like system availability, reliability, and cost savings, as well as passenger needs like short wait times, comfort, and safety. A driverless metro without on-board personnel is presented as a solution that meets all of these needs by allowing flexible operation, adjustable capacity, and lower maintenance costs while maintaining high performance, availability, and reliability. Examples are given of existing driverless metro lines in Copenhagen and their high levels of service availability over several years.
Methodology of Mathematical error-Based Tuning Sliding Mode ControllerCSCJournals
Design a nonlinear controller for second order nonlinear uncertain dynamical systems is one of the most important challenging works. This paper focuses on the design of a chattering free mathematical error-based tuning sliding mode controller (MTSMC) for highly nonlinear dynamic robot manipulator, in presence of uncertainties. In order to provide high performance nonlinear methodology, sliding mode controller is selected. Pure sliding mode controller can be used to control of partly known nonlinear dynamic parameters of robot manipulator. Conversely, pure sliding mode controller is used in many applications; it has an important drawback namely; chattering phenomenon which it can causes some problems such as saturation and heat the mechanical parts of robot manipulators or drivers. In order to reduce the chattering this research is used the switching function in presence of mathematical error-based method instead of switching function method in pure sliding mode controller. The results demonstrate that the sliding mode controller with switching function is a model-based controllers which works well in certain and partly uncertain system. Pure sliding mode controller has difficulty in handling unstructured model uncertainties. To solve this problem applied mathematical model-free tuning method to sliding mode controller for adjusting the sliding surface gain (ë ). Since the sliding surface gain (ë) is adjusted by mathematical model free-based tuning method, it is nonlinear and continuous. In this research new ë is obtained by the previous ë multiple sliding surface slopes updating factor (á). Chattering free mathematical error-based tuning sliding mode controller is stable controller which eliminates the chattering phenomenon without to use the boundary layer saturation function. Lyapunov stability is proved in mathematical error-based tuning sliding mode controller with switching (sign) function. This controller has acceptable performance in presence of uncertainty (e.g., overshoot=0%, rise time=0.8 second, steady state error = 1e-9 and RMS error=1.8e-12).
This document discusses different control methods for vehicle lateral control, including classical control theory, modern control theory, fuzzy logic, sliding mode control, and neural networks. It develops a 2DOF bicycle model of a vehicle and uses pole placement control to design a lateral controller. Simulation results show the vehicle can track a reference input but with large overshoots in yaw rate and velocity. An improved controller is designed with slower response but smaller state variable fluctuations. Future work involves implementing the controller with an observer and designing longitudinal control.
Navigation and Trajectory Control for Autonomous Robot/Vehicle (mechatronics)Mithun Chowdhury
The document is a presentation about navigation and trajectory control for autonomous vehicles. It was presented by two students from the University of Trento in Italy.
The presentation introduces mobile robot design considerations including the interrelation between tasks, environments, kinematic models, path/trajectory planning, and high-level and low-level control. It explains that the robot task and environment must be identified first and the kinematic model selected based on this. Path planning is then needed to generate admissible trajectories that satisfy the kinematic constraints. High-level control executes tasks and trajectories while low-level control handles velocity commands.
It also explains concepts like holonomic and non-holonomic constraints, accessibility spaces, and maneuvers
Observer-based controller design and simulation for an active suspension systemTom Hemans
This document summarizes a study that designed and simulated an observer-based controller for an active suspension system. A quarter car model was created in Simulink to represent the active suspension. An observer-based controller using a Kalman filter was designed to estimate unmeasurable states and regulate the system response. Simulation results showed that the weighted RMS acceleration of the car body was reduced by 10.9% when traveling over a rough road, demonstrating the advantages of applying a Kalman filter to an active suspension system.
This document summarizes investigations into a fuzzy logic controller for a sensorless switched reluctance motor drive. It begins by introducing switched reluctance motors and their nonlinear characteristics. It then describes designing a fuzzy logic controller to estimate rotor position with minimum steady state error and good dynamic response. The controller implementation and numerical simulation results using Matlab/Simulink are presented. Simulation results at different speeds and loads demonstrate the controller's steady state performance and ability to respond robustly under different conditions. The conclusions are that the fuzzy logic controller enables effective operation of the switched reluctance motor drive with only small errors in all tested scenarios.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This document discusses using PI and PID controllers to control the vibration of a bus suspension system. It presents a quarter-bus model to simplify the suspension system to a single mass-spring-damper system. The open-loop response shows oscillations with a large settling time. To address this, closed-loop control with PI and PID controllers is proposed. The controllers use proportional, integral and derivative terms to increase response speed and eliminate steady state error from disturbances. Simulation results in MATLAB/Simulink will analyze and improve the bus suspension system response.
The developed control methodology can be used to build more efficient intelligent and precision mechatronic systems. Three degrees of freedom robot arm is controlled by adaptive sliding mode fuzzy algorithm fuzzy sliding mode controller (SMFAFSMC). This plant has 3 revolute joints allowing the corresponding links to move horizontally. Control of robotic manipulator is very important in field of robotic, because robotic manipulators are Multi-Input Multi-Output (MIMO), nonlinear and most of dynamic parameters are uncertainty. Design strong mathematical tools used in new control methodologies to design adaptive nonlinear robust controller with acceptable performance in this controller is the main challenge. Sliding mode methodology is a nonlinear robust controller which can be used in uncertainty nonlinear systems, but pure sliding mode controller has chattering phenomenon and nonlinear equivalent part in uncertain system therefore the first step is focused on eliminate the chattering and in second step controller is improved with regard to uncertainties. Sliding function is one of the most important challenging in artificial sliding mode algorithm which this problem in order to solved by on-line tuning method. This paper focuses on adjusting the sliding surface slope in fuzzy sliding mode controller by sliding mode fuzzy algorithm.
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This document summarizes a research paper that models and evaluates control techniques for multirotor unmanned aerial vehicles (UAVs). It begins with an abstract that outlines the paper's contributions: developing an accurate mathematical model of a multirotor UAV using Newton-Euler dynamics, developing nonlinear control algorithms based on this model, and comparing the performance of backstepping control, sliding mode control, and fuzzy logic control through simulation. The document then provides details of the multirotor dynamic model and each control approach, evaluating their ability to stabilize the system and reject disturbances. It concludes that hybrid control systems combining advantages of different methods should be considered.
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This study presents experimental implementation of fractional-order proportionalintegral
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nonlinearities and uncertainties, in performing tracking of a complex path i.e. ∞-shaped
path. The FOPI controller is almost as simpler as proportional-integral (PI) controller
and has supplementary advantage over PI controller due to its fractional integral. The
tracking performances of both the controllers are compared and evaluated in terms of
integral of absolute error (IAE), integral of squared error (ISE) and root-mean-square of
error (RMSE). Experimental result shows that the FOPI controller exhibits iso-damping
properties and successfully attains tracking with reduced error. Also, in this paper,
discretization of FOPI controller by using zero-order hold (ZOH) is discussed and
presented for the purpose of programming implementation on microcontroller board.
Besides that, graphical visualization of FOPI controller is presented to provide an insight
and intuitive understanding on the characteristic of the controller
This document compares the switching behaviors of field oriented control (FOC) and direct torque control (DTC) for induction motors. Experimental tests using a dSpace 1103 controller board show that under no load conditions, FOC produces less torque ripple than DTC. However, the switching frequency of the inverter for a FOC controlled motor is about 75% higher than for a DTC controlled motor. Therefore, DTC may be preferable when fast dynamic performance is critical, while FOC provides better torque quality.
For Induction motor is a system that works at their speed, nevertheless there are applications at which the speed operations are needed. The control of range of speed of induction motor techniques is available. The robust control is used with induction motor and the performance of the system with the controller will be improved. The mathematical model to the controller, which were coded in MATLAB. The modeling and controller will be shown by the conditions of robustness of be less than one.
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This document describes the design and simulation of a neural network controller for a nonlinear quarter car active suspension system. It presents the mathematical modeling of the suspension system and hydraulic actuator. Three controller designs are proposed - NARMA-L2, model reference, and predictive controllers. The controllers are designed and simulated in MATLAB/Simulink. The results show that the NARMA-L2 controller improved the car's performance in terms of ride comfort and road handling by the active suspension system.
This document discusses dilemma zone response at signalized intersections and presents a model for analyzing dilemma zone incursions using video image processing. It aims to determine if video image processing can be used to reduce clearance interval conflicts without reducing traffic signal efficiency. The document provides background on clearance intervals and dilemma zones. It then describes developing a model to classify vehicles approaching yellow and all-red intervals, calculate stopping distances, and compare these to distances from the stop line to identify potential dilemma zone incursions. The model results would help monitor driver responses and develop an algorithm to only consider situations where drivers attempted to stop.
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system is widely used because it is very simple to understand and yet the control techniques
cover many important classical and modern design methods. In this paper, the mathematical
modeling for PID with feed-forward controller is proposed for nonlinear model with
disturbance effect. Feed-forward controller is proposed in this study in order to eliminate the
gravitational and wind disturbance effect. Simulation will be carried out . Finally, a C++
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This summary provides the key details about the document in 3 sentences:
The document describes the design and implementation of a speedometer and speed controller for radio-controlled cars using inexpensive Hall effect sensors to measure speed. It details how the speedometer was validated using a motion capture system and how a PID controller was implemented to regulate the car's speed at a desired level based on feedback from the speedometer. Experimental results showed the speedometer measurements matched the motion capture system and the PID controller was able to regulate the car's speed accurately based on validation tests under no-load conditions.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Comparison of active and semi active suspension systems using robust controllerMustefa Jibril
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2. Simulation results show that the active suspension system with H-infinity controller decreases body acceleration and maintains suspension deflection and body travel outputs, proving its effectiveness over the semi-active system.
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Adaptive Cruise Control System for Vehicle Using Model Predictive Control Alg...IRJET Journal
This document describes research on developing an adaptive cruise control system for vehicles using a model predictive control algorithm. It begins with an abstract that introduces adaptive cruise control and model predictive control. It then provides background on adaptive cruise control and how model predictive control is an advanced version of feedforward control that can predict future states and handle constraints. The document outlines the proposed adaptive cruise control system, which uses model predictive control and includes subsystems for vehicle acceleration dynamics, collision detection, and lane changing functions. It describes modeling the vehicle acceleration dynamics and the three operating modes of the adaptive cruise control system: free driving, vehicle following, and emergency braking. Finally, it discusses how the system was designed and simulated in MATLAB.
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This paper presents PID controller with feed-forward control. The cruise control system is one of the most enduringly popular and important models for control system engineering. The system is widely used because it is very simple to understand and yet the control techniques cover many important classical and modern design methods. In this paper, the mathematical modeling for PID with feed-forward controller is proposed for nonlinear model with disturbance effect. Feed-forward controller is proposed in this study in order to eliminate the gravitational and wind disturbance effect. Simulation will be carried out . Finally, a C++ program written and feed to the microcontroller type AMR on our robot
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1) The document describes the design of optimal and robust controllers for a quarter car active suspension system using LQR and μ-synthesis control methods.
2) Mathematical models of the quarter car system and various road disturbances are presented.
3) LQR and μ-synthesis controllers are designed in MATLAB and tested on the quarter car model under different road disturbances to maximize ride comfort and handling.
4) Simulation results show the effectiveness of the active suspension system with the μ-synthesis controller.
Quarter car active suspension systemdesign using optimal and robust control m...Mustefa Jibril
1) The document describes the design of optimal and robust controllers for a quarter car active suspension system using LQR and μ-synthesis methods.
2) Mathematical models of the quarter car system and various road disturbances are presented.
3) LQR and μ-synthesis controllers are designed in MATLAB and tested on the quarter car model under different road disturbances to maximize ride comfort and handling.
4) Simulation results show the effectiveness of the active suspension system with the μ-synthesis controller.
Quarter car active suspension systemdesign using optimal and robust control m...Mustefa Jibril
This document describes the design of optimal and robust controllers for a quarter car active suspension system. It first presents the mathematical model of a quarter car system and describes various road disturbances that could be used as inputs, including bumps, random variations, sine waves, and white noise. Then it details the design of a μ-synthesis controller using robust control methods and an LQR controller using optimal control methods. Various performance metrics are evaluated through simulation against the different road disturbances. The results show that the active suspension system with a μ-synthesis controller provides the best overall performance compared to the LQR controller design.
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This document discusses the design of optimal and robust controllers for a quarter car active suspension system. It first introduces the mathematical model of a quarter car system and describes different types of road disturbances that are used as inputs. Then it presents the design of a μ-synthesis controller and LQR controller for the active suspension system. The μ-synthesis controller accounts for uncertainty in the hydraulic actuator dynamics. The LQR controller is designed to minimize a quadratic cost function and provide optimal control gains. Finally, the controllers are simulated and evaluated using MATLAB.
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Simulation design of trajectory planning robot manipulatorjournalBEEI
Robots can be mathematically modeled with computer programs where the results can be displayed visually, so it can be used to determine the input, gain, attenuate and error parameters of the control system. In addition to the robot motion control system, to achieve the target points should need a research to get the best trajectory, so the movement of robots can be more efficient. One method that can be used to get the best path is the SOM (Self Organizing Maps) neural network. This research proposes the usage of SOM in combination with PID and Fuzzy-PD control for finding an optimal path between source and destination. SOM Neural network process is able to guide the robot manipulator through the target points. The results presented emphasize that a satisfactory trajectory tracking precision and stability could be achieved using SOM Neural networking combination with PID and Fuzzy-PD controller.The obtained average error to reach the target point when using Fuzzy-PD=2.225% and when using PID=1.965%.
Modeling and simulation of vehicle windshield wiper system using h infinity l...Mustefa Jibril
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wiping speed by tracking a reference speed signals. The reference speed signals used in this paper are step and sine
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effectiveness of the proposed H Loop Shaping controller to improve the wiping mechanism for the given two
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The document summarizes the modeling and control of an automobile cruise control system. It develops a mathematical model that relates the velocity of the car to the throttle setting and slope of the road. A PI controller is designed using this model to maintain a constant velocity even when the road slope changes. Parameters for the PI controller are selected to provide critical damping and a response speed that balances minimizing velocity errors with smooth control signals. Simulation results demonstrate the cruise control system can effectively maintain the desired velocity when the road slope changes compared to an open loop system without control.
A Much Advanced and Efficient Lane Detection Algorithm for Intelligent Highwa...cscpconf
This paper presents a much advanced and efficient lane detection algorithm. The algorithm is based on (ROI) Region of Interest segmentation. In this algorithm images are pre-processed by top-hat transform for de-noising and enhancing contrast. ROI of a test image is then extracted. For detecting lines in the ROI, Hough transform is used. Estimation of the distance between Hough origin and lane-line midpoint is made. Lane departure decision is made based on the difference between these distances. As for the simulation part we have used Matlab software.Experiments show that the proposed algorithm can detect the lane markings accurately and quickly.
A Much Advanced and Efficient Lane Detection Algorithm for Intelligent Highwa...
REU spring 2016
1. Path Following Control for Experimental Used Car-like Robots†
Zhenyuan Yuan1
Abstract— This paper presents a method of path following for
a car-like robot in an indoor setting using real-time feedback
from motion capture system. In particular, we implement a
modified version of Proportional Control for path following.
The major difficulty of the problem is due to the car’s non-
holonomic motion, which makes path following very difficult
due to the differential constraint so that the car cannot go
sideway. Path following is eventually realized by taking a linear
combination of the proportional gains over cross-track error
and heading error. The method has been experimentally tested
on a laboratory-scale car-like robot in an indoor environment.
The state feedback for the car is provided by a high-fidelity real-
time motion capture system which can provide high-frequency
feedback on the position, velocity as well orientation of the car.
The finally tuned controlled is tested on several paths (e.g.,
straight paths, paths composed of two parallel lines to simulate
the urban driving scenario of lane switching, etc.).
I. INTRODUCTION
Research on motion planning algorithm is experiencing a
tremendous growth recently in the field of autonomous cars.
These motion planning algorithms, such as Rapidly exploring
Random Tree (RRT) in [1] and the multi-robot motion
algorithm in [2], are planning algorithm that determines the
output according to the state of the robot. After the path
in generated, the vehicles need to follow the designated path
through a close loop so that the whole autonomy is achieved.
Path following for car-like robots becomes a complicated
issue because of the car’s non-holonomic motion, and thus
it is usually implemented through rather complicated al-
gorithm, in which the heavy computation requires, even
though provides accurate regulation, slows down the speed
of processing as well as requires high-fidelity on-board
hardware setup. In our lab, motion planning algorithm is
also the topic under research, and we need to verify the
algorithm through experiments on car-like robots by path
following. In order to keep the experiments cost-effective
while keeping the dynamics of cars, we use 1/10 Radio-
Controlled (RC) car as experimental-used car-like robot and
aims to keeps the cost of other setup as low as possible
so that the platform can be replicated easily for future use.
Thus in this paper, a computational-ease steering controller
is proposed to implement on car-like robots so that the
autonomous platform is kept at low cost but retains good
performance in following the path.
A lot of path following control researches are done in
theory but rarely implemented in experiment. Breaking the
†This work is supported by Networked Robotic Systems Lab from
Department of Mechanical and Nuclear Engineering, University Park.
1Zhenyuan Yuan is with department of Electrical Engineering,
The Pennsylvania State University, University Park, PA. 16802 USA.
zqy5086@psu.edu
path needed to follow into points and computing outputs
for the car with respect to the closest point as in [3] and
[4] theoretically fit our laboratory environment very well,
but the theory had only been simulated in software, and
there are a lot of realistic conditions, such as transmission
delay, computation capacity of the on board processor and
the steering accuracy, had not been taken into account.
Existing path following algorithm like [5], even though is
proved to be valid, is too computationally heavy, which
is unfeasible to be implemented on the microprocessor as
Arduino Uno on the car-like robots in our lab. Algorithm
developed in the experiment of car parking control using a
path controller in [6] seems to be a solution to the problem;
however, this algorithm is an adoption of control algorithm
for a two wheeled mobile robot. It is applicable on car-like
robots for motions on curvature such as parking, but when
it turns to urban driving scenarios such as lane following
switching and right angle turning where the non-holonomic
motion constraint becomes effective, the controller goes
highly unstable as it will be shown in the experiment section.
PID (Proportional-Integral-Derivative) controller was first
introduced in 1936, when Nicolas Minorsky was designing
a control algorithm for the automated steering on the ships
to avoid the disturbance force from distracting the ship from
the desired course [7]. As shown in Fig. 1, PID controller
implement proportional, integral and derivative operations
on an error between the output and the desired input so
that the output can be maintained at the desire level. PID
controller is now usually used in feedback loop and acts as
a method of regulation, such as regulating temperature and
pressure [8]. Similarly, PID controller is suitable for real-
time speed control of electric motors as demonstrated in [9]
and [10]. In [11], PID controller is used in steering control
for car following taking the feedback as relative position
with respect to the leading car. Similarly, PID controller
can also be used to address heading error between the
car and the reference path as well as the cross-track error
so that the computation is much relieved compared to the
transformations in [5].
In this paper, a path is given and a modification of PID
controller is presented as a method of path following for
car-like robots. The general function for PID controller is as
in Fig. 1. But for this project,instead of taking one source
of error, the new version of the controller, inspiring from
the theory in [3], takes a linear combination of proportional
control on two sources of error, heading error and cross-
track error, while remaining economical in computation. In
the rest of the paper, hardware setup and the function of
controller are explained in section II. The non-holonomic
2. Fig. 1.
Fig. 2. PID controller
system is analyzed in section III. In section IV, simulations
of different designs of the controller are displayed. In section
V, experimental validation of the successful controller is
presented, and conclusion is drawn in section VI.
II. HARDWARE SETUP AND THE CONTROLLER
An overview of the project is shown in Fig. 3. The car
used in the project is a 1/10 EXCEED RC 2.4GHz Electric
Infinitive RTR Off Road Truck. The parts original from the
car used in the project is the motor and the steering servo.
The Electronic Speed Control (ESC) is replaced by an off-
the-shelf motor driver. A platform is built upon the car in
order to hold the designed hardwares to satisfy the project
objective. As shown in Fig. 4, the stacks of the boards make
up the center of control for the car. Beginning from the top of
the layer is the circuit for steering control that is connected
to the steering servo. The steering servo is controlled by the
Pulse-Width-Modulation (PWM) signal sent from Arduino,
which is the control signal of the controller so that the output
of the steering can keep the car on the path. The second
layer is the motor driver. The third layer is equipped with
Bluetooth for transmission. The bottom one is the Arduino,
which is the microcontroller of the system that actuate the
car.
The proposed controller has its block diagram shown in
Fig. 2. The designated path specifies the line location as well
as the direction the car should go. Taking these two setpoints
as input, regulation is implemented on the cross-track error
and the heading error, which are the distance between the car
and the path and the difference between the path direction
and the car’s orientation, respectively. Then different gains
are implemented on the two errors to output an appropriate
PWM signal to the steering servo for steering adjustment so
that the can can converge to the designated path.
III. NON-HOLONOMIC MOTION CONSTRAINT
Throughout the whole control problem, the inherent non-
holonomic motion constraint of the car-like robot is proved
to be the most challenging part. The configuration of car-like
robots can be modeled as in Fig. 5, where the rear wheels are
fixed and always pointing to the moving direction. Since the
car-like robot in the experiment is usually run at low speed
as 50 cm/s, the assumptions of non-slipping motion and non-
sideway motion hold very well in the model but become the
most difficult part to overcome in order to converge to the
designated path. As explained in [1], using the same notation
in Fig. 5 the motion of the car is described by the following
equations:
˙x = us cosθ (1a)
˙y = us sinθ (1b)
˙θ =
us
L
tanuφ (1c)
where x,y are the coordinates in the imaginary plane and
θ is polar angle of the plane. These equations show that the
motion of the car is related to the speed and the steering
angle as well as limited by the maximum curvature when
it is turning. Thus, the error of the car in path following is
described by two parameters, the distance from the desired
path and orientation error. This makes it difficult when
applying the traditional PID controller because it is usually
implement on one dimensional error, whereas the error in
this problem is two dimensional. It becomes even more
difficult when the real world disturbance factors such as
communication delay, differential gearing and surface fiction
are introduced into the system.
IV. SIMULATION
The purposed algorithm, taking the combination of cross-
track error and the heading error as the input of the
controller, is simulated in MATLAB before being carried
out in experiment. The main purposes of simulations are
mimicking the behavior of the non-holonomic motion at
different situation, tuning and foreshadowing the gains in
actual experiment. As shown in Fig. 6, the simulations are
run on a designated square in the same dimension of the
testbed, the car is represented by a point but retaining the
car features such as car length and maximum steering angl
while its motion is simulated by the equations (1) and the
designated path is assigned by the four corner points, denoted
Fig. 3. Project overview
3. Fig. 4. Layers of circuit boards on top of the car platform
Fig. 5. Simple Car Model (source: [1])
as (x1,y1),(x2,y2),(x3,y3),(x4,y4), and the equation of the
line is followed by line equation
Ax+By+C = 0
in which
A = yj −yj+1
B = xj+1 −xj
C = xjyj+1 −xj+1yj
j is incremented when the car is getting close to the end point
of the line, in this case is 450 mm, to provide a smooth corner
turning. The calculation of the errors and the drawbacks of
using only either one of them are explained in the following
subsection.
A. CROSS-TRACK ERROR CALCULATION
Cross-track error was used as an input for PID controller,
which is the distance between the car and the designated
path, and the PID controller is adjusting output in order to
minimize this error. The cross-track error e(t)d related to
time is directly calculated as point-to-line distance as
e(t)d = (−1)sign(Ax+by+c)
|Ax+by+c|
√
A2 +B2
Fig. 6. Designated Trajectory in Simulation
Fig. 7. Simulation on cross-track error with optimal condition
in which, x and y are the corresponding coordinates of the
car, and the sign function is used to determined the side the
steering should turn. The steering servo functions within the
PWM signal input range from 1000 to 2000: at 1500 PWM
signal input, the steering stays straight, and the steering turns
right when the input is higher than 1500 and turns left when
it is lower.
The condition is very limited in order for the car to behave
well by taking only the cross-track error as the feedback input
for PID controller. This algorithm only works when the car
is running at low speed under minimal communication delay
and small initial offset. Successful simulation is shown in
Fig. 7, when the car speed is set at 500 mm/s, communication
delay as low as 0.05 s and is started off very close to the
designated path. When the car is run at higher or greater
communication delay in the simulation, the system becomes
as unstable as shown in Fig.8.
B. HEADING ERROR CALCULATION
The major drawback of using only cross-track error for
regulation is that it does not take the orientation into account,
which results in the misalignment between the car’s heading
and the path’s direction even though the car is right on the
track, and therefore the error is not reduced even though
the cross-track error is zero. The heading error is calculated
through the comparison between the heading direction and
the direction of the designated line. The PID controller taking
this error as input is trying to force the car to head in the same
direction as the designated path so the oscillatory motion can
4. Fig. 8. Simulation on cross-track error with nonideal condition
Fig. 9. Simulation on heading error
be avoided. The heading error e(t)h is calculated as
e(t)h = (−1)sign(θ −γ)(1−cos(θ −γ))
where θ is the heading angle of the car in the polar
coordinate system, and γ is the angle of the path. The sign
is used for indicating the side the steering should turn, the
same principle as in last subsection. The term 1−cos(θ −γ)
is for limiting the difference within the range -1 to 1 so that
the tunning process is easier.
As shown in Fig. 9, with only heading error for regulation,
the car cannot be turned back into the line once it is off since
the algorithm only makes the car goes in the same direction
as the path.
C. COMBINATION OF CROSS-TRACK ERROR AND
HEADING ERROR
Obviously, regulation using cross-track error and regu-
lation using heading error are complement to each other.
When merging the two error calculation methods together,
the drawbacks of both methods are complemented by the
advantages of the other. As it turns out, when taking the
linear combination of the two types of error, the car is
regulated to follow the direction of the path as a result of
the heading error, and it tends to converge back to the line
when it is off as the cross-track error is in effect. Simulation
result can seen in Fig.10, and through the simulation, the
new algorithm is more tolerable to the range of speed and
communication delay. The error of the combination e(t) is
calculated as
Fig. 10. Simulation taking the combinatio of both cross-track error and
heading error
e(t) = Ae(t)d +Be(t)h
where A and B are the gains for cross-track error and
heading error, respectively. The gain of the heading error is
set as large as 1970 to keep the car move in a proper direction
while the gain of the cross-track error is set as low as 0.028
so that the car can converge back to the line when it is off
but the unstable behavior as shown in Fig. 8 is negligible.
V. EXPERIMENT
The proposed algorithm is tested in experiments equipped
with indoor motion capture system, Vicon, which provides
position information that can be translated to Cartesian
coordinate to MATLAB[12], as shown in Fig. 11. Through
the same Cartesian coordinate system, designated path in
located through code in MATLAB, which also communicate
position information with Vicon. As shown in the lane-
switching scenario in Fig. 15, which is a good representation
for path following, the path designed for the car to complete
lane-switching motion is in Fig. 12 by MATLAB. The car,
running at low speed, started from the bottom right corner
in Fig. 13 with offset by purpose. As captured by Vicon,
the car trajectories are shown in Fig. 13 and Fig. 14. The
dots that are out of the continuous car path is due to the
noise of Vicon. Fig. 14 is the resulted plot when using only
cross-track error as an input for the controller; it is highly
unstable because of the non-holonomic motion constrain. On
the other hand, the algorithm using the combination of cross-
track error and heading error gives rise to stable control and
smooth performance in Fig. 13. Because of the transmission
defect, the car cannot fully converge to the path even though
the command is instructing to on the left top corner in
Fig. 13, but compared the scale in the figure with the car
dimension (39*30*14 cm3), the deviation is negligible. In the
end, the gains tuned for the controller in actual experiment
are 3050 for heading error and 0.225 for cross-track error.
VI. CONCLUSIONS
The main contribution of this paper is an steering control
algorithm for autonomous car path following in urban sce-
nario. The algorithm was validated in experiments, where the
desired performance is satisfying given the non-holonomic
5. Fig. 11. Vicon motion capture system
Fig. 12. Designated tracjectory in experiment
Fig. 13. Experiment in lane-swtiching scenario
Fig. 14. Car behavior using only cross-track error as input
Fig. 15. Lane-switching scenario
motion constrained. Experiments are held with the car start-
ing off close to the designated path without opposite heading
due to the space limitation as well as the desire to have the
car converge quickly to the path, but these assumptions hold
well since motion planning algorithm would generate path
starting from the car’s current position and heading. This
algorithm is proved to be valid for path following section
under motion planning , so in the coming research on-
board computer (NVIDIA Jetson TK-1) will be embedded
on the car-like robots to execute on-board motion planning
as well as minimize communication defect and integrate with
sensors. In this way, the car, according to the motion planning
algorithm developed in the lab, will be able to generate and
follow a path on its own for a given task, achieving the full
autonomy.
ACKNOWLEDGMENT
This work is supported by Networked Robotic Systems
Lab from Department of Mechanical and Nuclear Engineer-
ing, supported by Dr. Asok Ray. The author would also thank
for the supervision from Dr. Minghui Zhu and the assistance
and guidance provided by graduate student, Nurali Virani
and Devesh Jha.
REFERENCES
[1] S. M. LaValle, Planning algorithms. Cambridge university press, 2006.
[2] D. K. Jha, M. Zhu, and A. Ray, “Game theoretic controller synthesis
for multi-robot motion planning-part ii: Policy-based algorithms,”
IFAC-PapersOnLine, vol. 48, no. 22, pp. 168–173, 2015.
[3] R. DeSantis, “Path-tracking for car-like robots with single and double
steering,” Vehicular Technology, IEEE Transactions on, vol. 44, no. 2,
pp. 366–377, 1995.
6. [4] P. Encarnac¸ao and A. Pascoal, “Combined trajectory tracking and path
following: an application to the coordinated control of autonomous
marine craft,” in Decision and Control, 2001. Proceedings of the 40th
IEEE Conference on, vol. 1, pp. 964–969, IEEE, 2001.
[5] C. Samson, “Control of chained systems application to path following
and time-varying point-stabilization of mobile robots,” Automatic
Control, IEEE Transactions on, vol. 40, no. 1, pp. 64–77, 1995.
[6] K. Lee, D. Kim, W. Chung, H. W. Chang, and P. Yoon, “Car parking
control using a trajectory tracking controller,” in SICE-ICASE, 2006.
International Joint Conference, pp. 2058–2063, IEEE, 2006.
[7] N. Minorsky, “Steering of ships,” 1984.
[8] J. Bechhoefer, “Feedback for physicists: A tutorial essay on control,”
Reviews of Modern Physics, vol. 77, no. 3, p. 783, 2005.
[9] H.-B. Shin and J.-G. Park, “Anti-windup pid controller with integral
state predictor for variable-speed motor drives,” Industrial Electronics,
IEEE Transactions on, vol. 59, no. 3, pp. 1509–1516, 2012.
[10] J. Tang, “Pid controller using the tms320c31 dsk with online parameter
adjustment for real-time dc motor speed and position control,” in In-
dustrial Electronics, 2001. Proceedings. ISIE 2001. IEEE International
Symposium on, vol. 2, pp. 786–791, IEEE, 2001.
[11] T. Sangyam, P. Laohapiengsak, W. Chongcharoen, and
I. Nilkhamhang, “Path tracking of uav using self-tuning pid
controller based on fuzzy logic,” in SICE Annual Conference 2010,
Proceedings of, pp. 1265–1269, IEEE, 2010.
[12] Vicon Tracker User Guide, May 2015.