TWIP Control
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This document describes the control system for balancing a two-wheeled inverted pendulum robot, such as a Segway. It discusses using a mathematical model and state space equations in a model-based controller or a physical model and PID controller in an error-based controller. It then describes the hardware implementation using an Arduino, accelerometer, encoder, and DC motor to read sensor values, calculate angle and velocity, and provide feedback control to balance the robot.
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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.
07
This document describes the design of an operational amplifier (op-amp) with specific gain and slew rate specifications. The design process involves choosing an architecture, then designing the transistor sizes and compensation network. An existing two-stage op-amp architecture is adapted. Transistor widths and lengths are calculated to meet the gain of 20,000 V/V and slew rate of 20 MV/sec. The schematic is drawn and simulated. The output is as expected but cannot drive the load, so an output buffer is added to minimize delay for larger loads.
Ppt (2)
This document describes a vehicle speed and distance monitoring system that uses a reed switch and magnet on the wheel to send pulses to a microcontroller. The microcontroller counts pulses to calculate speed in km/hr and distance traveled. It displays these readings on an LCD and stores them in EEPROM memory. The system provides accurate digital readings of speed and distance that are easy for users to understand.
Ppt (2)
This document describes a vehicle speed and distance monitoring project. It uses a reed switch and magnet on the wheel to sense revolutions and send pulses to a microcontroller. The microcontroller counts pulses to calculate speed in km/h and distance traveled, displaying results on an LCD. It is accurate compared to analog meters, reliable due to the microcontroller, and can easily be built and installed on vehicles.
ELEN601_Project
1) The document describes a circuit designed to implement adaptive voltage scaling. It uses a ripple carry adder, frequency monitor, and voltage scaling logic.
2) Simulation results show the adder's frequency is 125MHz at 3.3V and 40MHz at 1V. The frequency monitor uses a binary counter to measure the adder's speed.
3) Rather than scaling voltage based on frequency, the final implementation scales voltage according to an input mode selection. Running simulations for different modes shows how supply voltage and adder speed vary.
Motorized pan tilt(Arduino based)
This document describes a project to control a pan-tilt mechanism using an accelerometer and Arduino. An ADXL345 accelerometer measures tilt and sends acceleration data to an Arduino Uno microcontroller. The Arduino controls the position of two servo motors attached to a pan-tilt platform based on the accelerometer's readings, allowing motion control through gesture. Code is provided to interface the accelerometer with the Arduino and map acceleration values to servo positions for a motorized pan-tilt camera platform.
Servo 2.0
Institute of infrastructure technology research and management (IITRAM) Ahmedabad. This is the project report given to us in the control sytem lab. This is basically a Servo postion control. Here we are using PID controller.
pwm for speed control
presentation was regarding speed control of dc motor using pulse width modulation techniques without wastage of power.
Light intensity/incident angle measurement.pptx
This prototype aims to measure the angle at which light intensity is at its maximum using an Arduino Uno, an LDR (Light Dependent Resistor), and an MPU6050 module. The project leverages the Arduino Uno's capabilities to interface with these components and gather the required data. The LDR is utilized to sense the ambient light intensity, employing a voltage divider circuit to translate it into an analog voltage. The MPU6050 module, equipped with a gyroscope and accelerometer, provides orientation information such as roll, pitch, and yaw angles. The project's main focus lies in determining the angle at which the light intensity reaches its peak.
The Arduino code facilitates the coordination of these components. It initializes both the LDR and MPU6050 in the setup function, capturing analog data from the LDR and orientation data from the MPU6050. By continuously integrating the gyroscope readings, the Arduino calculates and updates the orientation angles over time. Mapping the LDR's analog values to representative light intensity levels enhances the correlation between the orientation angles and the corresponding light intensities.
As a result, this project underscores the connection between physical orientation and environmental conditions. Through the data collected, users can identify the angle at which light intensity reaches its maximum, potentially offering insights into optimal lighting conditions for specific applications. The project's output, displayed via the Arduino's serial monitor, provides a real-time view of the relationship between orientation angles and light intensity, contributing to a more nuanced understanding of environmental interactions.
Design Calculation of Three Phase Self Excited Induction Generator Driven by ...
This document discusses the design calculation of a three-phase self-excited induction generator driven by a wind turbine. It presents the dq-modeling approach for transient state analysis of the induction generator and includes calculations of total impedance regulation, required capacitance for excitation, efficiency, and torque required to drive a 3.6 kW induction generator. The calculations are based on parameters of the 3.6 kW generator including stator and rotor resistances and inductances. Equivalent circuits are presented and curves of total impedance, capacitance, and efficiency versus slip are shown based on simulations in Matlab. The generator is most efficient when operating between slip values of -0.055 and -0.1, corresponding to rotor speeds of
Unity power factor control by pwm rectifier
Abstract This paper analyzes the principle of PWM rectifier and presents a unity power factor control method of PWM rectifier. Controller used double closed-loop PI control, which inner uses three-phase input current control method controlled by unity power factor and outer controls the output DC voltage of rectifier. Voltage phase detection methods which proposed could eliminate the affection of the voltage harmonics on phase detection accuracy. The result of the simulation and experiment verify the feasibility and effectiveness of the method. Keywords- PWM, rectifier, unity power factor, filter
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TWIP Control
- 1. Two Wheel Inverted Pendulum Control Hongtao Gu
- 2. 1. Introduction Segway is a commercial application of the inverted pendulum. https://www.groupon.com/deals/segway-of-richmond-8
- 3. 2. Approach 1. Model Based Controller Mathematical Model (State Space) Feedback Gain 𝑥 ሶ𝑥 𝜃 ሶ𝜃 State Space Equation: ሶ𝑥 = 𝐴𝑥 + 𝐵 𝑦 = 𝐶𝑥 + 𝐷 0 1 0 0 0 −0.006844 16.6194 0 0 0 0 1 0 −0.00053 234.8387 0 A= 0 161.0343 0 1248.9 B= 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 C= 0 0 0 0 D= [−31.6228 −92.1359 141.9806 11.9917]K=
- 4. 2. Approach 2. Error Based Controller Physical Model PID Error= target 𝜃 – actual 𝜃
- 5. 3. Implementation For balancing the system, 4 states value should be read by the controller. Accelerometer will output different voltage with respect to different acceleration. Encoder will read the rotational speed voltage signal. Labview will convert the voltage signal to the physical signal. Labview will also add a feedback gain on the 4 states. Physical Model Arduino Uno Accelerometer Encoder DC Motor
- 6. ADXL335 3-axis accelerometer Output Range -3~3 g Nonlinearity -0.3~0.3% SENSITIVITY 300 (270~ 330)mV/g Magnetic Encoder Channel A, B Pulse/Rev 3 Pulses/Channel 4. Hardware Arduino Uno Digital I/O 14 Pins Analog Input 6 Pins AI Resolution 10 bits Clock Speed 16MHz
- 7. 4. Read Angle and Angular Velocity Angle and Angular Velocity Z Y 𝜽 Sensor Calibration Read the two voltage signal when Z axis is same or opposite direction with gravity to get sensitivity. Z 1/m +1g -1g Delta_V Sensitivity z 1.308594 1.962891 0.654297 327.1485 y 1.264648 1.914062 0.649414 324.707 Read the voltage signal when Z axis is horizontal to compensate the 0 gravity. b 0-g y 1584.66 z 1613.57 𝜃 = atan( 𝑧 𝑦 ) Angular Velocity Averaging 4000 Hz 20 Samples y=m*x+b
- 8. 5. Read Encoder Motor RPM 3 pulses per revolution DC Motor Max Output RPM 200 RPM Gear Ratio 150:1 Encoder Pulses/s at maximum motor speed: = 200 RPM * Gear Ratio* 3 pulses/Rev= 1500 pulses/s Sampling Frequency >= 2 * 1500 Pulses/s = 3000 Hz The max Fs is 5000 Hz for Arduino, so 4000 Hz frequency is used. 𝑅𝑃𝑆 = σ 𝑅𝑖𝑠𝑖𝑛𝑔 𝐸𝑑𝑔𝑒 𝑆𝑎𝑚𝑝𝑙𝑖𝑛𝑔 𝑡𝑖𝑚𝑒 Displacement = σ (Rotation Speed ∗ Loop Time)
- 10. Reference [1] ADXL335:https://www.sparkfun.com/datasheets/Components/SMD/adxl335.pdf [2] Magnetic Encoder: https://www.pololu.com/product/3081 [3] Arduino Uno: https://www.arduino.cc/en/Main/ArduinoBoardUno [4] Bageant/Massachusetts Institute of Technology, M. R. (2011). DSpace@MIT: Balancing a two- wheeled Segway robot. Retrieved from https://dspace.mit.edu/handle/1721.1/69500 [5] Khaled/Technische Universitat Munchen, M. (2009, July). Balancing a Two Wheeled Robot (PDF Download Available). Retrieved from http://www.researchgate.net/publication/252629451