scholarly journals Comparative Study of DE, PSO and GA for Position Domain PID Controller Tuning

2021 ◽  
Author(s):  
Puren Ouyang ◽  
Vangjel Pano
Keyword(s):  
Performance Improvement ◽  
Pid Controller ◽  
Robotic Manipulators ◽  
Tracking Performance ◽  
Contour Tracking ◽  
Fitness Functions ◽  
Performance Indexes ◽  
Pid Controller Tuning ◽  
Optimal Gains ◽  
Better Than

Gain tuning is very important in order to obtain good performances for a given controller. Contour tracking performance is mainly determined by the selected control gains of a position domain PID controller. In this paper, three popular evolutionary algorithms are utilized to optimize the gains of a position domain PID controller for performance improvement of contour tracking of robotic manipulators. Differential Evolution (DE), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) are used to determine the optimal gains of the position domain PID controller, and three distinct fitness functions are also used to quantify the contour tracking performance of each solution set. Simulation results show that DE features the highest performance indexes for both linear and nonlinear contour tracking, while PSO is quite efficient for linear contour tracking. Both algorithms performed consistently better than GA that featured premature convergence in all cases.

scholarly journals Comparative Study of DE, PSO and GA for Position Domain PID Controller Tuning

2021 ◽  
Author(s):  
Puren Ouyang ◽  
Vangjel Pano
Keyword(s):  
Performance Improvement ◽  
Pid Controller ◽  
Robotic Manipulators ◽  
Tracking Performance ◽  
Contour Tracking ◽  
Fitness Functions ◽  
Performance Indexes ◽  
Pid Controller Tuning ◽  
Optimal Gains ◽  
Better Than

Gain tuning is very important in order to obtain good performances for a given controller. Contour tracking performance is mainly determined by the selected control gains of a position domain PID controller. In this paper, three popular evolutionary algorithms are utilized to optimize the gains of a position domain PID controller for performance improvement of contour tracking of robotic manipulators. Differential Evolution (DE), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) are used to determine the optimal gains of the position domain PID controller, and three distinct fitness functions are also used to quantify the contour tracking performance of each solution set. Simulation results show that DE features the highest performance indexes for both linear and nonlinear contour tracking, while PSO is quite efficient for linear contour tracking. Both algorithms performed consistently better than GA that featured premature convergence in all cases.

Design, analysis and modelling of a hybrid controller for serial robotic manipulators

Robotica ◽  
2016 ◽  
Vol 35 (9) ◽  
pp. 1888-1905 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Pid Controller ◽  
Robotic Manipulators ◽  
Convergence Speed ◽  
Model Reference ◽  
Control Approach ◽  
Hybrid Controller ◽  
Comparison Results ◽  
Convergence Performance ◽  
Model Reference Adaptive ◽  
Better Than

SUMMARYWhen the end-effector of a robotic arm grasps different payload masses, the output of joint motion will vary. By using a model reference adaptive control approach, the payload variation effect can be solved. This paper describes the design for a hybrid controller for serial robotic manipulators by combining a PID controller and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. The convergence performance of the PID controller, the MRAC and the PID+MRAC hybrid controller for 1-DOF, 2-DOF and subsequently 3-DOF manipulators is compared. The comparison results show that the convergence speed and its performance for the MRAC and the PID+ MRAC controllers is better than that of the PID controller, and the convergence performance for the hybrid control is better than that of the MRAC control.

scholarly journals PID Controller Tuning using ACO Algorithm for AVR Systems

2020 ◽  
Vol 9 (3) ◽  
pp. 560-563 ◽  
Keyword(s):  
Pid Controller ◽  
Optimization Technique ◽  
Step Response ◽  
Pid Controllers ◽  
Tuning Method ◽  
Avr System ◽  
Disturbance Response ◽  
Pid Controller Tuning ◽  
Control Response ◽  
Optimal Gains

This paper features an effective technique to device the parameters of PID controllers for utilization together with an Automatic Voltage Regulator System (AVR). The quintessential goal is to acquire a good load disturbance response by minimizing the performance index/(Integral time square error). Simultaneously, the transient response is assured by limiting maximum overshoot, settling time and rise time of the step response to minimal values. For achieving these goals, optimum and quick tuning of the parameters (Kp, Ki, and Kd) is essential. In an effort to accomplish the aforementioned, the paper put forth an algorithm developed based on the Ant Colony Optimization technique (ACO) to decide optimal gains of PID controller and for getting optimal performance within an AVR system. Simulation results establish superior control response may be accomplished in comparison with methods like conventional tuning method (trial and error) and built-in genetic algorithm (GA) took-kit.e.

Research of Adaptive PID Controller Based on Genetic Algorithm

2011 ◽  
Vol 48-49 ◽  
pp. 911-915 ◽  
Author(s):  
Huai Zhong Chen
Keyword(s):  
Genetic Algorithm ◽  
Pid Control ◽  
Pid Controller ◽  
Genetic Manipulation ◽  
Adaptive Mutation ◽  
Control Effect ◽  
Fitness Functions ◽  
Performance Indexes ◽  
And Control ◽  
Best Parameters

Aiming at the turning issue of PID control in industrial processes, a strategy of applying variable PID parameters was presented. This paper utilized the characteristic that genetic algorithm can rapidly optimize globally, performance indexes can form corresponding fitness functions through real number encoding of parameters of the controller, and best parameters of the controller can be obtained through adopting self-adaptive mutation rate for repeated genetic manipulation. Simulation results show that the method improves the optimal performance of parameters, and can achieve better dynamics performance and control effect.

PID CONTROLLER TUNING USING ANT COLONY METHOD FOR SERVO HYDRAULIC SYSTEM

2019 ◽  
Vol 42 (4) ◽  
pp. 148-152
Author(s):  
Shaymaa Mahmood Mahdi ◽  
Karam Samir Khalid ◽  
Shakir Mahmood Mahdi
Keyword(s):  
Hydraulic System ◽  
Pid Controller ◽  
Ant Colony ◽  
Controller Tuning ◽  
Pid Controller Tuning

Development of a dual-stage and visual-servo filming robot

2021 ◽  
pp. 095965182199136
Author(s):  
Liang-Chien Liu ◽  
Ping-Han Yang ◽  
Shih-Chi Liao ◽  
Bing-Peng Li ◽  
Fu-Cheng Wang ◽  
...  
Keyword(s):  
Fast Response ◽  
Tracking Performance ◽  
Visual Servo ◽  
Response Characteristics ◽  
Lower Stage ◽  
Upper Stage ◽  
Dual Stage ◽  
Switching Controller ◽  
Similar Evaluation ◽  
Better Than

This article presents the development of a visual-servo filming robot for dolly & truck style camera movement in filming applications. The robot was implemented with a fast-response slider as the upper stage on top of the slow-response tracked robot body as the lower stage, to improve target tracking performance. A new switching controller was developed, which controlled the stages’ motions by balancing and adjusting the weights of vision error and slider’s noncentering error of the upper stage, thus achieving tracking performance better than the traditional master–slave control strategy. The simulations were carried out to evaluate the tracking performance of the model, particularly focusing on evaluating how the dual stage improves the overall response of the model. The similar evaluation was executed experimentally as well. Both results confirm that the fast-response characteristics of the upper stage can compensate the slow dynamics of lower stage, the tracked robot which is inevitably heavy due to its composition.

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