Parameter optimization of 2-DOF-PID controller using genetic algorithm

2006 ◽  
Vol 24 (3-4) ◽  
pp. 131-145 ◽  
Author(s):  
Tae-Seok Oh ◽  
Wang-Heon Lee ◽  
Il-Hwan Kim
Keyword(s):  
Genetic Algorithm ◽  
Parameter Optimization ◽  
Pid Controller

The Design of Expert PID Parameter Optimized by Genetic Algorithm

2011 ◽  
Vol 130-134 ◽  
pp. 3091-3094
Author(s):  
Jia Tang Cheng ◽  
Wei Xiong ◽  
Li Ai
Keyword(s):  
Genetic Algorithm ◽  
Parameter Optimization ◽  
Pid Controller ◽  
Dynamic Performance ◽  
Parameter Tuning ◽  
Expert Pid ◽  
Parameter Values ◽  
Better Than

Aiming at the problems Expert PID parameter tuning for time-consuming, and the results are not necessarily the best. In this paper, genetic algorithm is introduced to the parameter optimization, finally get a set of optimal PID parameter values. In comparison with simulated experiments, the results show that the performance of the Designed to optimize the performance of optimization expert PID controller is better than conventional controller, can achieve good dynamic performance.

Application of PID Controller for Servo Motors

2014 ◽  
Vol 926-930 ◽  
pp. 1218-1221
Author(s):  
Jun Shi ◽  
Hua Jie Wu
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Parameter Optimization ◽  
Pid Controller ◽  
Controller Design ◽  
Optimization Method ◽  
Engineering Practice ◽  
Algorithm Optimization ◽  
Quantum Genetic Algorithm ◽  
Wide Range

Parameter optimization of PID controller design, parameter optimization method is proposed based on quantum genetic algorithm for PID controller tuning problem. Quantum Genetic Algorithm (QGA) DC servo motor control system PID parameter optimization control, quantum genetic algorithm to optimize the results of the genetic algorithm, the simulation results show that the QGA to optimize control get PID controller comprehensive performance is better than general genetic algorithm optimization PID controller, and the realization of the algorithm does not depend on the controlled object, so that the control system has better robustness and stability, with a wide range of practical in engineering practice play a good role in the control.

Longitudinal Nonlinear PID Controller Parameter Optimization of Autopilot Using Genetic Algorithm

2014 ◽  
Vol 709 ◽  
pp. 252-255 ◽  
Author(s):  
Xin Zhao ◽  
Wei Ping Zhao ◽  
Song Xiang
Keyword(s):  
Genetic Algorithm ◽  
Parameter Optimization ◽  
Pid Controller ◽  
Channel Model ◽  
Time Integration ◽  
Nonlinear Function ◽  
Controller Parameter ◽  
Nonlinear Pid Controller ◽  
Rate Optimization ◽  
Longitudinal Channel

This paper performed the longitudinal nonlinear PID Controller parameter optimization of general aircraft autopilot based on the longitudinal channel model and genetic algorithm. Proportion, integration and differential gain of nonlinear PID Controller is nonlinear function of controlling error. The objection function involves time integration of error’s absolute value, output of controller and system overshoot. The longitudinal controlling rate optimization of general aircraft autopilot is realized by minimizing the objection function value. Simulation results show that controller designed by the present method is better than traditional PID controller.

Machining Parameter Optimization of Bidirectional CFRP Composite Pipe by Genetic Algorithm

2014 ◽  
Vol 56 (9) ◽  
pp. 728-736 ◽  
Author(s):  
Krishnasamy Vijaykumar ◽  
Kavan Panneerselvam ◽  
Abdullah Naveen Sait
Keyword(s):  
Genetic Algorithm ◽  
Parameter Optimization ◽  
Composite Pipe ◽  
Cfrp Composite ◽  
Machining Parameter

scholarly journals Data-Driven Tuning of PID Controlled Piezoelectric Ultrasonic Motor

Actuators ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 148
Author(s):  
Sarah Makarem ◽  
Bülent Delibas ◽  
Burhanettin Koc
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Good Alternative ◽  
Data Driven ◽  
Grid Search ◽  
Single Source ◽  
Dual Frequency ◽  
Dual Source ◽  
Stage System ◽  
Piezoelectric Ultrasonic Motor

Ultrasonic motors employ resonance to amplify the vibrations of piezoelectric actuator, offering precise positioning and relatively long travel distances and making them ideal for robotic, optical, metrology and medical applications. As operating in resonance and force transfer through friction lead to nonlinear characteristics like creep and hysteresis, it is difficult to apply model-based control, so data-driven control offers a good alternative. Data-driven techniques are used here for iterative feedback tuning of a proportional integral derivative (PID) controller parameters and comparing between different motor driving techniques, single source and dual source dual frequency (DSDF). The controller and stage system used are both produced by the company Physik Instrumente GmbH, where a PID controller is tuned with the help of four search methods: grid search, Luus–Jaakola method, genetic algorithm, and a new hybrid method developed that combines elements of grid search and Luus–Jaakola method. The latter method was found to be quick to converge and produced consistent result, similar to the Luus–Jaakola method. Genetic Algorithm was much slower and produced sub optimal results. The grid search has also proven the DSDF driving method to be robust, less parameter dependent, and produces far less integral position error than the single source driving method.

scholarly journals Parameter Optimization of Three Phase Boost Inverter Using Genetic Algorithm for Linear Loads

2016 ◽  
Vol 90 ◽  
pp. 559-565 ◽  
Author(s):  
G. Arunkumar ◽  
I. Gnanambal ◽  
S. Naresh ◽  
P.C. Karthik ◽  
Jagadish Kumar Patra
Keyword(s):  
Genetic Algorithm ◽  
Parameter Optimization ◽  
Three Phase
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