A novel tuning method for PID controller based on improved PSO algorithm for unstable plants with time delay

2019 ◽  
Author(s):  
Yuanhai Xie ◽  
Wei Zhang
Keyword(s):  
Time Delay ◽  
Pid Controller ◽  
Pso Algorithm ◽  
Tuning Method ◽  
Improved Pso

Optimization for Design of PID Controller Based on Improved PSO

2011 ◽  
Vol 181-182 ◽  
pp. 571-576
Author(s):  
Jin Zhu ◽  
Wei Kang ◽  
Xiu Mei Zhang
Keyword(s):  
Pid Controller ◽  
Simple Structure ◽  
Pso Algorithm ◽  
The Other ◽  
Robust Performance ◽  
Improved Pso

A new algorithm which is the average local best position is presented to replace the local best of the traditional velocity update rule. One particle can acquire more messages of the other particles to adjust is movement in this method. Integrating PSO algorithm with PID controller, the three parameters of the PID controller can be optimized, which has the features of simple structure, easy implementation and robust performance. The simulation shows the PID controller integrated with the improved PSO algorithm achieved a good performance.

An Improved PSO Algorithm of Optimizing Selection for Multi-Objective Controller Parameter

2013 ◽  
Vol 401-403 ◽  
pp. 1805-1808
Author(s):  
Yan Juan Ren
Keyword(s):  
Performance Index ◽  
Pid Controller ◽  
Research Result ◽  
Pso Algorithm ◽  
Performance Comparison ◽  
Control Effect ◽  
Global Optimal ◽  
Selection For ◽  
Selection Of ◽  
Improved Pso

For the same controlled process, different controller is radically different in control effect. Aimed at the puzzle of being difficult to select the controller for the incompatibility among control performance index, the paper proposed a sort of improved PSO algorithm. Based on the construction of objective function in multi-performance index parameter, the algorithm could quickly search and converge to control parameter in global optimal extremum corresponded to each controller and single out the controller through performance comparison excellently. In the paper, it took the controller selection of wastewater treatment system as an example, designed the algorithm of multi-modal HSIC controller of DO parameter, made the experiment of system simulation, and the simulation demonstrated that the HSIC controller could be stronger in robustness and better in dynamical and steady control quality compared with improved PID controller. The research result shows that it is reasonable and applicable to optimize selection of controller.

scholarly journals Comparison of Particle Swarm Optimization and Ziegler Nichols Techniques

2020 ◽  
pp. 184-188
Keyword(s):  
Particle Swarm Optimization ◽  
Pid Controller ◽  
Optimization Technique ◽  
Heuristic Method ◽  
Particle Swarm ◽  
Absolute Error ◽  
Pso Algorithm ◽  
Computational Method ◽  
Swarm Optimization ◽  
Tuning Method

Two tuning techniques namely: Particle Swarm Optimization (PSO) and Ziegler Nichols (ZN) technique are compared. PSO is an optimization technique based on the movement and intelligence of swarms. PSO applies the concept of social interaction to problem solving. It is a computational method that optimizes a problem by iteratively trying to improve a candidate solution about a given measure of quality. Ziegler Nichols tuning method is a heuristic method of tuning a PID controller. The ZN close loop tuning is performed by setting the I (integral) and D (derivative) gains to zero and increasing proportional gain to obtain sustained oscillations. The DC Motor is represented by second order transfer function is used as a plant, which is controlled using PID controller. The PID controller parameters are chosen by tuning the controller using PSO algorithm and ZN method. The response of the system to unit step input is plotted and performance measures are evaluated for comparing PSO algorithm and ZN technique. Here we have compared the two tuning methods based upon the settling time (Ts), peak overshoot (Mp) and the two performance indices namely Integral square error (ISE) and Integral Absolute error (IAE).

scholarly journals A Tuning Method for PID Controller for an Integrating System with Time Delay

2018 ◽  
Vol 249 ◽  
pp. 03007
Author(s):  
Haitao Sun ◽  
Mohannad Jabbar Mnati ◽  
Mohamed N. Ibrahim ◽  
Alex Van den Bossche
Keyword(s):  
Time Delay ◽  
Pid Controller ◽  
Mathematic Model ◽  
Current Control ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Tuning Method ◽  
Tuning Methods ◽  
Integrating Process ◽  
System With Time Delay

A proportional integral derivative (PID) controller is the most commonly used in integrating process, where the time delay is inevitable. In order to tune a PID controller, several factors should be taken into account such as time delay, mathematic model and the feedback signals. Some existed tuning methods failed to obtain the correct parameters with all the factors. The proposed tuning method presents some formulas, which considers all the factors. The proposed tuning method is also tested by practical circuit, which proved that the method can be applied for several cases, especially for the inductor current control.

Research on Double Closed-Loop DC Speed-Regulation System Based on Improved Particle Swarm Optimization

2013 ◽  
Vol 846-847 ◽  
pp. 317-320 ◽  
Author(s):  
Le Peng Song ◽  
Han Qi
Keyword(s):  
Particle Swarm Optimization ◽  
Pid Controller ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Parameters Optimization ◽  
Step Response ◽  
Regulation System ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Improved Pso

For the defects of the parameter tuning and optimization of the PID controller uses an improved Particle Swarm Optimization (IPSO) algorithm to apply on the dual closedloop DC speed tuning system and adjust PID controller parameters online. The optimization result of adopting step response of the improved PSO algorithm is analyzed. It shows that using the improved PSO algorithm will obtain better dynamic performance, follow faster and more robustness than the traditional engineering design method. It provides a good performance of practical method for PID parameters optimization.

Knowledge acquisition based on improved PSO algorithm and entropy

2009 ◽  
Vol 29 (8) ◽  
pp. 2245-2249 ◽  
Author(s):  
Xiang XU ◽  
Dong-bo ZHANG ◽  
Hui-xian HUANG ◽  
Zi-wen LIU
Keyword(s):  
Knowledge Acquisition ◽  
Pso Algorithm ◽  
Improved Pso

Improved PSO algorithm based on cosine functions and its simulation

2013 ◽  
Vol 33 (2) ◽  
pp. 319-322
Author(s):  
Min ZHANG ◽  
Qiang HUANG ◽  
Zhouzhao XU ◽  
Baizhuang JIANG
Keyword(s):  
Pso Algorithm ◽  
Cosine Functions ◽  
Improved Pso
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