Optimization for Design of PID Controller Based on Improved PSO

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.181-182.571 ◽

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.

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

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.401-403.1805 ◽

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.

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Robust Performance of PID Controller by using Artificial Intelligence

International Journal of Current Engineering and Technology ◽

10.14741/ijcet/v.8.3.10 ◽

2018 ◽

Author(s):

Shachi Tiwary ◽

Ashraf Jafri ◽

Kushal Tiwari ◽

Richa Tiwari ◽

Chaman Yadav

Keyword(s):

Pid Controller ◽

Dynamic Behaviour ◽

Design Method ◽

Pso Algorithm ◽

Proportional Integral Derivative ◽

Robust Performance ◽

Bacterial Foraging Optimization ◽

Swarm Optimization ◽

Modern Methods ◽

Selection Of

This paper is meant to design method for determining the optimal proportional-integral-derivative (PID) controller parameters of plant system using the particle swarm optimization (PSO) algorithm and bacterial Foraging Optimization (BFO). There are several methods which are used to tune the controller parameters. They are categorized into two types known as classical methods and modern methods. In this paper the use of PSO method tuned the PID parameter to make them more general and to achieve the steady state error limit, also to improve the dynamic behaviour of the system. The performance and design criteria of automatic selection of controller constants are discussed below.

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

2019 Chinese Control Conference (CCC) ◽

10.23919/chicc.2019.8865547 ◽

2019 ◽

Author(s):

Yuanhai Xie ◽

Wei Zhang

Keyword(s):

Time Delay ◽

Pid Controller ◽

Pso Algorithm ◽

Tuning Method ◽

Improved Pso

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

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.846-847.317 ◽

2013 ◽

Vol 846-847 ◽

pp. 317-320 ◽

Cited By ~ 1

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.

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