Application of improved PSO for parameter tuning of PID controller

2010 ◽  
Vol 24 (2) ◽  
pp. 141-146 ◽  
Author(s):  
Cuiyun Jin ◽  
Jianlin Wang ◽  
Jiangning Ma ◽  
Ying Wang
Keyword(s):  
Pid Controller ◽  
Parameter Tuning ◽  
Improved Pso

scholarly journals An MEA-Tuning Method for Design of the PID Controller

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Yongli Zhang ◽  
Lijun Zhang ◽  
Zhiliang Dong
Keyword(s):  
Pid Controller ◽  
Industrial Process ◽  
Optimal Solution ◽  
Design Feature ◽  
Parameter Tuning ◽  
Parallel Structure ◽  
Evolutionary Information ◽  
Tuning Method ◽  
Efficiency And Effectiveness ◽  
Global Optimal

The optimization and tuning of parameters is very important for the performance of the PID controller. In this paper, a novel parameter tuning method based on the mind evolutionary algorithm (MEA) was presented. The MEA firstly transformed the problem solutions into the population individuals embodied by code and then divided the population into superior subpopulations and temporary subpopulations and used the similar taxis and dissimilation operations for searching the global optimal solution. In order to verify the control performance of the MEA, three classical functions and five typical industrial process control models were adopted for testing experiments. Experimental results indicated that the proposed approach was feasible and valid: the MEA with the superior design feature and parallel structure could memorize more evolutionary information, generate superior genes, and enhance the efficiency and effectiveness for searching global optimal parameters. In addition, the MEA-tuning method can be easily applied to real industrial practices and provides a novel and convenient solution for the optimization and tuning of the PID controller.

PSO and GA tuned conventional and fractional order PID controllers for quadrotor control

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hasan Saribas ◽  
Sinem Kahvecioglu
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Controller Design ◽  
Optimization Problems ◽  
Parameter Tuning ◽  
Absolute Error ◽  
Cost Functions ◽  
Pid Controllers ◽  
Content Type ◽  
Quadrotor Control

Purpose This study aims to compare the performance of the conventional and fractional order proportional-integral-derivative (PID and FOPID) controllers tuned with a particle swarm optimization (PSO) and genetic algorithm (GA) for quadrotor control. Design/methodology/approach In this study, the gains of the controllers were tuned using PSO and GA, which are included in the heuristic optimization methods. The tuning processes of the controller’s gains were formulated as optimization problems. While generating the objective functions (cost functions), four different decision criteria were considered separately: integrated summation error (ISE), integrated absolute error, integrated time absolute error and integrated time summation error (ITSE). Findings According to the simulation results and comparison tables that were created, FOPID controllers tuned with PSO performed better performances than PID controllers. In addition, the ITSE criterion returned better results in control of all axes except for altitude control when compared to the other cost functions. In the control of altitude with the PID controller, the ISE criterion showed better performance. Originality/value While a conventional PID controller has three parameters (Kp, Ki, Kd) that need to be tuned, FOPID controllers have two additional parameters (µ). The inclusion of these two extra parameters means more flexibility in the controller design but much more complexity for parameter tuning. This study reveals the potential and effectiveness of PSO and GA in tuning the controller despite the increased number of parameters and complexity.

scholarly journals Optimized PID Controller Based on Beetle Antennae Search Algorithm for Electro-Hydraulic Position Servo Control System

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2727 ◽  
Author(s):  
Yuqi Fan ◽  
Junpeng Shao ◽  
Guitao Sun
Keyword(s):  
Control System ◽  
Pid Controller ◽  
Search Algorithm ◽  
Three Dimensional ◽  
Parameter Tuning ◽  
Servo Control ◽  
Dimensional Parameter ◽  
Servo Control System ◽  
Position Servo Control ◽  
Position Servo

To improve the controllability of an electro-hydraulic position servo control system while simultaneously enhancing the anti-jamming ability of a PID controller, a compound PID controller that combines the beetle antennae search algorithm with PID strategy was proposed, and used to drive the position servo control system of the electro-hydraulic servo system. A BAS-PID controller was designed, and the beetle antennae search algorithm was used to tune PID parameters so that the disturbance signal of the system was effectively restrained. Initially, the basic mathematical model of the electro-hydraulic position servo control system was established through theoretical analysis. The transfer function model was obtained by identifying system parameters. Then, the PID parameter-tuning problem was converted into a class of three-dimensional parameter optimization problem, and gains of PID controllers were adjusted using the beetle antennae search algorithm. Finally, by comparing the effectiveness of different algorithms, simulation and experimental results revealed that the BAS-PID controller can greatly enhance the performance of the electro-hydraulic position servo control system and inhibit external disturbances when different interference signals are used to test the system’s robustness.

Double-Loop PID Parameter Tuning for DC Motor Based on Modified Particle Swarm Optimization

2011 ◽  
Vol 130-134 ◽  
pp. 3139-3142
Author(s):  
Tao Cheng ◽  
Wei Xing Lin
Keyword(s):  
Particle Swarm Optimization ◽  
Pid Controller ◽  
High Performance ◽  
Dynamic Performance ◽  
Particle Swarm ◽  
Parameter Tuning ◽  
Parameters Optimization ◽  
Double Loop ◽  
Swarm Optimization ◽  
Modified Particle Swarm Optimization

This paper proposes a modified particle swarm optimization to solve identification of tuning PID controller parameters. This paper elaborates the process that MPSO algorithm optimizes PID parameters in double-loop speed control system modeled by simulink. Through analyzing the results of the MPSO optimization, and comparing with standard PSO(SPSO) and traditional method, MPSO algorithm has better dynamic performance, provides a high performance methods for PID parameters optimization.

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.

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