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.

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.

scholarly journals Motion planning optimization of trajectory path of space manipulators

2019 ◽  
Vol 10 ◽  
pp. 11
Author(s):  
Dong Qiao
Keyword(s):  
Genetic Algorithm ◽  
Space Station ◽  
Pso Algorithm ◽  
Motion Trajectory ◽  
Motion Model ◽  
Planning Optimization ◽  
Space Manipulators ◽  
The Matrix ◽  
Global Optimal ◽  
Improved Pso

With the development of the aerospace industry, the work carried out inside and outside the weightless space station is becoming more and more complicated. In order to ensure the safety of astronauts, space manipulators are used for operation, but it will disturb the space station that is a base during work. In order to solve the above problems, in this paper, the planning method of the motion trajectory of manipulators, the motion model of manipulators and the particle swarm optimization (PSO) algorithm used for optimizing the trajectory are briefly introduced, the multi-population co-evolution method is used to improve the PSO algorithm, and the above two algorithms are used to optimize the motion trajectory of the floating pedestal space manipulator with three free degrees of rotation in the same plane by the matrix laboratory (MATLAB) software. It is compared with genetic algorithm. The results show that the improved PSO algorithm can converge to a better global optimal fitness with fewer iterations compared with the traditional PSO algorithm and genetic algorithm. The obtained motion trajectory optimized by the improved PSO algorithm has less disturbances to the pedestal posture, and less time is required to achieve the target motion; moreover the changes of mechanical arm joint are more stable during the motion.

Intelligence Fusion Strategy of Forming Process Control for Sport Equipment in Rubber Products

2013 ◽  
Vol 440 ◽  
pp. 210-215
Author(s):  
Bo Bi ◽  
Lei Li
Keyword(s):  
Control Strategy ◽  
Pid Controller ◽  
Research Result ◽  
Chemical Properties ◽  
Control Effect ◽  
Forming Process ◽  
Sport Equipment ◽  
Control Precision ◽  
Physical Chemical ◽  
Complex Process

The physical-chemical properties of rubber products in sport equipment such as elasticity,tolerance,endurance,hardness etc not only are related to the factors of formulation in material and structure size etc, but also mainly depend on the control effect of forming process in vulcanizing phase. Aimed at the puzzle of being difficult to control resulted from uncertainty in vulcanizing phase, the paper proposed a sort of intelligence fusion control strategy. In this paper, it summed the control puzzle in complex vulcanizing phase, researched on the cybernetics characteristic, explored the control strategy of complex process with uncertainty, proposed a sort of intelligence fusion control strategy, and constructed the control model and algorithm. The simulation and engineering verification demonstrated that it could be stronger in robustness, and higher in control precision compared with PID controller. The research result shows that the proposed control strategy is feasible and effective.

scholarly journals Robust Performance of PID Controller by using Artificial Intelligence

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.

The Application of PID Based on Optimized RBF in Thickness Control of Strip Steel

2012 ◽  
Vol 466-467 ◽  
pp. 52-56
Author(s):  
Yu Zhen Yu ◽  
Xin Yi Ren ◽  
Chun Yan Deng ◽  
Xiao Hui Wang
Keyword(s):  
Neural Network ◽  
Control System ◽  
Control Strategy ◽  
Pid Controller ◽  
Control Method ◽  
Rbf Neural Network ◽  
Pso Algorithm ◽  
Strip Thickness ◽  
Control Effect ◽  
Thickness Control

The strip thickness control system is difficult to establish an accurate mathematical model, and traditional PID control strategy has a poor adaptive ability, so the effect of control is always not satisfying. According to the problems above, a new control strategy of self-tuning PID controller based on RBF neural network whose parameters are optimized by PSO algorithm is proposed in the paper. The control method integrates advantages of RBF neural network as well as PID controller and good global search capability of PSO algorithm. The simulation results indicate that the method not only improves control performance and dynamic quality, but also has strong self-adapting ability and robustness. It achieved a very good control effect when used in strip thickness control system that proved the correctness and effectiveness of the control method.

Intelligence Based Control Strategy of Forming Process for Plastic & Rubber Products

2013 ◽  
Vol 345 ◽  
pp. 396-399
Author(s):  
Ping Tao ◽  
Qian Wu ◽  
Chao Xiao
Keyword(s):  
Control Strategy ◽  
Pid Controller ◽  
Control Algorithm ◽  
Simulation Experiment ◽  
Research Result ◽  
Chemical Properties ◽  
Control Effect ◽  
Forming Process ◽  
Control Precision ◽  
Complex Process

The physical-chemical properties of plastic & rubber products such as rigidity and endurance etc not only are related to the factors of formulations of materials & supplies and structure size etc, but also mainly depend on the control effect of forming process in the vulcanizing phase. Aimed at the puzzle of being difficult to control resulted from uncertainty in vulcanizing phase, the paper proposed a sort of intelligence based control strategy. In the paper, it summed the control puzzle in complex vulcanizing phase, explored the cybernetics characteristic, researched on control strategy of complex process with uncertainty, proposed a sort of intelligence based control strategy, and constructed the control algorithm. The simulation experiment and engineering verification demonstrated that it could be stronger in robustness, and higher in control precision compared with PID controller. The research result shows that it is feasible and effective to the proposed intelligence based control strategy.

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.

Sign in / Sign up

Export Citation Format

Share Document