scholarly journals Anti-synchronization of discrete-time chaotic systems using optimization algorithms

2011 ◽  
pp. 143-147
Author(s):  
Mahdieh Adeli ◽  
Hassan Zarabadipoor
Keyword(s):  
Particle Swarm Optimization ◽  
Pid Control ◽  
Pid Controller ◽  
Chaotic Systems ◽  
Optimization Algorithms ◽  
Particle Swarm ◽  
Optimization Methods ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Modified Particle Swarm Optimization

In this paper, anti-synchronization of discrete chaotic system based on optimization algorithms are investigated. Different controllers have been used for anti-synchronization of two identical discrete chaotic systems. A proportional-integral-derivative (PID) control is used and its parameters is tuned by the four optimization algorithms, such as genetic algorithm (GA), particle swarm optimization (PSO), modified particle swarm optimization (MPSO) and improved particle swarm optimization (IPSO). Simulation results of these optimization methods to determine the PID controller parameters to anti-synchronization of two chaotic systems are compared. Numerical results show that the improved particle swarm optimization has the best result.

Parameter Optimization of PID Controller Based on an Improved Particle Swarm Optimization for the Induction Motor

2011 ◽  
Vol 130-134 ◽  
pp. 1938-1942
Author(s):  
Xia Bo Shi ◽  
Wei Xing Lin
Keyword(s):  
Particle Swarm Optimization ◽  
Induction Motor ◽  
Parameter Optimization ◽  
Pid Controller ◽  
Dynamic Performance ◽  
Particle Swarm ◽  
Motor Speed ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Ipso Algorithm

This paper presents a new approach of PID parameter optimization for the induction motor speed system by using an improved particle swarm optimization (IPSO). The induction motor speed is changed by the stator voltage controlled with PID controller. The performance of PID controller based on IPSO is compared to Linearly Decreasing Inertia Weight (LIWPSO). Simulation results demonstrate that the IPSO algorithm has better dynamic performance, higher accuracy and faster convergence and good performance for the PID controller.

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.

Application of Fuzzy Immune PID Controller Based on Particle Swarm Optimization in Power Plant Steam Temperature Control System

2014 ◽  
Vol 950 ◽  
pp. 257-262 ◽  
Author(s):  
Fei Hu ◽  
Wu Neng Zhou
Keyword(s):  
Particle Swarm Optimization ◽  
Power Plant ◽  
Temperature Control ◽  
Pid Control ◽  
Pid Controller ◽  
Particle Swarm ◽  
Temperature Control System ◽  
Steam Temperature ◽  
Swarm Optimization ◽  
Adjustment Time

Power plant steam temperature control has characteristics of long delay and great inertia, a new method is proposed by analyzing above-mentioned problems and existing control methods on this paper. The method consists of an improved particle swarm optimization algorithm and a fuzzy immune PID controller. In addition, simulation results of PID, traditional fuzzy immune PID and fuzzy immune PID based on PSO are presented and compared. Fuzzy immune PID Control based on PSO has advantages of short adjustment time, quicker response time, better anti-interference ability and more stability. It can reduce the fluctuation of power plant steam temperature, and has better control performance and practical value.

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