Title :
Advanced particle swarm optimization-based PID controller parameters tuning
Author :
Jalilvand, Abolfazl ; Kimiyaghalam, Ali ; Ashouri, Ahmad ; Mahdavi, Meisam
Author_Institution :
Dept. of Electr. Eng., Zanjan Univ., Zanjan
Abstract :
PID parameter optimization is an important problem in control field. Particle swarm optimization (PSO) is powerful stochastic evolutionary algorithm that is used to find the global optimum solution in search space. However, it has been observed that the standard PSO algorithm has premature and local convergence phenomenon when solving complex optimization problem. To resolve this problem an advanced particle swarm optimization (APSO) is proposed in this paper. This new algorithm is proposed to augment the original PSO searching speed. This study proposes to use the (APSO) for its fast searching speed. These advanced particle swarm optimization to accelerate the convergence. The algorithms are simulated with MATLAB programming. The simulation result shows that the PID controller with (APSO) has a fast convergence rate and a better dynamic performance.
Keywords :
evolutionary computation; mathematics computing; particle swarm optimisation; stochastic systems; three-term control; MATLAB programming; PID controller; PID parameter optimization; advanced particle swarm optimization; parameters tuning; stochastic evolutionary algorithm; Artificial intelligence; Control systems; Convergence; Evolutionary computation; Genetic algorithms; PD control; Particle swarm optimization; Pi control; Proportional control; Three-term control; Advanced PSO Algorithm; Genetic Algorithm; PID Parameters Tuning; Parameter Optimization;
Conference_Titel :
Multitopic Conference, 2008. INMIC 2008. IEEE International
Conference_Location :
Karachi
Print_ISBN :
978-1-4244-2823-6
Electronic_ISBN :
978-1-4244-2824-3
DOI :
10.1109/INMIC.2008.4777776