NDLI: Advanced particle swarm optimization-based PID controller parameters tuning

Content Provider	IEEE Xplore Digital Library
Author	Jalilvand, A. Kimiyaghalam, A. Ashouri, A. Mahdavi, M.
Copyright Year	2008
Description	Author affiliation: Dept. of Electr. Eng., Zanjan Univ., Zanjan (Jalilvand, A.; Kimiyaghalam, A.; Ashouri, A.; Mahdavi, M.)
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.
Starting Page	429
Ending Page	435
File Size	1510956
Page Count	7
File Format	PDF
ISBN	9781424428236
DOI	10.1109/INMIC.2008.4777776
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-23
Publisher Place	Pakistan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Particle swarm optimization Three-term control Genetic algorithms Convergence Control systems Evolutionary computation Pi control Proportional control Artificial intelligence PD control PID Parameters Tuning Advanced PSO Algorithm Genetic Algorithm Parameter Optimization
Content Type	Text
Resource Type	Article

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