DocumentCode :
1868565
Title :
Strategic iniitialization of a hybrid particle swarm optimization-simullated annealing algorithm (HPSOSA) for PID controller design for a nonlinear system
Author :
Tharmalingam, Mathiruban ; Raahemifar, Kaamran
Author_Institution :
Dept. of Electr. Eng. & Comput. Eng., Ryerson Univ., Toronto, ON, Canada
fYear :
2012
fDate :
April 29 2012-May 2 2012
Firstpage :
1
Lastpage :
4
Abstract :
There exist some variations of the particle swarm optimization - simulated annealing optimization technique (PSOSA) hybrid algorithm for solving the PID control design problem, however most of these algorithms use the simulated annealing as a tool to escape local minimums that the PSO algorithm may get trapped in and also these algorithms initialize the particles within the solution space randomly. In this paper, the effects of initializing the particles strategically within the solution space along with the application of the SA algorithm to the hybrid algorithm at each iteration are explored. To test the effectiveness of the proposed modifications the algorithms are compared on common benchmark functions before the modified hybrid algorithm (MPSOSA) is used to design a PID controller for the inverted Pendulum problem.
Keywords :
control system synthesis; iterative methods; nonlinear control systems; particle swarm optimisation; pendulums; random processes; simulated annealing; three-term control; HPSOSA; MPSOSA; PID controller design; benchmark functions; hybrid particle swarm optimization-simulated annealing algorithm; inverted Pendulum problem; iterations; local minimums; modified hybrid algorithm; nonlinear system; particle strategic initialization; random process; solution space; Aerospace electronics; Algorithm design and analysis; Benchmark testing; Particle swarm optimization; Simulated annealing; Standards; Hybrid optimization Algorithm; Nonlinear systems; PID Controller; Particle Swarm Optimization (PSO); Simulated Annealing (SA);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical & Computer Engineering (CCECE), 2012 25th IEEE Canadian Conference on
Conference_Location :
Montreal, QC
ISSN :
0840-7789
Print_ISBN :
978-1-4673-1431-2
Electronic_ISBN :
0840-7789
Type :
conf
DOI :
10.1109/CCECE.2012.6334942
Filename :
6334942
Link To Document :
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