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A closed-loop particle swarm optimizer for multivariable process controller design. (English) Zbl 1144.93331

Summary: Design of general multivariable process controllers is an attractive and practical alternative to optimizing design by evolutionary algorithms since it can be formulated as an optimization problem. A Closed-Loop Particle Swarm Optimization (CLPSO) algorithm is proposed by mapping PSO elements into the closed-loop system based on control theories. At each time step, a proportional integral controller is used to calculate an updated inertia weight for each particle in swarms from its last fitness. With this modification, limitations caused by a uniform inertia weight for the whole population are avoided, and the particles have enough diversity. After the effectiveness, efficiency and robustness are tested by benchmark functions, CLPSO is applied to design a multivariable proportional-integral-derivative controller for a solvent dehydration tower in a chemical plant and has improved its performances.

MSC:

93C35 Multivariable systems, multidimensional control systems
93B51 Design techniques (robust design, computer-aided design, etc.)

Software:

MCPSO
PDFBibTeX XMLCite
Full Text: DOI

References:

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