Design of optimal disturbance rejection PID controllers using genetic algorithms

This paper presents a method to design an optimal disturbance rejection PID controller. First, a condition for disturbance rejection of a control system-H/sub /spl infin//-norm-is described. Second, the design is formulated as a constrained optimization problem. It consists of minimizing a performan...

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Veröffentlicht in:IEEE transactions on evolutionary computation Jg. 5; H. 1; S. 78 - 82
Hauptverfasser: Krohling, R.A., Rey, J.P.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.02.2001
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Connectionism. Neural networks
Constraint optimization
Control systems
Controllers
Design engineering
Design methodology
Design optimization
Disturbances
Exact sciences and technology
Genetic algorithms
Mathematics
Numerical analysis
Numerical analysis. Scientific computation
Numerical methods in mathematical programming, optimization and calculus of variations
Numerical methods in optimization and calculus of variations
Optimal control
Optimization
Performance analysis
Proportional integral derivative
Rejection
Sciences and techniques of general use
Servomotors
System testing
Three-term control
Performance evaluation
Disturbance rejection
Feedback system
Genetic algorithm
Control system
Constraint satisfaction
Servomechanism
Servomotor
Optimal design
Constrained optimization
Differential integral proportional regulator
ISSN:1089-778X, 1941-0026
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Beschreibung
Zusammenfassung:This paper presents a method to design an optimal disturbance rejection PID controller. First, a condition for disturbance rejection of a control system-H/sub /spl infin//-norm-is described. Second, the design is formulated as a constrained optimization problem. It consists of minimizing a performance index, i.e., the integral of the time weighted squared error subject to the disturbance rejection constraint. A new method employing two genetic algorithms (GA) is developed for solving the constraint optimization problem. The method is tested by a design example of a PID controller for a servomotor system. Simulation results are presented to demonstrate the performance and validity of the method.
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ISSN:1089-778X
1941-0026
DOI:10.1109/4235.910467