A genetic algorithm based optimisation method for iterative learning control systems

A genetic algorithm based optimisation method for iterative learning control systems

In this paper genetic algorithms are proposed as a method to implement optimality based iterative learning control algorithms. The strength of the proposed method is that it can cope with nonlinearities and hard constraints in the problem definition whereas most of the existing algorithms would fail...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Hatzikos, V., Owens, D.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Control systems
Convergence
Genetic algorithms
Iterative algorithms
Iterative methods
Manipulators
Modems
Motion control
Optimal control
Optimization methods
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Beschreibung
Zusammenfassung:In this paper genetic algorithms are proposed as a method to implement optimality based iterative learning control algorithms. The strength of the proposed method is that it can cope with nonlinearities and hard constraints in the problem definition whereas most of the existing algorithms would fail. Simulation examples show that this approach results in fast convergence for linear plants.
DOI:10.1109/ROMOCO.2002.1177143