Using a genetic algorithm to fully optimise a fuzzy logic controller for a two-link-flexible robot arm

Flexible manipulators have received wide attention because they surpass their rigid counterparts in many criteria. Unfortunately, traditional controller design methods for flexible arms implemented by human experts are usually tedious and intractable. In order to improve system behaviour, this paper proposes schemes based on genetic algorithms (GAs) which optimise the parameters of a fuzzy logic controller for a robotic manipulator with two-link flexibility and two-joint elasticity. Two alternative GA-optimised schemes are simulated and their control behaviour is compared with that of human-expert-designed controller.

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