Fuzzy and quantitative model-based control systems for robotic manipulators

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Abstract
Generally fuzzy control systems use simple controllers with a few inputs and one output. Here more complex control systems, based explicitly on a model of the controlled process and primarily developed in the frame of quantitative control, are adapted to fuzzy control. Three model-based control schemes are proposed for position control of a robotic manipulator. The feasibility of such control systems and the ability of their quantitative and fuzzy implementations to cope with disturbances, parameter variations and unmodelled dynamics, are evaluated and compared by simulation analysis. The extension of the model-based control paradigm to fuzzy control pinpoints a concept unknown in the usual fuzzy controllers, i.e. intrinsically fuzzy variables that may be a source of problems in fuzzy feedback loops.

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