Indirect adaptive fuzzy control
Christopher G. Moore, Chris J. Harris · International Journal of Control · 1992
Fuzzy controllers may be either static systems, which have a fixed rule base, or adaptive systems, which have the ability to alter their rules. A discussion of adaptive fuzzy controllers and a comparison with corresponding algebraic techniques concludes that all previous adaptive fuzzy controllers have been of the direct adaptive type. Such controllers use observations of closed loop performance to manipulate the controller rule base directly without any intermediate process model being produced. In this paper, an indirect adaptive fuzzy controller is proposed where an intermediate process model, identified from observed data, is used to perform on-line controller design. The resulting separation of the adaptation system from controller design enables learning convergence to be investigated. Examples are given of both fuzzy model identification and controller design for linear and nonlinear processes.