Self-organizing fuzzy control of multi-variable systems using learning vector quantization network

Using learning vector quantization (LVQ) network to construct a self-organizing fuzzy controller (SOFC) for multivariable nonlinear composite systems is developed in this paper. The LVQ network is used to provide information about the better locations of the IF-part membership functions through un-supervised learning. The generated fuzzy rule base is applied to the SOFC and updated by a self-learning procedure. Using Lyapunov stability methods, the proposed adaptive scheme is proven to provide the SOFC some degree of robust properties and guarantee uniform ultimate boundedness in the presence of disturbances, measurement noise and perturbed initialization error. The effectiveness of the proposed controller has been demonstrated numerically by applying to control a two-link manipulator. (C) 2001 Elsevier Science B.V. All rights reserved.