neural control of nonlinear systems with composite adaptation for ...
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neural control of nonlinear systems with composite adaptation for ...
radial basis function neural networks whose parameters are updated by a composite ... shall thus extend composite adaptation to a more gen- eral class of a ne ...
NEURAL CONTROL OF NONLINEAR SYSTEMS WITH COMPOSITE ADAPTATION FOR IMPROVED CONVERGENCE OF GAUSSIAN NETWORKS S. Fabri, V. Kadirkamanathan Department of Automatic Control & Systems Engineering The University of Sheeld, Mappin Street, Sheeld S1 3JD, U.K. Fax : +44 114 273 1729 and e-mail : COP95SF/visakan@sheeld.ac.uk Keywords : adaptive, neural nets, nonlinear control.
Abstract
proximation and their parameters are adjusted via on-line adaptive laws. In this respect, for an ane class of nonlinear systems, methods using direct adaptive laws and Gaussian radial basis function neural networks are well documented [3, 10, 14]. In this paper we shall implement a composite adaptive law for neural control of the same class of nonlinear systems, so as to improve parameter convergence and hence overall system performance. The approach is based on the composite adaptive schemes described in [13] for robot manipulators where the unknowns consisted of system parameters, such as mass. This work shall thus extend composite adaptation to a more general class of ane nonlinear plants whose unknowns are nonlinear functionals.
The use of composite adaptive laws for control of the ane class of nonlinear systems having unknown dynamics is proposed. These dynamics are approximated by Gaussian radial basis function neural networks whose parameters are updated by a composite law that is driven by both tracking and estimation errors. This is motivated by the need to improve the speed of convergence of the unknown parameters, hence resulting in better system performance. To ensure global stability despite the inevitable network approximation errors, the control law is augmented with a low gain sliding mode component and deadzone adaptation is used for the indirect part of the composite law. The stability of the system is analyzed and the e ectiveness of The objective is to design a controller that results in good the method is demonstrated by simulation. tracking performance for the class of nonlinear, singleinput single-output plants that could be expressed in the ane form: y(r) (t) = f (x) + g(x)u(t) (1) The use of control schemes based on composite adaptive where x 2
