A stable one-step-ahead predictive control of non-linear systems

Authors:
C. Kambhampati;J. D. Mason;K. Warwick
Affiliations:
Department of Cybernetics, The University of Reading, Whiteknights, Reading RG6 2AY, UK;Department of Cybernetics, The University of Reading, Whiteknights, Reading RG6 2AY, UK;Department of Cybernetics, The University of Reading, Whiteknights, Reading RG6 2AY, UK
Venue:
Automatica (Journal of IFAC)
Year:
2000

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Abstract

In this paper stability of one-step ahead predictive controllers based on non-linear models is established. It is shown that, under conditions which can be fulfilled by most industrial plants, the closed-loop system is robustly stable in the presence of plant uncertainties and input-output constraints. There is no requirement that the plant should be open-loop stable and the analysis is valid for general forms of non-linear system representation including the case out when the problem is constraint-free. The effectiveness of controllers designed according to the algorithm analyzed in this paper is demonstrated on a recognized benchmark problem and on a simulation of a continuous-stirred tank reactor (CSTR). In both examples a radial basis function neural network is employed as the non-linear system model.