Accessibility navigation


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

Kambhampati, C., Mason, J.D. and Warwick, K. (2000) A stable one-step-ahead predictive control of non-linear systems. Automatica, 36 (4). pp. 485-495. ISSN 0005-1098

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1016/S0005-1098(99)00173-9

Abstract/Summary

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.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science
ID Code:17796
Uncontrolled Keywords:Nonlinear systems; Neural networks; RBFN's; Predictive control; Stability; Robust; Input–output constraints
Publisher:Elsevier

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation