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.

To link to this article 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 > School of Systems Engineering
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