stability.pdf (220.6 kB)
Model predictive control of nonlinear systems: computational burden and stability
journal contribution
posted on 2008-11-03, 16:22 authored by Wen-Hua ChenWen-Hua Chen, Donald J. Ballance, John O'ReillyImplementation of Model Predictive Control (MPC) for nonlinear systems requires
on-line solution of a non-convex, constrained nonlinear optimisation problem.
Computational delay and loss of optimality arise in the optimisation procedures.
This paper presents a practical MPC scheme for nonlinear systems with
guaranteed asymptotic stability. It is shown that when an initial control profile is
chosen to satisfy an inequality condition in each on-line optimisation procedure,
the nonlinear system under the proposed nonlinear MPC is asymptotically stable.
The stability condition presented in this paper enables the “fictitious” terminal
control to be nonlinear, rather than only linear, and thus the stability region is
greatly enlarged. Furthermore it is pointed out that nominal stability is still guaranteed
even though the global, or even the local, minimisation of the objective
cost is not achieved within the prescribed computational time
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Citation
CHEN, W-H., BALLANCE, D. J. and O'REILLY, J., 2000. Model predictive control of nonlinear systems: computational burden and stability. IEE proceedings: control theory and applications, 147 (4), pp. 387-394Publisher
© Institution of Electrical EngineersPublication date
2000Notes
This is a journal article. It was published in the journal, IEE proceedings: control theory and applications and is subject to Institution of Engineering and Technology copyright: http://www.ietdl.org/journals/doc/IEEDRL-home/info/support/copyinf.jsp. The definitive version of the paper is available at IET Digital Library.ISSN
1350-2379Language
- en