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Dual-mode predictive control algorithm for constrained Hammerstein systems

Zhang H.T. and Li H.X. and Chen G.R.

International Journal of Control, Volume 81, Number 10, Pages 1609-1625, 2008

Abstract

In process industry, there exist many Hammerstein systems subject to input magnitude constraints. However, due to their complex structures, most of the existing control algorithms can not guarantee large enough closed-loop stable regions when being applied to such systems. In this paper, a Multi-Channel Identification Algorithm (MCIA) is proposed, in which the coefficient parameters are identified by LSE (least squares estimation) together with SVD (singular value decomposition) technique. Compared with traditional single-channel identification algorithms, the present method can enhance the approximation accuracy remarkably, and provide consistent estimates even in the presence of colored output noises under relatively weak assumptions on the PE (persistent excitation) of the inputs. Then, to facilitate the following controller design, this MCIA is converted into a Two Stage Single-Channel Identification Algorithm (TS-SCIA), which preserves most of the advantages of MCIA. With this TS-SCIA as the inner model, dual-mode NMPC (Nonlinear Model Predictive Control) algorithm is developed. In detail, over a finite horizon, an optimal input profile found by solving a open-loop optimal control problem drives the nonlinear system state into the terminal invariant set, afterwards a linear output-feedback controller steer the state to the origin asymptotically. In contrast to the traditional algorithms, the present method has a maximal stable region, a better steady-state performance and a lower computational complexity. Finally, simulation results on a heat exchanger are presented to show the efficiency of both the identification and the control algorithms.

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BibTex Entry

@Article{,: author = {Zhang H.T. and Li H.X. and Chen G.R.},; journal = {International Journal of Control},; title = {Dual-mode predictive control algorithm for constrained Hammerstein systems},; year = {2008},; number = {10},; pages = {1609-1625},; volume = {81}
}



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