An integrated state space partition and optimal control method of multi-model for nonlinear systems based on hybrid systems. (January 2015)

• Record Type: Journal Article
• Authors: Song, Chunyue; Wu, Bing; Zhao, Jun; Li, Ping
• Is Part Of: Journal of process control. Volume 25(2015:Jan.)
• Page Start: 59
• Page End: 69
• Publication Date: 2015-01
• Subjects: Nonlinear systems -- State space partition -- Optimal control -- Multilinear model -- Hybrid systems; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2014.10.010
• Languages: English
• ISSNs: 0959-1524

Abstract

Highlights: An integrated decomposition and combination of multi-model approach for nonlinear systems based on optimal control of hybrid systems is initially addressed. The active region of each linear model survival is evaluated from the closed-loop optimal control view of the point, not from the open-loop view. The optimal control is designed according to the obtained optimal state space partition. A systematic procedure of integrated state space partition and optimal control of multi-model for nonlinear systems based on hybrid systems is proposed. Abstract: Multilinear model approach turns out to be an ideal candidate for dealing with nonlinear systems control problem. However, how to identify the optimal active state subspace of each linear subsystem is an open problem due to that the closed-loop performance of nonlinear systems interacts with these subspaces ranges. In this paper, a new systematic method of integrated state space partition and optimal control of multi-model for nonlinear systems based on hybrid systems is initially proposed, which can deal with the state space partition and associated optimal control simultaneously and guarantee an overall performance of nonlinear systems consequently. The proposed method is based on the framework of hybrid systems which synthesizes the multilinear model, produced by nonlinear systems, in a unified criterion and poses a two-level structure. At the upper level, the active state subspace of each linear subsystem is determined under the optimal control index of a hybrid system over infinite horizon, which is executed off-line. At the low level, the optimal control is implemented online via solving the optimal control of hybrid system over finite horizon. The finite horizon optimal control problem is numerically computed by simultaneous method for speeding up computation. Meanwhile, the model mismatch produced by simultaneous method is avoided by using the strategy of receding-horizon. Simulations on CSTR (Continuous Stirred Tank Reactor) confirm that a superior performance can be obtained by using the presented method.