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Open AccessArticle

A Control-Performance-Based Partitioning Operating Space Approach in a Heterogeneous Multiple Model

College of Automation and Electronic Engineering, Qingdao University of Science & Technology, Qingdao 266061, China
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Processes 2020, 8(2), 215; https://doi.org/10.3390/pr8020215
Received: 9 December 2019 / Revised: 1 February 2020 / Accepted: 2 February 2020 / Published: 11 February 2020
An operating space partition method with control performance is proposed, where the heterogeneous multiple model is applied to a nonlinear system. Firstly, the heterogeneous multiple model is obtained from a nonlinear system at the given equilibrium points and transformed into a homogeneous multiple model with auxiliary variables. Secondly, an optimal problem where decision variables are composed of control input and boundary conditions of sub-models is formulated with the hybrid model developed from the homogeneous multiple model. The computational implementation of an optimal operating space partition algorithm is presented according to the Hamilton–Jacobi–Bellman equation and numerical method. Finally, a multiple model predictive controller is designed, and the computational implementation of the multiple model predictive controller is addressed with the auxiliary vectors. Furthermore, a continuous stirred tank reactor (CSTR) is used to confirm the effectiveness of the developed method as well as compare with other operating space decomposition methods.
Keywords: heterogeneous multiple model; operating space partition; nonlinear system; model predictive control heterogeneous multiple model; operating space partition; nonlinear system; model predictive control
MDPI and ACS Style

Wu, B.; Liu, X.; Yue, Y. A Control-Performance-Based Partitioning Operating Space Approach in a Heterogeneous Multiple Model. Processes 2020, 8, 215.

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