Cooperative Fuzzy Model-Predictive Control

被引:23
作者
Killian, Michaela [1 ]
Mayer, Barbara [1 ,2 ]
Schirrer, Alexander [1 ]
Kozek, Martin [1 ]
机构
[1] Vienna Univ Technol, Inst Mech & Mechatron, A-1060 Vienna, Austria
[2] FH Joanneum, Inst Ind Management, A-8605 Kapfenberg, Austria
关键词
Cooperative model-predictive control (MPC); fuzzy control; fuzzy MPC; stability; Takagi-Sugeno (T-S) model; STABILITY; SYSTEMS;
D O I
10.1109/TFUZZ.2015.2463674
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a cooperative fuzzy model-predictive control (CFMPC) is presented. The overall nonlinear plant is assumed to consist of several parallel input-coupled Takagi-Sugeno (T-S) fuzzy models. Each such T-S fuzzy subsystem is represented in the form of a local linear model network (LLMN). The control of each local linear model in each LLMN is realized by model-predictive control (MPC). For each LLMN, the outputs of the associated MPCs are blended by the fuzzy membership functions, which leads to a fuzzy model-predictive controller (FMPC). The resulting structure is one FMPC for each LLMN subsystem. Overall, a parallel combination of FMPCs results, which mutually affects all LLMN subsystems by their respective manipulated variables. To compensate detrimental cross-couplings in this setup, a cooperation between the FMPCs is introduced. For this cooperation, convergence is proven, and for the closed-loop system, a stability proof is given. It is demonstrated in a simulation example that the proposed input-constraint CFMPC algorithm achieves convergence of the fuzzy LLMNs within few cooperative iteration steps. Simulations are given to demonstrate the effectiveness of the theoretical results.
引用
收藏
页码:471 / 482
页数:12
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