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Decentralized Networked Control System Design Using T–S Fuzzy Approach

机译:基于TS模糊方法的分散网络控制系统设计

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摘要

The robust control problem is studied for a class of large-scale networked control systems. The subsystems are in the nonlinear form, and they exchange information through the communication networks. The interconnections considered are nonlinear, and not the traditional linear form, which brings a challenging issue for the decentralized control design. We develop a new memoryless control scheme with the use of the decomposition for each subsystem that is based on the input matrix. By Takagi–Sugeno (T–S) fuzzyfication for each subsystem, the interconnected T–S fuzzy subsystems are obtained. When the upper bound functions of uncertain interconnections are known, we design a decentralized memoryless state feedback controller. When the parameters of bound functions are not available, the adaptive method is used, and the decentralized memoryless adaptive controller is developed. By the construction of a new Lyapunov–Krasovskii functional, we prove the stability of the resultant closed-loop system for the both cases. Finally, we apply the theoretic results to the decentralized controller design of networked interconnected chemical reactor systems. The simulations are performed, and the effectiveness of the proposed method is demonstrated.
机译:针对一类大型网络控制系统,研究了鲁棒控制问题。子系统为非线性形式,它们通过通信网络交换信息。考虑的互连是非线性的,而不是传统的线性形式,这给分散控制设计带来了挑战。我们使用基于输入矩阵的每个子系统的分解来开发新的无记忆控制方案。通过对每个子系统进行Takagi–Sugeno(TS)模糊化,可以获得相互联系的TS–S模糊子系统。当不确定互连的上限函数已知时,我们设计了一种分散的无记忆状态反馈控制器。当约束函数的参数不可用时,采用自适应方法,并开发了分散式无记忆自适应控制器。通过构造新的Lyapunov–Krasovskii函数,我们证明了这两种情况下所得闭环系统的稳定性。最后,我们将理论结果应用于网络互连化学反应器系统的分散控制器设计。仿真结果表明了该方法的有效性。

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