In this paper, the problem of adaptive fuzzy decentralized optimal control is investigated for a class of nonlinear large-scale systems in strict-feedback form. The considered nonlinear large-scale systems contain the unknown nonlinear functions and unmeasured states. By utilizing the fuzzy logic systems to approximate the unknown nonlinear functions and cost functions, a fuzzy state observer is established to estimate the unmeasured states. The control design is divided into two phases. First, by using the state observer and the backstepping design technique, a feedforward decentralized controller with parameters adaptive laws is designed, by which the original controlled strict-feedback nonlinear large-scale system is transformed into an equivalent affine nonlinear large-scale system. Second, by using adaptive dynamic programming theory, a feedback decentralized optimal controller is developed for the equivalent affine nonlinear system. The whole adaptive fuzzy decentralized optimal control scheme consists of a feedforward decentralized controller and a feedback decentralized optimal controller. It is shown that the proposed adaptive fuzzy decentralized optimal control approach can guarantee that all the signals in the closed-loop system are bounded, and the tracking errors converge to a small neighborhood of zero. In addition, the proposed control approach can guarantee that the cost functions are minimized. Simulation results are given to demonstrate the effectiveness of the proposed control approach.

中文翻译：

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严格反馈非线性大型系统的基于观测器的自适应模糊分散最优控制设计


本文研究一类严格反馈形式的非线性大系统的自适应模糊分散最优控制问题。所考虑的非线性大系统包含未知的非线性函数和不可测量的状态。利用模糊逻辑系统逼近未知的非线性函数和代价函数，建立模糊状态观测器来估计未测量的状态。控制设计分为两个阶段。首先，利用状态观测器和反步设计技术，设计了具有参数自适应律的前馈分散控制器，将原来的受控严格反馈非线性大系统转化为等效仿射非线性大系统。其次，利用自适应动态规划理论，针对等效仿射非线性系统建立了反馈分散最优控制器。整个自适应模糊分散最优控制方案由前馈分散控制器和反馈分散最优控制器组成。结果表明，所提出的自适应模糊分散最优控制方法能够保证闭环系统中的所有信号都是有界的，并且跟踪误差收敛到零的小邻域内。此外，所提出的控制方法可以保证成本函数最小化。仿真结果证明了所提出的控制方法的有效性。