IEEE Trans Cybern. 2018 Apr;48(4):1326-1339. doi: 10.1109/TCYB.2017.2692384. Epub 2017 May 16.
This paper considers the optimal decentralized fuzzy adaptive control design problem for a class of interconnected large-scale nonlinear systems in strict feedback form and with unknown nonlinear functions. The fuzzy logic systems are introduced to learn the unknown dynamics and cost functions, respectively, and a state estimator is developed. By applying the state estimator and the backstepping recursive design algorithm, a decentralized feedforward controller is established. By using the backstepping decentralized feedforward control scheme, the considered interconnected large-scale nonlinear system in strict feedback form is changed into an equivalent affine large-scale nonlinear system. Subsequently, an optimal decentralized fuzzy adaptive control scheme is constructed. The whole optimal decentralized fuzzy adaptive controller is composed of a decentralized feedforward control and an optimal decentralized control. It is proved that the developed optimal decentralized controller can ensure that all the variables of the control system are uniformly ultimately bounded, and the cost functions are the smallest. Two simulation examples are provided to illustrate the validity of the developed optimal decentralized fuzzy adaptive control scheme.
本文考虑了一类具有未知非线性函数的严格反馈形式的互联大规模非线性系统的最优分散模糊自适应控制设计问题。引入模糊逻辑系统分别对未知动力学和代价函数进行学习，并开发了一个状态估计器。通过应用状态估计器和回溯递推设计算法，建立了一个分散前馈控制器。通过使用回溯分散前馈控制方案，将所考虑的严格反馈形式的互联大规模非线性系统转化为一个等效仿射大规模非线性系统。随后，构建了一个最优分散模糊自适应控制方案。整个最优分散模糊自适应控制器由分散前馈控制和最优分散控制组成。证明了所开发的最优分散控制器可以确保控制系统的所有变量都是一致有界的，并且代价函数是最小的。提供了两个仿真示例来说明所开发的最优分散模糊自适应控制方案的有效性。
