Kang Shijia, Liu Peter Xiaoping, Wang Huanqing
School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China.
School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China; Department of Systems and Computer Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada.
ISA Trans. 2023 Apr;135:476-491. doi: 10.1016/j.isatra.2022.09.028. Epub 2022 Sep 28.
In this article, the problem of decentralized fuzzy adaptive control is addressed for a class of stochastic interconnected nonlinear large-scale systems including saturation and unknown disturbance. Fuzzy logic systems (FLSs) are used to estimate packaged nonlinear uncertainties. The command filter technique is presented to eliminate the "explosion of complexity" obstacle associated with the backstepping procedures and the corresponding error compensation mechanism is constructed to alleviate the effect of the errors generated by command filters. The influence of input saturation is compensated by introducing an auxiliary system. Meanwhile, an improved adaptive fuzzy decentralized controller is developed and it is able to minimize calculation time since there is no need for repeated differentiation for the virtual control laws. The presented control scheme not only assures the semi-global boundedness of all the signals in the closed-loop system, but also makes the output tracking errors reach a small neighborhood around the origin. Finally, both numerical and practical examples are provided to illustrate the efficiency and effectiveness of our theoretic result.
本文针对一类包含饱和特性和未知干扰的随机互联非线性大规模系统，研究了分散模糊自适应控制问题。采用模糊逻辑系统（FLSs）来估计集中式非线性不确定性。提出了指令滤波器技术以消除与反步过程相关的“计算复杂性爆炸”障碍，并构建了相应的误差补偿机制以减轻指令滤波器产生的误差影响。通过引入辅助系统来补偿输入饱和的影响。同时，开发了一种改进的自适应模糊分散控制器，由于无需对虚拟控制律进行重复求导，从而能够减少计算时间。所提出的控制方案不仅确保了闭环系统中所有信号的半全局有界性，还使输出跟踪误差在原点附近达到一个小邻域。最后，通过数值和实际例子说明了理论结果的有效性和实用性。
