IEEE Trans Cybern. 2014 Jul;44(7):1204-13. doi: 10.1109/TCYB.2013.2281458. Epub 2013 Sep 20.
In this paper, a methodology for designing a fuzzy dynamic output feedback controller for discrete-time nonlinear networked control systems is presented where the nonlinear plant is modelled by a Takagi-Sugeno fuzzy model and the network-induced delays by a finite state Markov process. The transition probability matrix for the Markov process is allowed to be partially known, providing a more practical consideration of the real world. Furthermore, the fuzzy controller's membership functions and premise variables are not assumed to be the same as the plant's membership functions and premise variables, that is, the proposed approach can handle the case, when the premise of the plant are not measurable or delayed. The membership functions of the plant and the controller are approximated as polynomial functions, then incorporated into the controller design. Sufficient conditions for the existence of the controller are derived in terms of sum of square inequalities, which are then solved by YALMIP. Finally, a numerical example is used to demonstrate the validity of the proposed methodology.
本文提出了一种设计离散时间非线性网络控制系统模糊动态输出反馈控制器的方法,其中非线性 plant 采用 Takagi-Sugeno 模糊模型建模,网络诱导延迟采用有限状态马尔可夫过程建模。允许 Markov 过程的转移概率矩阵部分已知,为实际情况提供了更实际的考虑。此外,模糊控制器的隶属函数和前提变量不假定与 plant 的隶属函数和前提变量相同,即所提出的方法可以处理 plant 的前提不可测或延迟的情况。plant 和控制器的隶属函数被近似为多项式函数,然后将其纳入控制器设计中。以平方和不等式的形式推导出控制器存在的充分条件,然后通过 YALMIP 求解。最后,通过数值示例验证了所提出方法的有效性。