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Adaptive fuzzy control for a class of unknown nonlinear dynamical systems

机译:一类未知非线性动力学系统的自适应模糊控制

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In this study, we investigate an adaptive fuzzy controller design for a class of nonlinear multi-input multi-output (MIMO) systems in interconnected form. The systems considered comprise n subsystems and an unknown interconnection term is included in every equation for each subsystem. The interconnection term is a function of all the states from the first to the (n - 1)th subsystems. Moreover, the effects of dead-zone models are considered in each subsystem of the systems. These properties of the systems cause the difficulties and add further complexity to the design. In order to overcome these difficulties, we use the following methods: (1) the fuzzy logic systems are employed to approximate the appropriate unknown functions of the systems, (2) a novel backstepping design procedure is constructively designed, and (3) compensative adaptation laws are provided to compensate for the effects of the dead-zone inputs. We show that all the signals in the closed-loop system are bounded and that the outputs converge to a compact set by using the Lyapunov analysis theorem. Simulated examples are presented that validate the effectiveness of the approach.
机译:在这项研究中,我们研究了一类互连形式的非线性多输入多输出(MIMO)系统的自适应模糊控制器设计。所考虑的系统包括n个子系统,每个子系统的每个方程式中都包含一个未知的互连项。互连项是从第一个子系统到第(n-1)个子系统的所有状态的函数。此外,在系统的每个子系统中都考虑了死区模型的影响。系统的这些特性造成了困难,并增加了设计的复杂性。为了克服这些困难,我们使用以下方法:(1)使用模糊逻辑系统来近似系统的适当未知函数,(2)构造性地设计了新颖的反推设计程序,以及(3)补偿适应提供了一些法律来补偿死区输入的影响。我们表明,使用Lyapunov分析定理,闭环系统中的所有信号都是有界的,并且输出收敛到一个紧凑集合。给出了仿真示例,验证了该方法的有效性。

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