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Observer based adaptive fuzzy sliding mode controller for MIMO nonlinear systems with general input matrix

机译:一种基于Observer基于MIMO非线性系统的自适应模糊滑模控制器

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In this paper a new observer-based adaptive fuzzy sliding mode (AFSM) controller is proposed for tracking control of a class of unknown multi-input multi-output (MIMO) nonlinear systems with general input matrix. The fuzzy system is used to approximate the ideal sliding mode controller. Also, a robust controller is designed to compensate the fuzzy estimation error. The bound of errors are adjusted adaptively. Unlike the previous works, in this paper the more general class of nonlinear MIMO systems are considered in which the subsystems of the plant are coupled through both states and inputs. The normalization factors are used for linear combination of fuzzy system outputs which are tuned adaptively. Adaptive laws are derived based on Lyapunov stability analysis, therefore asymptotic tracking and the stability are guaranteed. Numerical results show the efficiency of the proposed algorithm.
机译:在本文中,提出了一种新的观察者的自适应模糊滑模(AFSM)控制器,用于跟踪具有一般输入矩阵的一类未知多输入多输出(MIMO)非线性系统的控制。 模糊系统用于近似理想的滑模控制器。 此外,鲁棒控制器旨在补偿模糊估计误差。 误差的界限适自适应。 与以前的作品不同,在本文中,考虑了更多一般的非线性MIMO系统类别,其中工厂的子系统通过各种状态和输入耦合。 归一化因子用于自适应地调谐的模糊系统输出的线性组合。 基于Lyapunov稳定性分析来推导自适应法律,因此渐近跟踪和稳定性得到保证。 数值结果显示了所提出的算法的效率。

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