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Adaptive sliding mode fault tolerant control design for uncertain nonlinear systems with multiplicative faults: Takagi-Sugeno fuzzy approach

机译:不确定的具有多重故障的非线性系统的自适应滑模容错控制设计:Takagi-Sugeno模糊方法

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摘要

The present article deals with adaptive sliding mode fault tolerant control design for uncertain nonlinear systems, affected by multiplicative faults, that is described under Takagi-Sugeno fuzzy representation. First, we propose to conceive robust adaptive observer in order to achieve states and multiplicative faults estimation in the presence of nonlinear system uncertainties. Under the nonlinear Lipschitz condition, the observer gains are attained by solving the multi-objective optimization problem. Second, sliding mode controller is suggested to offer a solution of the closed-loop system stability even the occurrence of real fault effects. The main objective is to compensate multiplicative fault effects based on output feedback information. Sufficient conditions are developed with H infinity performances and expressed as a set of linear matrix inequalities subject to compute controller gains. Finally, simulation results, using the nonlinear model of a single-link flexible joint robot system, are given to illustrate the capability of the suggested fault tolerant control strategy to treat multiplicative faults.
机译:本文讨论了受高阶故障影响的不确定非线性系统的自适应滑模容错控制设计,在Takagi-Sugeno模糊表示下进行了描述。首先,我们提出构想鲁棒的自适应观测器,以便在存在非线性系统不确定性的情况下实现状态和乘法故障估计。在非线性Lipschitz条件下,通过解决多目标优化问题可以获得观测器增益。其次,建议使用滑模控制器来提供闭环系统稳定性的解决方案,即使出现实际故障影响也是如此。主要目的是基于输出反馈信息来补偿乘法故障影响。具有H无限性能的充分条件被开发出来,并表示为一组线性矩阵不等式,服从于计算控制器增益。最后,使用单链接柔性关节机器人系统的非线性模型给出了仿真结果,以说明所建议的容错控制策略处理乘法故障的能力。

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