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Robust adaptive control of uncertain MIMO non-linear systems — feedforward Takagi-Sugeno fuzzy approximation based approach

机译:不确定MIMO非线性系统的鲁棒自适应控制-基于前馈Takagi-Sugeno模糊逼近的方法

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摘要

This paper proposes a robust adaptive controller using a feedforward Takagi-Sugeno (T-S) fuzzy approximator for a class of multi-input multi-output (MIMO) non-linear plants that is highly unknown. Different to typical fuzzy approximation approaches, the desired commands are taken as input variables of a T-S fuzzy system. Meanwhile, the unknown feedforward terms required during steady state are adaptively approximated and compensated. This allows a simpler architecture during implementation and drops the typical boundedness assumption on fuzzy universal approximation errors. Furthermore, according to H~(∞) control techniques, non-linear damping design, and sliding mode control, the controllers are synthesised to assure either only the disturbance attenuation, the attenuation of both disturbances and estimated fuzzy parameter errors, or globally asymptotic stable tracking. A linear matrix inequality (LMI) technique then provides a straightforward gain design. Finally, numerical simulations are carried out on a two-link robot to illustrate the expected performance.
机译:本文针对未知的一类多输入多输出(MIMO)非线性设备,提出了一种使用前馈Takagi-Sugeno(T-S)模糊逼近器的鲁棒自适应控制器。与典型的模糊逼近方法不同,所需命令用作T-S模糊系统的输入变量。同时,自适应估计和补偿稳态期间所需的未知前馈项。这允许在实现过程中使用更简单的体系结构,并消除了对模糊通用逼近误差的典型有界假设。此外,根据H〜(∞)控制技术,非线性阻尼设计和滑模控制,可以对控制器进行综合以确保仅减小干扰衰减,减小干扰和估计的模糊参数误差,或者确保全局渐近稳定跟踪。然后,线性矩阵不等式(LMI)技术提供了一种简单的增益设计。最后,在两连杆机器人上进行了数值模拟,以说明预期的性能。

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