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Fuzzy neural network quadratic stabilization output feedback control for biped robots via H∞ approach

机译:基于H∞的双足机器人模糊神经网络二次稳定输出反馈控制。

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摘要

A novel fuzzy neural network (FNN) quadratic stabilization output feedback control scheme is proposed for the trajectory tracking problems of biped robots with an FNN nonlinear observer. First, a robust quadratic stabilization FNN nonlinear observer is presented to estimate the joint velocities of a biped robot, in which an H∞ approach and variable structure control (VSC) are embedded to attenuate the effect of external disturbances and parametric uncertainties. After the construction of the FNN nonlinear observer, a quadratic stabilization FNN controller is developed with a robust hybrid control scheme. As the employment of a quadratic stability approach, not only does it afford the possibility of trading off the design between FNN, H∞ optimal control, and VSC, but conservative estimation of the FNN reconstruction error bound is also avoided by considering the system matrix uncertainty separately. It is shown that all signals in the closed-loop control system are bounded.
机译:针对具有FNN非线性观测器的两足机器人的轨迹跟踪问题,提出了一种新颖的模糊神经网络二次稳定输出反馈控制方案。首先,提出了鲁棒的二次稳定FNN非线性观测器来估计两足机器人的关节速度,其中嵌入了H∞方法和可变结构控制(VSC)以减弱外部干扰和参数不确定性的影响。在构造FNN非线性观测器之后,开发了具有鲁棒混合控制方案的二次稳定FNN控制器。由于采用了二次稳定性方法,因此不仅提供了在FNN,H∞最优控制和VSC之间进行折衷设计的可能性,而且还通过考虑系统矩阵不确定性来避免FNN重构误差范围的保守估计。分别。结果表明,闭环控制系统中的所有信号都是有界的。

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