Tairen Sun

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1 This paper presents a practical direct adaptive fuzzy H ∞ tracking control (AFHC) approach for a class of uncertain nonlinear systems with unknown control gain functions and external disturbances. A modified output tracking error is defined to eliminate high gain at the control input and to improve transient performance. An ideal control law is developed(More)
High-gain observers have been extensively applied to construct output-feedback adaptive neural control (ANC) for a class of feedback linearizable uncertain nonlinear systems under a nonlinear separation principle. Yet due to static-gain and linear properties, high-gain observers are usually subject to peaking responses and noise sensitivity. Existing(More)
It is well-known that standard adaptive fuzzy control (AFC) can only guarantee uniformly ultimately bounded stability due to inherent fuzzy approximation errors (FAEs). This paper proves that standard AFC with proportional-derivative (PD) control can guarantee global asymptotic stabilization even in the presence of FAEs for a class of uncertain affine(More)
This paper focuses on biomimetic hybrid feedback feedforward (HFF) learning for robot motion control. Existing HFF robot motion control approaches have a major problem that accurate estimation of the robotic dynamics, which is crucial for mimicking biological control, is not taken into account. In this study, a composite learning technique is presented to(More)