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This paper presents hybrid control strategy for robust trajectory tracking control for a class of uncertain nonlinear mechanical systems. The design combines adaptive fuzzy system with robust adaptive control algorithm. Adaptive fuzzy system approximates unknown nonlinear system dynamics while a robustifying adaptive control term is used to cope with uncertainties due to the presence of external disturbance,...
In the face of large scale parametric uncertainties, the single model (SM)-based classical adaptive control approach demands high observer, controller and adaptation gains in order to achieve good tracking performance. The well known problem of having high-gain based design is that it amplifies the input and output disturbance as well as excites hidden unmodeled dynamics causing poor tracking performance...
In this paper, we propose an adaptive fuzzy output feedback control method for trajectory tracking control problem for robotic systems. Using Lyapunov method, we first develop a stable adaptive fuzzy state feedback control algorithm by assuming that the systems output and its derivatives are available for feedback control design. The algorithm combines fuzzy systems with robust adaptive controller...
In the face of large scale parametric uncertainties, the existing single model (SM)-based sliding mode control (SMC) demands high controller gains to achieve good transient tracking performance. The main practical problem of having high-gains based design is that it amplifies the input and output disturbance as well as excites hidden unmodeled dynamics causing high-frequency switching and infinitely...
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