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In this paper, a decentralized adaptive neural network sliding mode control scheme is proposed for trajectory tracking control problem of reconfigurable manipulators based on data-based modeling. This method can be implemented to reconfigurable manipulators with different configurations and degrees of freedom without modifying any control parameters. Different from the previous works, the proposed...
A wavelet neural network (WNN)-based robust total-sliding-mode control scheme is developed for the synchronization of uncertain chaotic systems. The proposed control system offers a design method to drive the state trajectory to track a desired trajectory, and it is comprised of an adaptive WNN controller and a robust compensator. The adaptive WNN controller acts as the principal tracking controller,...
By the combination of the adaptive backstepping design with the dynamic surface control technique, an novel adaptive neural control approach is investigated for a class of pure-feedback stochastic nonlinear systems with multiple unknown time-varying delays. To overcome the design difficulty arising from the non-affine structure of pure-feedback stochastic systems, the mean value theorem is exploited...
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