Fuzzy Adaptive Control for Wireless Optimal Charging Gantry Robot System This paper mainly studies the realization of the wireless optimal charging gantry robot system using type2 fuzzy adaptive control for mobile rechargeable devices. The wireless charging system is based on the energy management systems using the adaptive control algorithm to achieve the maximum charging power control. The type2 fuzzy dynamic model is used to approximate the charging system in accordance with current standards without constructing sector deadzone inverse, where the parameters of the fuzzy model are obtained both from the fuzzy inference and online update laws. The tracking trajectory tore chargeable devices including forwardinverse kinematics written by C in Visual Studio is used for obtaining the joint angles of the xyz table corresponding to the desired trajectory. By feedback the charging current from the coil to detect position of the mobile devices, the optimal charging device tracking algorithm is given for obtaining the shortest distance and maximum power transmission between the induction coil and the rechargable device. Based on the Lyapunov criterion and Riccatiinequality, the control scheme is derived to stabilize the closedloop system such that all states of the system are guaranteed to be bounded due to uncertainties, deadzone nonlinearities, and external disturbances. The advantage of the proposed control scheme is that it can better handle the vagueness or uncertainties inherent in linguistic words using fuzzy set membership functions with adaptation capability by linear analytical results instead of estimating nonlinear system functions as the system parameters are unknown. Finally, both simulation and experimental results are provided to verify the validity of the wireless optimal charging system.

Adaptive Fuzzy Inverse Compensation For Actuator Deadzone With Piecewise Timevarying Parameters Existing adaptive control methods for canceling actuator deadzone nonlinearity are restricted to an assumption that the deadzone parameters are constants. But in realistic circumstances, such assumption cannot be always satisfied because the deadzone parameters may vary with time and even experience abrupt jumps. To address this issue, a new adaptive fuzzy control strategy is proposed to handle such dynamic deadzone characteristics. Specifically, our scheme is developed with a modified tuning functions method and a novel piecewise Lyapunov analysis. Moreover, to improve the system transient performance in the presence of the dynamic deadzone nonlinearities, prescribed performance bounds based method is incorporated with the backstepping design. It is proved that besides the system stability, the tracking error is always preserved in a predefined compact set irrespective of the sudden parameter jumps. Simulation example demonstrates this conclusion.