Adaptive Finite-Time Control of Nonlinear Quantized Systems With Actuator Dead-Zone

This paper investigates a finite-time control problem of nonlinear quantized systems with actuator dead-zone in a non-strict feedback form. By combining a simplified dead-zone model and the sector-bound characteristic of a hysteretic quantizer, the control difficulties caused by the coexistence of unknown actuator dead-zone and control signal quantization effect are overcome. By applying the approximation ability of neural network systems, an novel neural adaptive controller is constructed, which can compensate the unknown control gain. The designed neural controller can ensure the transient performance of nonlinear quantized systems with actuator dead-zone in finite-time. Based on the Bhat and Bernstein theorem, the finite-time stability of system is proved. Finally, a numerical example is given to verify the validity of the proposed approach.