Adaptive control for a class of nonlinear chaotic systems with quantized input delays

This paper proposes adaptive prediction-based control design for nonlinear chaotic systems in the presence of input quantization with actuator delay. A class of sector-bounded quantizer, namely the hysteresis quantizer, has been used to quantize the control signal. Adaptive scheme is utilized to estimate unknown parameters of the nonlinear chaotic system. A new prediction vector is introduced to compensate actuator delay for nonlinear systems with unknown parameters. The proposed controller does not require the restrictive conditions for quantized parameters in contrast to some existing control schemes for systems with input quantization. By error analysis, it is insured that the upper bound of the state vector norm is limited. Moreover, a maximum allowable upper bound for actuator time-delay is achieved and is guaranteed that for any input delay less than this value, the closed-loop system is stable. To show the efficiency of the proposed method, it is applied to brushless DC motor and Chua's circuit with delayed hysteresis input and compared to the existing results in the literature. Simulation results show that the proposed method is able to compensate actuator time-delay with hysteresis quantized input for a class of nonlinear systems having unknown parameters. The robustness and efficiency of the suggested approach are illustrated by comparative simulation results. (C) 2019 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.