Adaptive Quantized Tracking Control for Non-Linear Systems With Sensor Failure and Output Constraint

This paper focuses on adaptive quantized tracking control for a class of non-linear systems that experience sensor failure and output constraint. The non-linear functions in this study adhere to more general growth conditions compared to previous research. To address these challenges, a reduced-order observer is developed using only the measured output signal in the presence of sensor failure. Then by utilizing the barrier Lyapunov function technique, a quantized tracking controller is proposed. The study demonstrates that with this approach, all closed-loop signals remain bounded and the real tracking error converges to a small neighborhood around the origin, while ensuring that the real output signal adheres to the constraint. An illustrative example is also presented to validate the efficacy of the control strategy.