Prescribed-time adaptive quantized control for nonlinear systems with actuator hysteresis and external disturbance via compound disturbances observer

This paper develops a novel prescribed-time quantized adaptive control algorithm for nonlinear systems with actuator hysteresis based on a compound disturbances observer (CDO). The concept of non-time-varying scaling function coordinate transformation is proposed to achieve prescribed-time control, which ensures that the tracking error converges to a vicinity of the origin within a prescribed time without relying on initial conditions, while reducing the complexity of the controller design. Moreover, by combining multi-dimensional Taylor network (MTN) with a disturbance observer, an improved new CDO is developed which accounts for both unknown external disturbances and the approximation error of MTN, enhancing the disturbance rejection capabilities of system. Additionally, a second-order integral filter is employed to mitigate the complexity explosion caused by traditional backstepping design process, while further improving the disturbance attenuation. The developed control scheme not only resolves the conflict of coexisting hysteresis and quantization input but also ensures the boundedness of signals in the closed-loop system. The superiority of the scheme is demonstrated through the simulation part.