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For a class of switched nonlinear systems with unmatched external disturbances and unknown backlash-like hysteresis, an adaptive fuzzy-based control strategy is proposed to handle the anti-disturbance issue. The unmatched external disturbances come from a switched exosystem. Our aim is to achieve the output tracking performance and the disturbance attenuation by using the adaptive fuzzy-based composite anti-disturbance control technique. First, based on the fuzzy logics, we design a switching adaptive fuzzy disturbance observer to estimate unmatched external disturbances. Second, a composite switching adaptive anti-disturbance controller is constructed. By means of the backstepping technique, disturbance estimations are added in each virtual control to offset the unmatched disturbances, which results in the different coordinate transformations. At last, the availability of the proposed approach is illustrated by a mass-spring-damper system. [ABSTRACT FROM AUTHOR]

This paper investigates the finite-time adaptive neural control and almost disturbance decoupling problems for multi-input/multi-output (MIMO) nonlinear systems with disturbances and non-strict-feedback structure. In the design procedure of the adaptive controller, neural networks are employed to estimate the unknown nonlinearities and Young's inequality is utilized to cope with the disturbance terms derived from all subsystems. In order to characterize the disturbance attenuation performance of finite-time adaptive control, a criterion named finite-time almost disturbance decoupling is first developed. Under this criterion, an adaptive neural controller is designed via the backstepping method and the appropriate selection of Lyapunov function. It is revealed that the proposed controller can guarantee all variables of the closed-loop system are bounded, and the performance of finite-time almost disturbance decoupling is realized. Finally, a practical example is employed to validate the effectiveness of the designed controller. [ABSTRACT FROM AUTHOR]

Abstract In this paper, the multiple model strategy is applied to the adaptive control of switched linear systems to improve the transient performance. The solvability of the adaptive stabilization problem of each subsystem is not required. Firstly, the two-layer switching mechanism is designed. The state-dependent switching law with dwell time constraint is designed in the outer-layer switching to guarantee the stability of the switched systems. During the interval of dwell time constraint, the parameter resetting adaptive laws are designed in the inner-layer switching to improve the transient performance. Secondly, the minimum dwell time constraint providing enough time for multiple model adaptive control strategy to work fully and maintaining the stability of the switched systems is found. Finally, the proposed switched multiple model adaptive control strategy guarantees that all the closed-loop system signals remain bounded and the state tracking error converges to zero. [ABSTRACT FROM AUTHOR]