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This paper deals with the problem of robust output feedback control for a class of 5DOF upper-limb exoskeleton robot. It is able to assist with shoulder, elbow and wrist joint movements. Robustness is assured for the proposed controller in the presence of model uncertainties. Ultimate boundedness is proved for the presented adaptive observer-based controller. The other advantage of the proposed method is that the implemented information for feedback is only the measurement of position. The estimation of velocity and acceleration is provided by an adaptive observer without additional sensors. By utilizing a novel adaptive logic-based switching control scheme, a trajectory tracking performance is well achieved with a tunable error bound. The simulation example also verifies the effectiveness of the proposed control scheme.

This paper deals with active fault tolerant controller design against time-varying actuator fault, aiming to improve the robustness, sensitivity of fault detection and the rapidity of whole diagnosis and compensation procedure. A high-gain observer technique is developed to design a residual signal with the estimation error of system states and the derivatives of system output. Then a reconfiguration controller is directly constructed based on the fault information from diagnosis procedure. A qualitative relation is derived to connect the robustness, rapidity and sensitivity of the proposed fault diagnosis scheme with the observe parameters. By prescribing the observer/controller parameters, the set of detectable faults, the time of detection and compensation and the bound of the closed-system signals are quantified. Finally, the theoretical results are illustrated by a simulation example of surfacemounted permanent magnet synchronous motors (PMSM).

The point of this article is the sensor fault estimation and fault‐tolerant controller design for IT2 fuzzy systems via sliding mode approach. In order to estimate accurately the system states and sensor faults, a novel proportional and derivative sliding mode observer is introduced, which provide more design freedom and eliminate the effects of sensor faults. By splitting the operating domain and estimating the membership functions, a set of relaxation stability conditions subject to the information of membership functions and system states are obtained. Then, a sliding mode controller in form of IT2 fuzzy model is designed to stabilize the closed‐loop systems. An example of bolt‐tightening tool model is considered to demonstrate the validity of the proposed results.

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