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Adaptive Sensor-Fault Tolerant Control of Unmanned Underwater Vehicles With Input Saturation
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作者 xuerao wang Qingling wang +2 位作者 Yanxu Su Yuncheng Ouyang Changyin Sun 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第4期907-918,共12页
This paper investigates the tracking control problem for unmanned underwater vehicles(UUVs)systems with sensor faults,input saturation,and external disturbance caused by waves and ocean currents.An active sensor fault... This paper investigates the tracking control problem for unmanned underwater vehicles(UUVs)systems with sensor faults,input saturation,and external disturbance caused by waves and ocean currents.An active sensor fault-tolerant control scheme is proposed.First,the developed method only requires the inertia matrix of the UUV,without other dynamic information,and can handle both additive and multiplicative sensor faults.Subsequently,an adaptive fault-tolerant controller is designed to achieve asymptotic tracking control of the UUV by employing robust integral of the sign of error feedback method.It is shown that the effect of sensor faults is online estimated and compensated by an adaptive estimator.With the proposed controller,the tracking error and estimation error can asymptotically converge to zero.Finally,simulation results are performed to demonstrate the effectiveness of the proposed method. 展开更多
关键词 Asymptotic stability fault-tolerant control input saturation robust integral of the sign of error unmanned underwater vehicle
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Adaptive tracking control of high-order MIMO nonlinear systems with prescribed performance
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作者 xuerao wang Qingling wang Changyin SUN 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2021年第7期986-1001,共16页
In this paper,an observer-based adaptive prescribed performance tracking control scheme is developed for a class of uncertain multi-input multi-output nonlinear systems with or without input saturation.A novel finite-... In this paper,an observer-based adaptive prescribed performance tracking control scheme is developed for a class of uncertain multi-input multi-output nonlinear systems with or without input saturation.A novel finite-time neural network disturbance observer is constructed to estimate the system uncertainties and external disturbances.To guarantee the prescribed performance,an error transformation is applied to transfer the time-varying constraints into a constant constraint.Then,by employing a barrier Lyapunov function and the backstepping technique,an observer-based tracking control strategy is presented.It is proven that using the proposed algorithm,all the closedloop signals are bounded,and the tracking errors satisfy the predefined time-varying performance requirements.Finally,simulation results on a quadrotor system are given to illustrate the effectiveness of the proposed control scheme. 展开更多
关键词 Adaptive tracking control Prescribed performance Input saturation Disturbance observer Neural network
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