Hui Bi, Weitian He, Xiaowei Wang, Tao Zou, Zhijia Zhao
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Adaptive fault-tolerant control of a nonlinear 2-DOF helicopter system with prescribed performance
This study investigates a novel tracking control with prescribed performance for an uncertain nonlinear 2-DOF helicopter subject to actuator failure. The control design aims to address partial actuator faults, and to mitigate their effects, an adaptive auxiliary variable is introduced. Additionally, a neural network is employed to accurately approximate the system uncertainties. The prescribed performance is formulated as time-varying constraints, and the barrier Lyapunov function (BLF) technique is applied to achieve the constrained control. Finally, the stability analysis of the closed-loop system is provided, and the validity of the proposed control scheme is illustrated through a simulation study on the 2-DOF helicopter system.
期刊介绍:
IET Control Theory & Applications is devoted to control systems in the broadest sense, covering new theoretical results and the applications of new and established control methods. Among the topics of interest are system modelling, identification and simulation, the analysis and design of control systems (including computer-aided design), and practical implementation. The scope encompasses technological, economic, physiological (biomedical) and other systems, including man-machine interfaces.
Most of the papers published deal with original work from industrial and government laboratories and universities, but subject reviews and tutorial expositions of current methods are welcomed. Correspondence discussing published papers is also welcomed.
Applications papers need not necessarily involve new theory. Papers which describe new realisations of established methods, or control techniques applied in a novel situation, or practical studies which compare various designs, would be of interest. Of particular value are theoretical papers which discuss the applicability of new work or applications which engender new theoretical applications.