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An augmented system is first constructed by treating the sensor fault as an auxiliary state. An adaptive fault estimation scheme with an  H∞H_\\infty H∞​  performance criterion is then developed to simultaneously estimate the actuator and sensor faults. To achieve the tracking control, a nonlinear sliding mode-based state feedback control law is proposed depending on the estimated states and information about fault from the fault estimating unit. The efficacy of the suggested technique is evaluated using a nonlinear model of the multirotor unmanned aerial vehicle (UAV) system with six degrees-of-freedom (DoF) motion. The proposed method is implemented in the inner loop subsystem in order to obtain the attitude and altitude tracking while the outer-loop control is simply a PID controller. Several simulations on the nonlinear system are performed to prove the effectiveness of the proposed method compared with the existing methods.",[11,12,13,14,15,16],"Ashraf, Muhammad Ammar","Ijaz, Salman","Javaid, Umair","Hussain, Shariq","Anwaar, Haris","Marey, Mohamed",[18,19,20,21,22,23],"0000-0002-4845-9422","0000-0003-1483-4754","0000-0002-4263-7849","0000-0003-2093-7274","0000-0002-4274-3641","0000-0002-2105-7239",2021,"https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2021.3137388","W4206620940","IEEE Access","a-robust-sensor-and-actuator-fault-tolerant-control-scheme-for-nonlinear-system.png",[30,31,32,33,34,35,36,37,38,39,40,41,42,43],"Control theory (sociology)","Actuator","Nonlinear system","Computer science","Fault tolerance","Control engineering","Sliding mode control","Controller (irrigation)","Fault (geology)","Attitude control","Multirotor","Engineering","Control (management)","Artificial intelligence",{"type":45,"children":46,"toc":210},"root",[47],{"type":48,"tag":49,"props":50,"children":51},"element","p",{},[52,55,208],{"type":53,"value":54},"text","In this article, a new fault-tolerant control (FTC) method is presented for the Lipschitz nonlinear systems that is capable of handling the actuator faults, sensor faults, unknown external disturbances, and system uncertainties. 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