Abstract:In this paper, two active fault-tolerant control (AFTC) structures are proposed for multiplicative and additive actuator faults respectively. Considering that the traditional generalized internal model control (GIMC) changes the dynamic input-output relationship of the original system, more exact fault information is employed to design the robustification controller of GIMC with the help of fault diagnosis observers. Further, a feedforward compensation unit and a feedback compensation unit are respectively des… Show more
“…Researchers use two methods to solve the FTC problem: active FTC (Guo et al, 2019; Shen et al, 2019) and passive FTC (Hasan et al, 2020; Patel and Shah, 2019). Passive FTC uses an invariant controller to ensure the closed-loop system is robust to specific faults.…”
The vibration control problem was investigated in this study in the presence of unknown loss of actuator effectiveness fault and loss of sensor effectiveness fault in a flexible aircraft wing system. A series of partial differential equations was used as the mathematical model of the wing with unknown boundary disturbances. An adaptive fault-tolerant boundary controller was designed accordingly. All signals of the closed-loop control system are globally uniformly bounded and the controlled state asymptotically converges. Numerical simulations were conducted to validate the proposed control scheme.
“…Researchers use two methods to solve the FTC problem: active FTC (Guo et al, 2019; Shen et al, 2019) and passive FTC (Hasan et al, 2020; Patel and Shah, 2019). Passive FTC uses an invariant controller to ensure the closed-loop system is robust to specific faults.…”
The vibration control problem was investigated in this study in the presence of unknown loss of actuator effectiveness fault and loss of sensor effectiveness fault in a flexible aircraft wing system. A series of partial differential equations was used as the mathematical model of the wing with unknown boundary disturbances. An adaptive fault-tolerant boundary controller was designed accordingly. All signals of the closed-loop control system are globally uniformly bounded and the controlled state asymptotically converges. Numerical simulations were conducted to validate the proposed control scheme.
“…Force/position control, as a useful way to tackle contacting environment tasks of manipulators, have attracted extensive attentions in practices. Recently, force/position control approaches have been divided into parallel force/position control [1], hybrid force/position control [2], impedance [3] etc. Hu et al [4] addressed force/position control problem of the manipulator via sliding mode control.…”
A critic-observer decentralized force/position approximate optimal control method is presented to address the joint trajectory and contacted force tracking problem of modular and reconfigurable manipulators (MRMs) with uncertain environmental constraints. The dynamic model of the MRM systems is formulated as an integration of joint subsystems via extensive state observer (ESO) associated with the effect of interconnected dynamic coupling (IDC). A radial basis function neural network (RBF-NN) is developed to deal with the IDC effects among the independent joint subsystems. Based on adaptive dynamic programming (ADP) approach and policy iteration (PI) algorithm, the Hamilton–Jacobi–Bellman (HJB) equation is approximately solved by establishing critic NN structure and then the approximated optimal control policy can be derived. The closed-loop manipulator system is proved to be asymptotic stable by using the Lyapunov theory. Finally, simulation results are provided to demonstrate the effectiveness and advantages of the proposed control method.
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