Tangent barrier Lyapunov function‐based constrained control of flexible manipulator system with actuator failure

Abstract

This article puts forward an adaptive neural network fault-tolerant control scheme under the state constraints for the flexible manipulator system with uncertain terms. The dynamic model of the system is described by partial differential equations. The tangent barrier Lyapunov functions are chosen in the design process for the sake of ensuring that all states in the system satisfy the constrained conditions. The uncertainties resulted from load mass, hub inertia, and bending stiffness in the system are approximated by using the universal approximation property of neural networks. The adaptive method is used to counteract the influence of joint motor actuator failure. At the same time, combining with the backstepping design framework to design effective controllers to assure that all signals in the closed-loop system are bounded. Lyapunov stability analysis method is used to prove the stability of the system. Finally, the simulation results prove the availability of the raised control method.

Quantized feedback control of linear system with performance barrier

“…The authors in Reference 22 used exponent‐dependent barrier Lyapunov function (BLF) to study the tracking control problem for a class of uncertain nonlinear parametric strict‐feedback systems under actuator faults. The BLF was applied in the manipulator systems and autonomous underwater vehicles 23,24 . In recent years, many works on safety‐critical control systems employed a so‐called control barrier function (CBF) approach 25,26 .…”

“…The BLF was applied in the manipulator systems and autonomous underwater vehicles. 23,24 In recent years, many works on safety-critical control systems employed a so-called control barrier function (CBF) approach. 25,26 By merging the control Lyapunov function (CLF) and the concept of CBF, a novel nonlinear control method was proposed in References 27 for solving the stabilization problem of nonlinear affine systems with guaranteed safety.…”

Adaptive multiple estimation fault-tolerant control for teleoperation systems with deferred time-varying output constraints

“…(1) The initial value is known, but the system's output or tracking deviation violates the initial constraint. In this scenario, the BLF-based control schemes in [9][10][11][14][15][16][17][18][19][20][21][22][23][24] cannot be directly applied unless a new BLF is reselected;…”

“…(1) Unlike existing BLF-based constraint treatments in [9][10][11][14][15][16][17][18][19][20][21][22][23][24], which require that the system's initial conditions be within the constraint boundaries, the shifting function is integrated into the ABLF, thus removing the strict assumptions involved in dealing with the constraint issues. (2) An adaptive fault-tolerant control law based on NNs and DOs is developed to handle the issue of teleoperation systems suffering from potentially actuatorfailure, which improves the robustness, adaptability and security of the teleoperation system in the face of complex and extremely dangerous environments.…”

“…Violating constraints will lead to degradation of control performance, system instability, or even catastrophic accidents. Over the past decade, applications of BLF [9][10][11][14][15][16][17][18][19][20][21][22][23][24] to address the control concerns of nonlinear systems with constraints have become a popular issue, which has attracted extensive attention and research from many scholars. In [9], Yang combines the log-type BLF with the fast terminal sliding mode theory to address the error constraint issue in teleoperation systems.…”