Predefined‐time control for Euler–Lagrange systems with model uncertainties and actuator faults

Abstract

Summary A novel adaptive predefined‐time tracking control algorithm is proposed for the Euler–Lagrange systems (ELSs) with model uncertainties and actuator faults. Compared with traditional finite‐time and fixed‐time studies, the system output tracking error under the proposed predefined‐time controller converges to a small neighborhood of zero in finite time, whose upper bound is exactly a design parameter in the control algorithm. For the uncertain model, radial‐based function neural network (RBFNN) is utilized to approximate the continuous uncertain dynamics. To deal with the actuator faults, an adaptive control law is involved in the fault‐tolerant controller. In order to achieve the predefined‐time bounded, a novel predefined‐time sliding mode surface is designed. It is proved that the tracking error vector trajectory of closed‐loop system is semi‐globally uniformly ultimately predefined‐time bounded, and the upper bounds of both the system settling time and the corresponding output tracking error can be adjusted with a simple parameter. Simulation examples finally demonstrate the effectiveness of the proposed control algorithm.