Asymptotical Fault-Tolerant Time-Varying Tracking Control of Networked Mobile Flexible Manipulators Under Prescribed Performances and DoS Attacks
Xiangqian Yao, Xing Li, Zhijie Liu, Huanli Gao, Jianqiang Li, Yu Liu
Abstract
This article focuses on the asymptotic time-varying consensus tracking for the mobile dual flexible manipulators with unknown gain faults, prescribed performances, and denial-of-service (DoS) attacks. Our main contribution is to provide a novel distributed boundary control scheme for reaching the asymptotic consensus tracking of partial differential equation (PDE) coupled ordinary differential equation (ODE) systems under a heterogeneous linear leader. To this end, an adaptive distributed switched observer is first proposed to asymptotically observe the leader's signal, functioning effectively whether the network is under attack or not. Secondly, a servo system is introduced to generate the desired transverse displacement. Subsequently, the tracking errors of two angles and the moving positions of all agents can meet the prescribed transient performance requirements by utilizing barrier Lyapunov functions (BLFs) and finite-time performance functions (FTPFs). Moreover, adaptive radial basis function neural networks (RBFNNs) are used to approximate unknown parameters, and the adaptive technique is employed to compensate for gain faults and compound disturbances. The asymptotic convergence results and prescribed control performances for closed-loop systems are demonstrated using Lyapunov stability theory, and the well-posed problem is addressed using the operator semi-group methodology. Finally, the simulation results demonstrate the effectiveness of the designed boundary control laws.