Observer-Based Adaptive Prescribed- Time H∞ Coordinated Control for Multiple Robot Manipulators With Prescribed Performance and Input Quantization

In this paper, a prescribed-time adaptive H_{\infty } cooperative strategy with novel prescribed performance and input quantization based on a leader state observer is proposed for uncertain multiple robot manipulators. First, a novel prescribed performance function is introduced into the asymmetric log-type barrier Lyapunov function, which can limit angle errors and reduce the loss of communication resources among multiple robot manipulators. Second, a new prescribed-time leader state estimation observer is proposed to estimate the leader's state information and pass it to the other followers without acceleration information. Third, a prescribed-time adaptive command filter is designed to solve the "explosion of the complexity" problem and improves the convergence performance of the control system. Fourth, an adaptive prescribed-time H_{\infty } cooperative controller with novel prescribed performance and input quantization is designed. Finally, simulation examples are presented to evaluate the stability of the proposed control system.