Observer-based Prescribed Performance Bipartite Consensus for Human-in-the-loop Multi-manipulator Systems

This paper investigates the problem of prescribed performance bipartite consensus tracking control of a class of human-in-the-loop multi-manipulator systems with communication topology represented by a signed directed graph. In order to converge to a prescribed accuracy within a prescribed time, an observer-based prescribed performance control strategy is proposed. First, a prescribed-time and prescribed-accuracy observer is designed to estimate the leaderś output information. Meanwhile, the bipartite consensus of observer outputs is achieved through cooperation/competition information exchange. Notably, the designed observer does not require inputs and higher-order derivatives of outputs of the leader manipulator. In addition, an event-triggered mechanism without Zeno behavior is adopted to reduce the communication burden among different manipulators. Second, the constrained output tracking problem for manipulator systems is transformed into an unconstrained stability problem for error systems by using backstepping and error transformation techniques. Subsequently, an output regulation controller for manipulator systems is designed based on observer outputs. It is worth mentioning that the proposed control strategy does not necessitate prior knowledge of the systemś initial states and avoids the issue of infinite control gains at prescribed time, thereby enhancing the systemś reliability. Finally, simulation results demonstrate the feasibility and superiority of the proposed control strategy. © 2024 Science Press. All rights reserved.