摘要
This paper proposes a novel adaptive predefinedtime control strategy for the n-link robotic multi-agent systems(MASs)to achieve the consensus tracking control.First,unlike existing research on the control problems of a single robotic manipulator system,the consensus tracking control problem of the robotic MASs is studied.Then,in contrast to the finite-time and fixed-time control theories,the controller constructed based on the predefined-time control theory enables the user to define the convergence time of each agent in advance,regardless of the initial state and parameters of the system.The radial basis function neural networks(RBFNNs)are applied to approximate the unknown functions during the controller design process.Only one parameter is updated online,which saves computational costs.Moreover,to deal with the shortage of network resources that may occur when the robotic MASs perform complex tasks,the controllers are constructed by combining the switching threshold event-triggered control(ETC)mechanism to save communication resources.Finally,a simulation example demonstrates the efficacy of the proposed control strategy.
