Finite-time multi-target tracking based on the super-twisting algorithm

This paper focuses on multi-agent systems with known boundaries of complex disturbance factors, where the specific disturbance factors include parameter uncertainties and external perturbations. A finite-time hierarchical control algorithm based on the super-twisting algorithm is proposed to solve the finite-time multi-target tracking control problem.Firstly, the Euler-Lagrange dynamic equations are adopted to model the multi-agent system, and the control objectives of the considered problem are put forward simultaneously. Secondly, by utilizing the super-twisting algorithm and a tracking error observer, a finite-time hierarchical control algorithm is designed, which consists of a local layer algorithm and an estimation layer algorithm. Then, stability analysis is conducted on the estimation layer algorithm: the finite-time stability of the closed-loop system for the estimation layer is derived via the Lyapunov stability principle. Subsequently, stability analysis is performed on the local layer algorithm, and the stability conditions for the local layer are deduced also based on the Lyapunov stability principle. Finally, simulations are carried out using MATLAB software. An Euler-Lagrange system simulation model is established, and 13 manipulators are selected and divided into 3 sub-networks for simulation. The simulation results show that the manipulators in each sub-network can track the state of the corresponding leader within a finite time, with small tracking errors, short tracking time, and strong anti-disturbance capability, which verifies the effectiveness of the proposed control method.