| Distributed coordinated tracking control for multi-agent systems is one of the research hotspots in the control field in recent years,which is widely used in industry,aerospace and medical fields.In practice,each agent system is represented by a specific mathematical model.Euler-Lagrange system as a special nonlinear system,is characterized by uncertainty,nonlinearity and strong coupling.It can represent a variety of electrical or mechanical system dynamics.Therefore,it is widely used in multi-agent systems research.In this paper,the uncertainties,coordinated tracking and convergence speed of multiple Euler–Lagrange systems are studied.The main research work is as follows:Firstly,the coordinated tracking problem of multi-agent system based on multiple Euler-Lagrange system is studied.Aiming at the internal nonlinearity of multiple Euler-Lagrange system,dynamic surface control technology is introduced based on backstepping method to solve the computational complexity problem in controller design process.In order to solve the problem of coordinated tracking speed of multi-agent system,a distributed fixed-time coordinated tracking control algorithm is designed.Finally,five manipulator systems are selected for comparative simulation under two initial states,which verifies that the system achieves coordinated tracking in fixed time and solves the problem that convergence time depends on initial state in finite time theory.Secondly,considering the uncertainty and nonlinearity of the model parameters in the practical engineering application of multiple Euler-Lagrange system,an adaptive control method is introduced to estimate the uncertain parameters of the model,and the influence of the nonlinearity and uncertainty on the steady-state performance of the system is solved.Under the leader-follower strategy,a distributed fixed-time coordinated tracking control algorithm based on adaptive is designed to realize the coordinated tracking of multi-agent systems and ensure the system convergence in fixed time.The superiority of the proposed algorithm is verified by the simulation of multi-manipulator system.Finally,the coordinated tracking control and convergence rate problem of multiple Euler-Lagrange systems with unknown perturbations and model uncertainties are studied.Adaptive RBF neural network is adopted to approximate the uncertainty and external disturbance of the system,and further solve the internal uncertainty and external disturbance of the system.Combined with fixed time control theory,a distributed fixed time tracking control algorithm based on RBF neural network was designed respectively,and the stability of the system in fixed time was proved.Finally,simulation results show that the proposed algorithm can further improve the steady-state performance and accelerate the convergence rate. |
