Adaptive Cooperative Control Of Fully State Constrained Nonlinear Multi-agent System

Nowadays,with the rapid development of industrial technology,UAV formation,robot cooperation and other fields are inseparable from the support of control theory,therefore,higher requirements are put forward for the consensus tracking control method of multiagent system.This paper deeply discusses the full-state constraints adaptive consessus tracking control algorithm for nonlinear multi-agent systems.On the one hand,a consensus tracking control algorithm suitable for the problem of unknown control direction in coopetitive networks is proposed.On the other hand,a full-state constraints adaptive consensus tracking control algorithm suitable for individuals with nonstrict feedback structure and requiring finite time convergence is proposed.The applicable full state constraints adaptive tracking control algorithm can better match the physical system of practical engineering,and solve the problems of slow convergence speed and poor antiinterference in the case of traditional control scheme.The central works of proposed research are summed up as:1.For general nonlinear multi-agent systems,a consensus tracking control method considering full-state constraints is proposed in this paper,which is based on command filtering backstepping and barrier Lyapunov function.The second-order filter is applied to solve the computational explosion caused by backstepping,the error compensation signal is designed to correct the error produced by the filter.Combining fuzzy logic system and adaptive control technology to approach the nonlinear dynamics of the system.The designed control law can achieve the function of state constraints and ensure the consensus tracking performance to achieve the convergent goal.At last,the good performance of the algorithm is verified by simulation comparison experiments.2.Aiming at the problem of adaptive tracking control algorithm for nonlinear coopetition multi-agent systems with unknown control direction and full state constraints,this paper designs the command filtered backstepping control signal,uses the weighted directed graph to describe the coopetition relationship,the Nussbaum function to solve the problem of unknown control direction,and the barrier Lyapunov function to prove that the system can control the states within the expected range.For the common computational explosion problem in backstepping,the influence is reduced by command filter,and combined with error compensation signals to reduce the noise influence in the filtering mechanism.Fuzzy logic system and adaptive control algorithm approximate the unknown nonlinear dynamics.At last,the good performance of the algorithm is verified by simulation experiments.3.For nonstrict feedback nonlinear multi-agent systems,a consensus tracking control algorithm considering finite time convergence and full-state constraints is proposed.By using fractional power function,the finite-time convergence of the system is ensured.The computational explosion problem caused by the backstepping process is eliminated by the command filter,and the error in the filtering process is reduced by the error compensation mechanism.Fuzzy logic system and adaptive control algorithm redescribe the unknown nonlinear dynamics.In particular,the nonstrict feedback problem of state variables is solved by using the properties of basis function in fuzzy logic system.At the same time,the barrier Lyapunov function is introduced to ensure that all system states and compensated tracking error signals are constrained within the expected range.At last,the good performance of the algorithm is verified by simulation comparison experiments.