Adaptive Cooperative Control Of Multiple Underwater Robot Systems With State Constraint

With the development and utilization of marine resources,the application scenario of autonomous underwater vehicle(AUV)is very extensive.Due to the development of intelligent control,the tracking control strategy of AUV has received more and more attention.This paper studies the distributed adaptive cooperative control problem of AUV with state constraints under different control strategies.A command filtered backstepping control scheme for multiple AUVs system with state constraints is proposed;Aiming at the problems of poor anti-interference and slow convergence speed in the case of asymptotic convergence,a finite-time distributed adaptive consensus tracking control scheme for multiple AUVs system with state constraints is proposed.The thesis mainly includes the following research contents:1.Aiming at the problem of adaptive consensus tracking for multiple AUVs system with state constraints.A command filtered backstepping control scheme with position state constraints based on radial basis function-neural network(RBF-NN)is proposed.In this scheme,the unknown nonlinear dynamics part is approximated by RBF-NN.The virtual control signal is filtered by command filter to avoid the problem of needing to use its differentiation.Error compensation is constructed to offset the filtering error caused by the filter.The proposed controller can ensure that the position tracking error converges to the desired neighborhood without exceeding the pre-defined state constraints.Finally,data analysis with Matlab,which proves the feasibility and correctness of the scheme.2.Considering the weak anti-interference and slow response of the asymptotic convergence control strategy in the tracking control of the AUV under state constraints,an adaptive command filtering finite-time control scheme was proposed.The control scheme not only solves the computational complexity problem by using a finite-time command filter but also constructs an error compensation signal to eliminate the filtering error,and uses the RBF-NN approximation technique to deal with the unknown nonlinear dynamics in the system.Finally,it is proved that the proposed controller can guarantee that the position tracking error converges to the desired neighborhood within a finite-time and does not exceed the pre-defined state constraints.A simulation confirms the feasibility and rationality of the controller.3.The research content extends from the finite-time tracking control of single AUV to the finite-time tracking control of multiple AUVs system.A new finite-time command filtered backstepping control scheme based on RBF-NN and Barrier Lyapunov function is proposed.Use finite-time command filters to handle virtual control signals,design error compensation mechanism to avoid the influence of filtering error on the system,and the RBF-NN approximation technology is used to deal with the unknown nonlinear dynamics of the system.The control scheme can guarantee that the consensus tracking error of the position state converges to the desired neighborhood of the origin in a finite-time,while not exceeding predefined constraints.Finally,the simulation confirms the feasibility and rationality of the controller,and compared with the progressive convergence control strategy and the finite-time dynamic surface control(DSC)strategy,it verifies that the control scheme has a faster convergence speed and better stability.