Research On Trajectory Tracking Control Strategy For Underwater Unmanned Aerial Vehicle System With Uncertain Parameter

With the development of science and technology,the application range of autonomous underwater vehicles(AUVs)is more and more extensive and it plays a very important role in underwater search and rescue,military missions,and many other fields.However,the autonomous underwater vehicle is a highly uncertain and strongly coupled nonlinear system,which makes the precise trajectory tracking control of the autonomous underwater vehicle difficult.This thesis focuses on the design of trajectory tracking controllers for autonomous underwater vehicles with input saturation,external disturbances,and model parameter uncertainty.The specific research content is as follows:First,considering external disturbances,a novel command filtered backstepping control strategy is proposed for autonomous underwater vehicle systems with unknown model parameters and input saturation.Firstly,the virtual control input of autonomous underwater vehicle system is designed based on the backstepping method.Secondly,command filters are used to solve the problems of unmodeled dynamics and external disturbances.Thirdly,the hyperbolic tangent function is used to deal with the input saturation problem.Then,the stability of the proposed control strategy is demonstrated through Lyapunov stability theory.Finally,the comparative simulation results indicate the effectiveness of the proposed command filtered backstepping control strategy.Second,considering external disturbances,an improved adaptive command filtered backstepping control strategy is proposed for autonomous underwater vehicle systems with completely unknown model parameters and input saturation.Firstly,the command filter is used to deal with model parameter uncertainty and external disturbances.Secondly,a virtual control input function is constructed to eliminate the influence of unknown time-varying inertia matrix on controller design.Thirdly,the adaptive control technique is introduced to estimate the unknown time constant matrix of the controller.Then,the Lyapunov stability theory proves that the trajectory tracking error ultimately converges to a small neighborhood near the origin.Finally,simulation results indicate that the proposed adaptive command filtered backstepping control strategy can still effectively track the reference trajectory in the presence of model parameter uncertainty.Third,considering input saturation,a fixed-time adaptive neural network command filtered backstepping tracking controller is designed for the autonomous underwater vehicle system with completely unknown model parameters and external disturbances.Firstly,a novel virtual control input is constructed to solve the singularity problem in the design process of the fixed-time controller.Secondly,command filter and adaptive neural network are used to solve the problem of model parameter uncertainty in the autonomous underwater vehicle system.Thirdly,stability analysis proves that trajectory tracking error can converge to a small neighborhood near the origin within a fixed time.Finally,simulation results demonstrate the effectiveness of the proposed control strategy.