| Nowadays,with the rapid development of science and technology,more and more marine resources have been discovered.However,more than 90% of the marine resources are still unexplored.In the exploration of marine resources,advanced technology and equipments are essential.Underwater vehicles are the only important equipment that can work in the deep sea and play an important role in marine development.AUV plays an important role in marine development because of its good maneuverability and large range of operation.However,AUV often works in complex marine environments and its autonomous control needs to overcome strong coupling,non-linear features,and random distrubance such as ocean currents.To sum up,the motion control of AUV has become a very challenging subject.The thruster is an important power component of the AUV,and it is also the most prone component to failure.The timely diagnosis of the early fault of the thruster is of great significance to ensure the safety of the AUV itself.In this paper,based on the study of AUV dynamics model and weak fault feature extraction of thrusters,the region tracking control method for AUV is emphatically studied.Establishing a more accurate AUV dynamics model can lay the foundation for achieving accurate region tracking control.Firstly,this paper establishes the motion equation based on the motion features of AUV.Then,the AUV is subjected to a force analysis,which focuses on the problem of AUV buoyancy changes in the deep-sea environment.And analyze the features of seawater at different depths.Based on the relation between residual buoyancy and depth,and the performance of the experimental carrier "UVIC-I ",the restoring force matrix in the dynamics model is modified.Therefore,a more accurate AUV dynamics model is constructed in deep sea.The thrust loss term in the AUV dynamics model is related to thruster fault diagnosis of AUV.At the same time,the thruster fault diagnosis technology is a prerequisite to achieve more accurate region tracking control.The existence of self-noise and current distrubance during the operation of AUV makes it difficult to extract the thruster fault features of the weak fault signals.In view of this problem,this paper starts from the energy and frequency domain features of sensor signals and controller signals.Based on wavelet packet energy and Fast Fourier Transform,a weak fault feature extraction method is proposed and performs multi-source mapping and redundant description of weak thruster faults.The Matlab software was used to process the experimental data of the actual pool,and the method in this paper was compared with the traditional wavelet energy method,thereby verifying that the method in this paper has stable and high identification accuracy.The identified fault degree of thruster output can provide experimental conditions for region tracking control and be used as the basis for region tracking control.The performance of the motion controller is decreased due to the existence of complex current disturbance,modelling uncertainty and thruster fault in AUV operation,which will cause the tracking error to fail to converge asymptotically.In order to solve the problem,a controller for AUV region tracking control is first designed,and use the RBF neural network to identify the genernal uncertainty online.Through Lyapunov function,the region tracking error of the controller based on RBF neural network in this paper is deduced to converge uniformly and gradually.Through Matlab/Simulink software,simulations of region tracking control in different environments and different target regions are performed.Compared with the traditional region tracking controller based on the boundary potential energy function,the controller in this paper has better control effect with complex ocean current disturbance,modelling uncertainty and thruster fault.In the above study,it is found that when the actual initial position of the AUV deviates greatly from the initial point of the desired region,the traditional controller's control effect is not good,and even control fault may occur.To address this problem,a region tracking control system is developed for underwater vehicles with large initial deviation and general uncertainty.The developed system is a nonlinear cascaded system,consisting of two subsystems in series.The fixed gain controller of the first subsystem is designed to compensate for the region tracking error caused by the large initial deviation.In the second subsystem,the RBF neural network is adopted to approximate the general uncertainty along with the external disturbance and modelling uncertainty.According to the Lyapunov theory,the control law of the two subsystems and adaptive law of the second subsystem are derived to ensure the region tracking errors asymptotically converge to zero.Finally,through the Matlab/Simulink software,the validity of the control system is verified by a series of simulations under the environment of ocean current distrubance,modelling uncertainty,thruster fault,and even large initial deviation. |
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