Research On Depth Control Algorithm Of Deep Sea Profiling Float Based On RBF-PID

The ocean is not only rich in resources,but also closely related to the climate.Carrying out ocean exploration and building a maritime power has become China's research and development trend.Self-sustaining profiling floats can achieve independent agility by adjusting their buoyancy.The deployment of self-sustaining profiling floats and the construction of a comprehensive ocean observation network are of great significance for preventing catastrophic climate and understanding the marine environment.At present,most of the profiling floats deployed are shallow sea floats below 2000 meters.The observation system of shallow sea exploration has been basically improved,and deep sea exploration is still in its infancy.Deep-sea selfsustaining profiling floats extend the depth of ocean exploration to deep seas below4000 meters,providing possibilities for understanding the deep sea and developing deep-sea resources.Depth-deep hovering is an important task of profiling floats.Its purpose is to collect hydrological data of a certain depth by hovering,and it is of great significance to improve the precision of the depth control to improve the accuracy of data acquisition.The unidirectional controllability of the buoyancy drive system and the complexity of the marine environment put forward higher requirements for the deep-seated control system of the deep-sea self-supporting profiling floats.In this thesis,a RBF-PID-based deep-sea profiling float depth control algorithm is proposed to achieve high-precision depth control.Firstly,a nonlinear dynamic model is established by analyzing the structural characteristics of the buoyancy drive system of the profiling float.The modeling process fully considers the nonlinear characteristics of each parameter and then analyzes each parameter.Comparing the data collected by the floating stage of the profiling float sea test process with the simulation results,the accuracy of the proposed nonlinear model is verified,which paves the way for high precision depth control.Secondly,the RBF-PID algorithm is added to the nonlinear model of deep-sea selfholding profiling floats,and the PID controller gain is adjusted by RBF neural network.The simulation results show that the RBF-PID depth control algorithm has the ability to improve the depth control accuracy of deep-sea self-holding profiling floats,reduce the steady-state error,and enhance the anti-interference ability of the system.At the same time,the change of motor current is analyzed to calculate the power consumption of the 4000 meters deep control process.Finally,the principle and simulation system interface of the deep-sea self-holding profiling floats pressure test are introduced.The influence of random error collected by the pressure test process on the RBF-PID depth control algorithm of the profiling float is analyzed.The results show that the proposed control method can resist the interference of random error.According to the nonlinear dynamic model,the simulation interface is set to improve the operability of the simulation process and the intuitiveness of the simulation results.The maximum depth of the deep-sea self-sustaining profiling float proposed in this paper exceeds 4000 meters,and its depth control accuracy at 4000 meters can be stabilized at around ±12 m.Profiling float depth control algorithm based on RBF-PID has strong robustness.The buoy anti-interference ability is significant enhanced.