Research On Key Issues Of A Deep-Sea Self-Sustaining Intelligent Profile Buoy System

In order to effectively improve the observation capabilities of ocean circulation laws such as ocean circulation and seawater energy exchange,and provide theoretical basis and technical support for the profile measurement of environmental elements in deep sea water,a deep-sea self-sustaining intelligent profile buoy is studied that is suitable for a depth of 0?4000m.The deep-sea self-sustaining intelligent profile buoy is referred to as the deep-sea intelligent buoy(DSIB).Several key issues of the DSIB system have been analyzed and studied.The key issues contain net buoyancy changes,overall flow field characteristics,dynamic modeling under complex sea conditions,and depth control strategy.The main research contents and research results are as follows:(1)Aiming at the problem that the DSIB closed-loop depth control system quickly converges to a predefined depth within a predefined control time range under ocean current disturbances,a finite–time boundedness(FTB)depth control strategy based on over shoot estimation in pole placements(OEIPP)method has been proposed in which variable gains are adjusted.The finite time transition matrix is established by using the state transition matrix method.The OEIPP method is introduced to carry out the norm estimation for the finite time transition matrix of the DSIB closed-loop depth control system.The convergence of FTB depth control strategy is proved.An adjustment rule of the control gains under different current disturbances based on the FTB depth control method is analyzed.Numerical simulation and experimental results show that the proposed depth control algorithm has better convergence and robustness compared with the traditional PID controller.(2)In order to eliminate the external interference caused by net buoyancy and water resistance of DSIB system in the actual depth positioning work and improve the depth control accuracy within the allowable depth error range of the actual hydrographic survey,the active–disturbance rejection depth control(ADRDC)depth controller is designed to by using the active disturbance rejection control method.In the ADRDC depth controller,an extended state observer and a non-linear state error feedback controller are designed to solve the external disturbance error compensation problem of the DSIB closed-loop depth control system under external disturbance.The control convergence of the aforementioned two kinds of controllers are verified by the Lyapunov stability principle.In view of the fact that the designed ADRDC depth controller has many parameters that are difficult to adjust and the control accuracy is easy to be reduced,a genetic algorithm based on quantum theory(QGA)is proposed to optimize the optimal parameter combination of the ADRDC depth controller.The genetic population evolution optimization of the main parameters of the ADRDC depth controller are realized by using the individual expression form of qubit and the and the adjustment strategy of quantum rotary gate.Aiming at the problems that the QGA algorithm needs more search space in the parameter optimization process and the speed and accuracy of global optimization is lower,an ADRDC depth controller based on genetic chaos particle swarm hybrid algorithm(GACPSO)is proposed.Taking the number of odd and even evolutions as the best combination point of the two population search algorithms,the global optimization calculation of genetic algorithm and the fast iterative calculation ability of chaos particle swarm optimization algorithm are maximized.The comparison of simulation and experimental results with the designed ADRDC depth controller show that the optimized ADRDC depth controller based on the aforementioned population intelligent search algorithms has better control accuracy and robust performance than the ADRDC depth controller before optimization,and the ADRDC depth controller based on GACPSO algorithm has the best control effect.(3)In view of the practical problem that the how much ballasting weight should be added when the DSIB system with glass spherical pressure-resistant structure goes down to a predefined depth,the net buoyancy analysis method based on the ballast weight deviation is proposed from the experimental point of view.The feasibility of the proposed method is verified by the deep-sea high-pressure simulation experiment.The fluctuation relationship law between the diving depth and the ballasting weight deviation is obtained within a depth range of 0 to 4000 m.It was found through experiment that the ballasting weight changes fluctuate between 0.05 and 0.15 g by increasing the diving depth by 1 m.At the same time,according to the experiment results,the total volume of the external shell of DSIB system at 1 atm is 0.0524m³,and the total compression coefficient of the external shell is 2.88×10^-10/Pa.Based on the aforementioned key parameters of DSIB system obtained by the ballasting weight deviation method,in order to solve the net buoyancy self-adaptive adjustment problem of DSIB system in different sea areas for different seasons of the world,so as to minimize the adjustment oil needed for the precise positioning of the buoyancy-driven system at a predefined depth,the ballasting weight(BW)model and minimum oil content(MOC)model for DSIB system are proposed by introducing the double e exponential function models of actual density and actual temperature distribution in the oceans.The proposed models provide a important theoretical guidance for extending the sustainable operation of the DSIB system in global ocean.