| The ocean has been actively developed since 21 century.Argo(Array for Real-time Geostrophic Oceanography)program was established as a sub-program of the "Global Ocean Observing System".Argo buoy is generally used to observe the temperature and salinity of the deep-sea area.The real-time data observed through the program is used in research of meteorology and oceanography,which is significant for researching,developing and managing of the ocean.The precision and anti-noise capability of depth control strategy at present is weak,which will make a difference in the quality of buoy data to a certain extent.Therefore,we proposed a depth control strategy for deep-sea intelligent Argo buoy based on fuzzy adaptive PID to improve the precision of the depth control and anti-noise capability.The general study for this thesis is as follow:1.Analyzed the motion process,drew the free body diagram,and modelled system dynamics of the deep-sea intelligent Argo buoy.Created simulation model of with Simulink,which lay foundation for research of depth control strategy.2.Designed increment PID controller for the depth control based on the dynamics model of the buoy.Designed fuzzy controller for the PID controller to achieve real-time tuning for the gain parameters.Simulation results demonstrate that dynamic performance of fuzzy adaptive PID controller is better than increment PID controller.3.Analyzed the motion feature of the deep-sea intelligent Argo buoy,and designed Kalman filter for the controller to reduce measurement noise.Improved the dynamic performance of depth control.Simulation results demonstrate that anti-noise capability and precision of the depth control are improved due to Kalman filter.4.Established experiment environment with a high pressure environment system,and verified the strategies with hardware-in-loop simulation.Experiments demonstrates that dynamic performance of depth control is greatly improved with as a result of adopting control strategy in this thesis. |
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