Depth Control Method of Profiling Float Based on an Improved Double PD Controller

Qiu

Yang

et al. 2022

Sci Rep

To understand the physical ocean laws of ocean circulation in the deep ocean below 2000 m, a profiling float named FUXING is presented to meet the deep-ocean observation requirements at a depth of 4000 m. First, to meet the low energy consumption and buoyancy regulation stability of the profiling float, the low–power buoyancy adjustment process of FUXING is effectively solved by introducing the external seawater pressure as the driving force. Then, to reduce the energy consumption of the single profile for the profiling float, the optimization of the oil draining adjustment mode in the floating process is studied. Simultaneously, a buoyancy-driven system characterization test was performed to examine the buoyancy adjustment of FUXING. When the frequency of oil draining is 15 times, the total energy consumption of FUXING is the lowest. Finally, FUXING was deployed in the northeast off the Luzon Island to validate the feasibility and reliability. The at-sea experiments indicated that the optimized oil draining adjustment mode can reduce the total energy consumption in the floating process by more than 20%. The profile data showed that the outer sea water gradually mixes with the South China Sea water after passing through the northeast off the Luzon Island.

Section: Design Of the Fuxing Buoyancy-driven Systemmentioning

confidence: 99%

“…The relationship between starting power consumption of DC motor ( W s ) and its load torque ( T 2 ) is expressed as 24 . …”

Section: Design Of the Fuxing Buoyancy-driven Systemmentioning

confidence: 99%

Design and experimental research of a novel deep-sea self-sustaining profiling float for observing the northeast off the Luzon Island

Qiu

Yang

et al. 2022

Sci Rep

“…In terms of the principle of traditional PD method, an improved double PD depth-control strategy of the DSIB was proposed [ 5 ]. The DSIB suspended at a depth of 1000 m with a mean depth-tracking error within 6 m. Because the DSIB system model is established by means of the speed and flow expectation functions of the arctangent model, it was difficult to optimize the depth-control method.…”

Section: Introductionmentioning

confidence: 99%

“…Comparing the advantages and disadvantages of various depth-control strategies [ 5 , 6 , 7 , 8 , 9 , 10 ], it can be seen that the inversion method has been widely used in underwater vehicles motion control technology and achieved good results. At the same time, the time-constraint stability strategy has strong robustness and better anti-disturbance performance, and the state of the system can converge to the equilibrium state in a finite time.…”

Section: Introductionmentioning

confidence: 99%

Depth-Keeping Control for a Deep-Sea Self-Holding Intelligent Buoy System Based on Inversion Time Constraint Stability Strategy Optimization

Qiu

et al. 2022

Sensors

Based on the nonlinear disturbance observer (NDO), the inversion time-constraint stability strategy (ITCS) is designed to make the deep-sea self-holding intelligent buoy (DSIB) system hovered at an appointed depth within a specified time limit. However, it is very challenging to determine the optimal parameters of an ITCS depth controller. Firstly, a genetic algorithm based on quantum theory (QGA) is proposed to obtain the optimal parameter combination by using the individual expression form of quantum bit and the adjustment strategy of quantum rotary gate. To improve the speed and accuracy of global search in the QGA optimization process, taking the number of odd and even evolutions as the best combination point of the genetic and chaos particle swarm algorithm (GACPSO), an ITCS depth controller based on GACPSO strategy is proposed. Besides, the simulations and hardware-in-the-loop system experiments are conducted to examine the effectiveness and feasibility of the proposed QGA–ITCS and GACPSO–ITCS depth controller. The results show that the proposed GACPSO–ITCS depth controller provides higher stability with smaller steady-state error and less settling time in the depth-control process. The research of the proposed method can provide a stable operation condition for the marine sensors carried by the DSIB.

“…In recent years, there have been many attempts in the field of ocean engineering. Mu et al [33,34] proposed an improved double PD control method for typical nonlinear and large-time-delay systems (profiling float). The low-power control strategy for the floating process and the real-time prediction of position were proposed, which resulted in favorable robustness and stability for nonlinear time-varying floating systems.…”

Section: Introductionmentioning

confidence: 99%

Double-Loop Sliding Mode Controller with An Ocean Current Observer for the Trajectory Tracking of ROV

Sun³

et al. 2021

JMSE

Self Cite

To solve the trajectory tracking problem of insufficient response and the large tracking error of remotely operated vehicles (ROVs) under the interference of large ocean currents, this paper proposes a double-loop sliding mode controller with an ocean current observer. The designed controller consisted of an outer-loop controller (the position controller) and an inner-loop controller (the velocity controller): the outer controller was designed by the position error, and a reference velocity was created for the inner loop to achieve accurate positioning and attitude tracking. The reference control input was treated as a new target to design the inner-loop controller, enabling the ROV to achieve accurate reference velocity tracking. Based on the theoretical idea of active disturbance rejection control, a kinematic equation-based ocean current observer was designed to estimate and compensate for large unknown currents to ensure accurate trajectory tracking performance under large currents. The simulation results proved that the double-loop sliding-mode control scheme with an ocean current observer always showed good tracking performance, demonstrating the excellent control performance and high robustness of the scheme. Compared with the high-complexity control schemes such as neural network-based PID control or fuzzy sliding mode control, it effectively improves the robustness to ocean current disturbances without increasing the computational effort excessively, and is more practical in ROV systems with limited computational power.