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.
Keywords: chaotic particle swarm optimization (CPSO); deep-sea self-holding intelligent buoy (DSIB); depth control; inversion time-constraint stability (ITCS); quantum genetic algorithm (QGA).