Xin, G.; Zhou, M.; Yang, B., and Ding, X., 2020. Energy optimization control algorithm of underwater vehicle based on model predictive control. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 830–834. Coconut Creek (Florida), ISSN 0749-0208.

In order to improve the accuracy of energy optimization control of underwater vehicle and improve the running stability of underwater vehicle, an energy optimization control method of underwater vehicle based on model predictive control is proposed. The underwater dynamics and kinematics model of underwater vehicle is constructed, and the fuzzy feedback error tracking fusion control law of underwater vehicle is constructed with phase offset and inertia torque as constraint parameters. Fuzzy parameter fusion and adaptive parameter adjustment methods are used to optimize the energy control and model prediction of underwater vehicle. The state adaptive correction and energy optimization control design of underwater motion of robot is realized by model parameter prediction and adaptive weighted information processing. The simulation results show that the energy optimization control design of underwater vehicle using this method has good adaptability, eliminates the angle and azimuth error of energy optimization control, reduces the energy cost of the robot, and improves the stability control accuracy of the energy output of the robot.