Predictive control method for ballast leveling systems with multiple switchgear

Zhizheng Gao; Siyuan Wang; Zhongli Yao

doi:10.1117/12.2679396

18 July 2023 Predictive control method for ballast leveling systems with multiple switchgear

Zhizheng Gao, Siyuan Wang, Zhongli Yao

Proceedings Volume 12722, Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023); 127222L (2023) https://doi.org/10.1117/12.2679396
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023), 2023, Hangzhou, China

Abstract

The tilt of the leveling ship in the leveling process has to meet the high precision process requirements while at the same time minimizing the actuator action frequency in the control process and extending the actuator life, which is very important for leveling processes with time delays and complex external disturbances. A group of advanced control strategies must be designed to match them. Firstly, a ballast leveling mechanism model is established based on the hydrostatic characteristics of the ship, followed by the design of a multi-switch device predictive control algorithm. By making the rolling time domain larger than the maximum time delay and ensuring that the switchgear combination is constant in the time domain, LESO is introduced for online prediction of unpredictable disturbances and rolling optimized predictive control of the equipment combination, the influence of time delay and external disturbances on the control system is weakened, and the switching frequency of switchgear is reduced. In the final simulation, the tilt tracking RMSE was reduced by 22.2% compared to conventional switching control, and the number of actuator switches was reduced by 6%.

Citation Download Citation

Zhizheng Gao, Siyuan Wang, and Zhongli Yao "Predictive control method for ballast leveling systems with multiple switchgear", Proc. SPIE 12722, Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023), 127222L (18 July 2023); https://doi.org/10.1117/12.2679396

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