Energy optimization of fin stabilizer system based on multi-objective cloud genetic algorithm

Energy optimization is the key issue in the fin stabilizer system. The roll angle variance, fin angle variance and energy consumption of fin stabilizer system are analyzed to establish the performance indicators of the fin stabilizer system. In order to solve the problem of lacking of flexibility of convergence and low optimization efficiency of MOGA, using randomness and stable tendency of cloud model, MOCGA is brought forward to optimize the performance indicators of the fin stabilizer system in this paper. In addition, fitness function is improved. The results show that MOCGA can improve the roll reduction efficiency, at the same time it can reduce the energy consumption of the roll reduction device. It has good control effect and provides a theoretical basis for the roll reduction device.