针对船舶动力定位系统中一类非线性有约束的推力分配问题，提出了一种以粒子群算法为基础，并引入混沌理论和遗传算法中交叉及变异策略的混合算法。建立以推进系统能耗最小为目标，包括推进器功率消耗、磨损、推力误差等；以推进器推力、方位角的工作范围和变化速率等为约束条件的多变量非线性有约束优化问题。通过仿真表明，该算法能够解决该优化问题，而且能够兼顾船舶推进系统的能耗和操纵性能，有效地提高了船舶动力定位系统的相关性能。
To solve the problem of a class of nonlinear constrained thrust distribution in ship dynamic positioning system, a hybrid algorithm based on particle swarm algorithm and crossover and mutation strategy in chaotic theory and genetic algorithm is proposed. To establish the multivariate nonlinear constrained optimization problem, by the minimum propulsion system energy consumption as the goal, including propulsion power consumption, wear and tear, thrust error, avoid singular structure, etc; by the propeller thrust, the azimuth Angle scope of work and change rate as constraint. The simulation results show that the proposed algorithm can solve the optimization problem, and can improve the energy consumption and maneuverability of the ship propulsion system, improve the performance of the ship dynamic positioning system effectively.
2018,40(12): 99-103 收稿日期：2017-03-31
DOI：10.3404/j.issn.1672-7649.2018.12.020
分类号：U664.82
作者简介：李新想(1993-),男,硕士研究生,研究方向为复杂系统控制与优化
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