中文摘要：

针对人工鱼群算法存在群体协调性差、盲目搜索、收敛缓慢和求解精度低等问题,提出一种自适应人工鱼群算法,并将其应用于无人艇控制系统设计的参数优化中。改进的基本思想为采用蹲守行为以改善群体协调性,并引入人工鱼的消亡与重生机制来增强鱼群的生存和进化能力,从而使群体行为更加突出;采取可变求解域和自适应调整鱼群参数等策略以提高求解精度与收敛速度。仿真对比试验表明：自适应人工鱼群算法具有更强的寻优能力和自适应性,并显著提高全局收敛速度和求解精度。控制系统设计实例也验证该算法的有效性。

英文摘要：

Aiming at the problems of poor compatibility of colony, blindness of search, slow rate of convergence, and low accuracy of optimum solution in the artificial fish swarm algorithm （AFSA）, an adaptive artificial fish swarm algorithm （AAFSA） was proposed to solve the parameter optimization problem of control system design for unmanned surface vessel （USV）. Watch behavior was adopted in AAFSA to improve the compatibility of fish swarm, and death and renascence mechanism of artificial fish was introduced to enhance the capability of artificial fish survival and evolution, which can markedly improve the colony behavior of artificial fish swarm. Variable solution domain and adaptive adjustment parameter strategies were adopted to increase the convergence rate and precision. The simulation results show that AAFSA has better optimization ability and adaptability, and it improves the global convergence rate and precision. The effectiveness of the AAFSA is validated by design example of control system.