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分析了飞机定常下滑过程中平衡状态的基本特征以及常规求解平衡状态方法的缺点,提出了一种基于自适应变异算子鱼群算法的新型配平方法。该算法在标准人工鱼群算法的基础上,对鱼群行为加以改进,并在搜索过程中加入鱼群个体变异机制,弥补了原始算法的不足,提高了算法的收敛速度、精度和稳定度,并使算法具有较好的克服早熟能力。引入了代价函数,用该算法对其寻优,从而将配平问题转换成求解代价函数的最大值问题。仿真结果表明,该方法可以准确地找到平衡点位置,且对初值要求不高,具有一定的通用性。
Based on the analysis of the basic characteristics of the equilibrium state during the steady decline of the aircraft and the shortcomings of the conventional method for solving the equilibrium state, a new type of leveling method based on the adaptive mutation operator Fish Swarm Algorithm is proposed. Based on the standard artificial fish school algorithm, this algorithm improves the behavior of fish schools and adds individual variation mechanism of fish stocks to the search process to make up for the deficiencies of the original algorithm and improve the convergence speed, accuracy and stability of the algorithm. And make the algorithm better to overcome precocious ability. The cost function is introduced, which is optimized by the algorithm, so as to convert the trim problem into the maximum problem of solving the cost function. The simulation results show that this method can accurately find the location of the equilibrium point, and the initial value of the less demanding, has a certain versatility.