基于差分进化算法的飞行控制律评估

摘要

针对传统文化算法进化后期收敛速度慢和差分进化算法在进化过程中缺乏对知识有效利用的问题，提出一种新的文化差分进化算法。该算法以文化算法为框架，将差分进化算法的变异、交叉和选择作为种群空间的进化操作，并通过信念空间的知识指导种群进化。根据飞行品质规范选取迎角响应限制准则，以飞机模型ADMIRE为研究对象，利用该算法对存在不确定条件下的飞行控制律进行非线性评估，克服传统网格评估方法在工程应用中的不足。仿真结果表明，与改进差分进化算法相比，文化差分进化算法在全飞行包线范围内找出最坏的不确定参数组合，具有更高的可靠性和效率。%Aiming at the slow converge rate in traditional cultural algorithm and lower use efficiency of knowledge about evolutionary information in differential evolution algorithm, a new cultural differential evolution algorithm is proposed. The cultural algorithm is utilized as the framework of the proposed algorithm, in which the evolution in population space consists of mutation, crossover and selection of the differential evolution. In addition, the population space evolution is guided by the belief space knowledge. According to the flying quality specifications, a nonlinear criterion is presented. The proposed algorithm is then applied to evaluate angle of attack limit exceedance criterion, which is current widely used in the aerospace industry. The full authority flight control law of the Aero-Data Model in Research Environment ( ADMIRE) is evaluated with uncertainties by the proposed algorithm, which overcomes the limitations of traditional grid-based ones. The simulation results validate that the reliability, computational complexity and efficiency of the proposed algorithm outperform those of the modified differential evolution algorithm, especially in searching for the worst uncertain parameter combinations for the whole flight envelope.