【摘要】 根据(N+ M)容错控制系统模型高度非线性和复杂性的特点,尝试用一种改进的遗传算法来实现对此类复杂模型的优化求解。模拟退火和分层遗传算法是2种较好的改进遗传算法性能的方法,通过对其进行研究,将这两种思想有机地结合起来,提出了一种基于模拟退火机制的分层遗传算法。该算法以分层遗传算法流程作为主体流程,把模拟退火机制融入其中,用以调整优化群体。并将他应用于(N+ M)容错系统的数学模型的优化。仿真结果表明,该算法与传统遗传算法相比,不仅能增强算法的全局收敛性,还能加快遗传进化速度,得到满意的全局最优解。更多还原

【Abstract】 Because of high nonlinearity and complexity of the model for (N+M) fault-tolerant control system,an improved genetic algorithms is designed to optimize and solve this kind of complicated models in the thesis.Simulated annealing algorithm and hierarchic genetic algorithm are two helpful methods which can improve the performance of genetic algorithm.These two ideas are well combined in this paper after researched,and a new algorithm is derived,that is the hierarchic genetic algorithm based on simulated annealing method.The hierarchic genetic algorithm is served as main flow of the new algorithms which involve the mechanism of simulated annealing to adjust the optimization population.It is also applied to the optimization of (N+M) fault-tolerant system.The simulated results show that it improves the convergent speed and accelerates evolutionary velocity,and obtains the better globally optimal solutions.更多还原