为了有效地应用遗传算法解决 鲁棒控制系统设计问题，将遗传算法与局部优化方法相结合，提出了基于降维扫描方法的自适应多目标遗传算法（DRSA-MOGA）。通过引入适应度函数标准化方法、基于最优Pareto解集搜索的降维扫描方法和适应度函数自适应调整方法，提高了算法的全局优化性能和局部搜索能力。仿真结果表明，DRSA-MOGA算法在不损失解的均匀度的情况下可以达到很高的逼近度-For effective application of genetic algorithms to solve robust control system design problems, genetic algorithms and local optimization method, based on reduced-order adaptive scanning method multi-objective genetic algorithm (DRSA-MOGA). Fitness function through the introduction of standardized methods, based on the Pareto optimal solution set of search methods and dimensionality reduction scan fitness function adaptive adjustment method, the algorithm improve the performance of global optimization and local search capabilities. The simulation results show that, DRSA-MOGA algorithm solution without loss of uniformity can be achieved under a high degree of approximation