基于多层蚁群算法的变论域模糊控制

针对模糊控制器控制精度不高、自适应能力有限等问题,提出一种变论域自适应模糊控制方式.首先在对离散蚁群算法改进的基础上,提出用于连续域寻优的多层蚁群算法.其通过将解空间分成有限网格,并且算法在迭代过程中采用三个阶段的搜索策略,每个阶段采用异构搜索机制.然后根据系统性能利用改进算法动态调整伸缩因子,从而构成基于多层蚁群算法的变论域自适应模糊控制器.最后将此控制器用于中厚板液压位置伺服系统中.仿真结果表明,采用自适应模糊控制器的伺服系统收敛速度明显加快,此控制策略在适应能力与鲁棒性好于其它控制方式.

Variable Universe Fuzzy Control Based on Multilayer Ant Colony Algorithm

Aiming at the low accuracy and poor adaptation of the fuzzy control algorithm, an adaptive fuzzy controller with variable universe is proposed. Firstly, based on the theory of ant colony optimization (ACO), a muhilayer ant colony algorithm for continuous domains is designed. Through decomposing solution space into finite grids, the proposed algorithm is realized by three-stage search strategy with the progress of iterations, and heterogeneous mechanism is utilized at each stage. Secondly, the intelligent algorithm is used to optimize the contraction and expansion factors. Thus, the universe of fuzzy controller is adjusted on line according to performance indicator. Meanwhile, the adaptive fuzzy controller with variable universe is adopted to hydraulic servo system of medium plate. Finally, the simulation results show that the convergence speed of the system with adaptive fuzzy controller is higher than that of others. And the proposed control strategy has fine property in effectiveness and robustness.