基于遗传算法信息组合的自适应模糊控制

利用模糊理论分别建立了与控制对象和控制知识信息相对应的控制系统，应用遗传算法获取2个系统在不同时间段的最佳组合因子，消除了对组合因子赋值的主观性和不准确性．基于李雅普诺夫函数的方法推导了模糊控制系统中参数的自适应控制律，并且证明了系统的稳定性和收敛性．将遗传算法信息组合的自适应模糊控制方法应用在达芬混沌系统的控制中，仿真结果对比表明，虽然组合型自适应控制方法可以有效地控制达芬强迫震荡系统，但文中提出的方法能使各控制状态有界，并且能够迅速准确地跟踪目标．

Adaptive Fuzzy Control Based on Genetic Algorithm Organizing Information

Fuzzy theory is employed to establish the control systems based on the knowledge of object and controlling. Genetic algorithm is utilized to obtain the data o optimal combination mode of these two systems within different time interval to eliminate the subjectivity and uncertainty. Then the adaptive laws which adjust the free parameters of the fuzzy systems are developed with Lyapunov function, and the stability and convergence of the whole control system is proved. The proposed method is validated with the Dulling forced-oscillation system, and the simulation results illustrate that the proposed method enables every state variable to trace the object more quickly and accurately than the composed adaptive method.