用填充函数改进的智能控制系统全局优化算法

为了提高全局优化算法的速度，提出了智能控制系统全局优化算法。该算法应用了闭环控制系统的反馈的思想,使得在寻优迭代过程中被优化函数的值不断接近设定值，直至达到其全局最优值。该算法的关键在于控制策略的设计和策略中的参数值的设定。为了降低参数初值设定的难度同时提高算法的寻优精度,利用填充函数法对智能控制系统全局优化算法进行改进。经12个标准的测试函数的验证，改进后的算法的速度较填充函数法快，算法的精度比智能控制系统全局优化算法高。

Improved global optimization algorithm of intelligence control system with filled function

In order to improve the speed of global optimization algorithm,a global optimization algorithm of intelligence control system was presented.The feedback idea of closed loop control system was applied in this algorithm that made the value of the object function gradually close to the input in the iterative process until reaching the global optimization.The key of the algorithm lies in the design of control strategy and the initial setting of parameters.In order to reduce the difficulty of initial setting of parameters and ensure the precision of the algorithm,the filled function was used to improve the global optimization algorithm of intelligence control system.Verified by twelve standard test functions,the improved algorithm is faster than filled function method,and is more accurate than the global optimization algorithm of intelligence control system.