Abstract: A guaranteed cost control for the stochastic distribution systems, memory state feedback control algorithm is presented via this expansions to represent the dynamics weighting systems between the systems input and the weights related to the output Probability Density Function（PDF）, and  the control algorithms are optimized by the convex optimization techniques. Simulations are given to show that the systems output probability density function follows the target probability density function, and ensures prescribed performance.

Key words: non-Gaussian stochastic distribution systems, probability density function, state memory feedback control, guaranteed cost control

摘要： 对于连续随机分布控制中的保守性问题，采用平方根B样条逼近建立系统静态模型（输出概率密度函数模型），利用系统输入和输出概率密度函数权值之间的动态关系建立动态模型，提出状态记忆反馈保性能控制算法，并利用凸优化技术优化算法，通过计算机仿真验证，该算法能够实现系统输出概率密度函数追踪目标概率密度函数，并满足规定的性能指标。

关键词: 非高斯随机分布系统, 概率密度函数, 状态记忆反馈, 保性能控制