An Information Geometric Algorithm for Multi-input and Multi-output Stochastic Distribution Control Systems With Output Feedback Vector

摘要：

　　An information geometric algorithm is proposed to control the shape of the conditional output probability density function for stochastic distribution control systems.The considered system is of multi-input and multi-output with stochastic noises and a output feedback vector.Based on the assumption that the probability density function of the stochastic noise is known,we obtain the conditional output probability density function using the probability theories,whose shape can be considered to be determined by the control input vector and the output feedback vector.The set of the conditional output probability density function forms a manifold(M),and the control input and the output feedback can be considered as the coordinate system from the viewpoint of information geometry.The Kullback-Leibler divergence acts as the distance between the conditional output probability density function and the target probability density function,and can be considered as an error function.For the output feedback vector is known,our propose is to design the control input vector to make the conditional output probability density function as close as possible to the given one.Thus,an iterative formula for the control input vector is proposed in the sense of information geometry.Finally,an illustrative example is utilized to demonstrate the effectiveness of the algorithm.

关键词： Stochastic Distribution Control Information Geometry Kullback-Leibler Divergence Differentiable Manifold

作者: ZHANG Zhenning ZHAO Xu ZHOU Juntong

作者单位: College of Applied Sciences,Beijing University of Technology,Beijing,100124,P.R.China College of Electronic Information and Control Engineering,Beijing University of Technology,Beijing,1

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 5340-5344

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）