Title: Shape control of conditional output probability density functions for linear stochastic systems with random parameters
Authors: Aiping Wang, Yongji Wang, Hong Wang
Addresses: Institute of Computer Sciences, Anhui University, Hefei, Anhui, PR China. ' Department of Control Science and Engineering, Huazhong University of Science and Technology, 430074 Wuhan, PR China. ' Northeastern University, Shenyang, PR China; and The University of Manchester, Manchester, UK
Abstract: This paper presents a controller design for shaping conditional output probability density functions (pdf) for non-Gaussian dynamic stochastic systems whose coefficients are random and represented by their known pdfs. The moment-generating function is applied to all the pdfs, leading to a simple mathematical relationship amongst all the transferred conditional pdfs of the system output and random parameters. A new performance function is introduced and its minimisation is performed so as to design an optimal control input that makes the shape of the conditional output pdf follow a target distribution. An example is included to illustrate the use of the algorithm.
Keywords: dynamic stochastic systems; probability density functions; moment-generating function; gradient-based optimisation; shape control; conditional output; linear stochastic systems; random parameters; controller design; optimal control.
International Journal of Systems, Control and Communications, 2011 Vol.3 No.1, pp.82 - 94
Published online: 31 Mar 2015 *Full-text access for editors Access for subscribers Purchase this article Comment on this article