Stochastic distribution control aims at developing control algorithms for non-Gaussian stochastic systems so that the output probability density functions of the system can be made to follow a target distribution shape.
It is a new research area in stochastic control originated at CSC and has potential applications in most distribution control systems such as the particle size distribution control in chemical processing, 2D and 3D web forming systems in, the steel, film and paper industries, combustion flames and distribution control in power generation. In addition, minimum tracking error entropy control has been developed that can lead to a better closed loop control performance (funded by EPSRC/Leverhulme Trust).
- H. Wang, "Robust control of the output probability density functions for multivariable stochastic systems with guaranteed stability", IEEE Transactions on Automatic Control, Vol. 41, pp.2103-2107, 1999.
- H. Wang, Bounded Dynamic Stochastic Distributions Modelling and Control, Springer-Verlag Ltd (London), March, 2000. (ISBN 1-85233-187-9)
- H. Wang, J. H. Zhang, “Bounded stochastic distribution control for pseudo ARMAX systems”, IEEE Transactions on Automatic Control, Vol.46, pp.486-490, 2001.
- H. Wang, "Minimum entropy control for non-Gaussian dynamic stochastic systems", IEEE Transactions on Automatic Control, Vol. 47, pp.398 – 403, 2002.
- H. Yue and H. Wang, "Minimum entropy control of closed loop tracking errors for dynamic stochastic systems", IEEE Transactions on Automatic Control, Vol. 48, pp. 118-122, 2003.