Advanced Search

Query:

Fill in the form and click »Search«...

Format:

Display: entries per page entries

Zbl 1149.93350
Guo, L.; Wang, H.; Wang, A.P.
Optimal probability density function control for NARMAX stochastic systems. (English)
[J] Automatica 44, No. 7, 1904-1911 (2008). ISSN 0005-1098

Summary: This paper presents a new control strategy for a class of non-Gaussian stochastic systems so that the output Probability Density Function (PDF) of the system can be made to follow a desired PDF. The system considered is represented by an Nonlinear AutoRegressive and Moving Average with eXogenous (NARMAX) inputs with input channel time-delay and non-Gaussian noise. A multi-step-ahead nonlinear cumulative cost function is used to improve tracking performance. For this purpose, a relationship between the PDFs of all the inputs and the PDFs of multiple-step-ahead output is formulated by constructing an auxiliary multivariate mapping. By minimizing this performance function, a new explicit predictive controller design algorithm is established with less conservatism than some previous results. Furthermore, an improved approach is developed to guarantee the local stability of the closed-loop system by tuning the weighting parameters recursively. Simulations are given to demonstrate the effectiveness of the proposed control algorithm and desired results have been obtained.

MSC 2000:: *93E20 Optimal stochastic control (systems)
93C10 Nonlinear control systems
93E15 Stochastic stability

Keywords: probability density functions; non-Gaussian systems; stochastic control; optimal control; nonlinear systems; time-delay systems; stability analysis

Comment on this Item PDF MathML XML ASCII DVI PS BibTeX Online Ordering Article Journal

	Scientific prize winners of the ICM 2010
	Overhang
	Lie groups, physics and geometry. An introduction for physicists, engineers and chemists.

Advanced Search

Zentralblatt MATH Berlin [Germany]