Robust filtering for a class of nonlinear stochastic systems with probability constraints
- Authors: Ma L.1, Wang Z.2,3, Lam H.4, Alsaadi F.E.3, Liu X.2
- 
							Affiliations: 
							- School of Automation
- Brunel University London
- King Abdulaziz University
- King’s College London, Strand Campus
 
- Issue: Vol 77, No 1 (2016)
- Pages: 37-54
- Section: Topical Issue
- URL: https://journals.rcsi.science/0005-1179/article/view/150190
- DOI: https://doi.org/10.1134/S0005117916010033
- ID: 150190
Cite item
Abstract
This paper is concerned with the probability-constrained filtering problem for a class of time-varying nonlinear stochastic systems with estimation error variance constraint. The stochastic nonlinearity considered is quite general that is capable of describing several well-studied stochastic nonlinear systems. The second-order statistics of the noise sequence are unknown but belong to certain known convex set. The purpose of this paper is to design a filter guaranteeing a minimized upper-bound on the estimation error variance. The existence condition for the desired filter is established, in terms of the feasibility of a set of difference Riccati-like equations, which can be solved forward in time. Then, under the probability constraints, a minimax estimation problem is proposed for determining the suboptimal filter structure that minimizes the worst-case performance on the estimation error variance with respect to the uncertain second-order statistics. Finally, a numerical example is presented to show the effectiveness and applicability of the proposed method.
About the authors
Lifeng Ma
School of Automation
							Author for correspondence.
							Email: malifeng@njust.edu.cn
				                					                																			                												                	China, 							Nanjing						
Zidong Wang
Brunel University London; King Abdulaziz University
														Email: malifeng@njust.edu.cn
				                					                																			                												                	United Kingdom, 							Uxbridge, Middlesex; Jeddah						
Hak-Keung Lam
King’s College London, Strand Campus
														Email: malifeng@njust.edu.cn
				                					                																			                												                	United Kingdom, 							London						
Fuad E. Alsaadi
King Abdulaziz University
														Email: malifeng@njust.edu.cn
				                					                																			                												                	Saudi Arabia, 							Jeddah						
Xiaohui Liu
Brunel University London
														Email: malifeng@njust.edu.cn
				                					                																			                												                	United Kingdom, 							Uxbridge, Middlesex						
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