Optimal H∞ fusion filters for a class of discrete-time intelligent systems with time delays and missing measurement

Neurocomputing

Volumn 74, Issue 18, 2011, Pages 3741-3752

  Liu, Meiqin ^a   Qi, Donglian ^a   Zhang, Senlin ^a   Qiu, Meikang ^b   Zheng, Shiyou ^c  

^a ZHEJIANG UNIVERSITY   (China)

^b UNIVERSITY OF KENTUCKY   (United States)

^c Radar and Avionics Institute of AVIC   (China)

Author keywords

Discrete time systems; H fusion filtering; Intelligent systems; Missing measurements; Multi sensor fusion

Indexed keywords

CONDITIONAL PROBABILITY DISTRIBUTIONS; DELAY INDEPENDENT; DESIGN PROCEDURE; DISCRETE TIME SYSTEM; DISCRETE-TIME; DISTRIBUTED FUSION FILTER; EIGENVALUE PROBLEM; FILTERING PERFORMANCE; GLOBALLY ASYMPTOTICALLY STABLE; LINEAR DYNAMIC SYSTEM; LUR'E SYSTEMS; LYAPUNOV-KRASOVSKII FUNCTIONAL METHOD; MEAN SQUARE; MISSING MEASUREMENTS; MISSING OBSERVATIONS; MULTI SENSOR; MULTI-SENSOR FUSION; NONLINEAR OPERATOR; OPTIMIZATION PROBLEMS; PERFORMANCE CONSTRAINTS; SIMULATION EXAMPLE; STOCHASTIC ANALYSIS; SWITCHING SEQUENCE; SYSTEMS WITH TIME DELAY; TAKAGI AND SUGENO FUZZY MODEL; UNIFIED DESCRIPTION;

DIGITAL CONTROL SYSTEMS; DISCRETE TIME CONTROL SYSTEMS; EIGENVALUES AND EIGENFUNCTIONS; FUZZY FILTERS; FUZZY NEURAL NETWORKS; LINEAR CONTROL SYSTEMS; LINEAR MATRIX INEQUALITIES; LYAPUNOV FUNCTIONS; OPTIMIZATION; PROBABILITY DISTRIBUTIONS; SENSORS; STOCHASTIC SYSTEMS; SWITCHING SYSTEMS; TIME DELAY;

INTELLIGENT SYSTEMS;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; DIGITAL FILTERING; DISCRETE TIME INTELLIGENT SYSTEM; FILTER DESIGN; FUSION FILTERING; FUSION FILTERING ALGORITHM; FUZZY SYSTEM; LINEAR MATRIX INEQUALITY; LINEAR SYSTEM; LYAPUNOV KRASOVSKII FUNCTIONAL METHOD; MATHEMATICAL ANALYSIS; MISSING MEASURMENT; NONLINEAR SYSTEM; PRIORITY JOURNAL; PROBABILITY; SIMULATION; STATISTICAL ANALYSIS; TIME DELAY;

EID: 80053318284     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2011.06.016     Document Type: Article

References (27)

1. Tseng C.-S. Robust fuzzy filter design for a class of nonlinear stochastic systems. IEEE Trans. Fuzzy Syst. 2007, 15(2):261-274.
2. ∞ filtering and solution bound for non-linear systems. Int. J. Control 2001, 74:565-570.
3. ∞ estimation for nonlinear systems. IEEE Signal Process. Lett. 1998, 5(8):199-202.
4. Xu S. Robust filtering for a class of discrete-time uncertain nonlinear systems with state delay. IEEE Trans. Circuits Syst. I 2002, 49(12):1853-1859.
5. ∞ filtering for uncertain discrete-time state-delayed systems. IEEE Trans. Signal Process. 2004, 52(6):1631-1640.
6. ∞ filter for 2-D system. IEEE Signal Process. Lett. 2008, 18:217-220.
7. ∞ minimum error state estimation of linear stationary processes. IEEE Trans. Autom. Control 1990, 35(5):554-558.
8. ∞ filter design for systems with time-varying interval delay. IEEE Trans. Circuits Syst. II: Express Briefs 2006, 53(11):1235-1239.
9. ∞ filtering for uncertain discrete-time systems with time-varying delay based on a finite sum inequality. IEEE Trans. Circuits Syst. II: Express Briefs 2006, 53(12):1466-1470.
10. ∞, and Nonlinear Approaches 2006, John Wiley & Sons, Inc., Hoboken, New Jersey, USA.
11. ∞ filtering for stochastic time-delay systems with missing measurements. IEEE Trans. Signal Process. 2006, 54(7):2579-2587.
12. ∞ control with missing measurements and time delays. IEEE Trans. Autom. Control 2007, 52(9):1666-1672.
13. 2 approximation of multiple input/output delay systems. J. Process Control 2004, 14(6):627-634.
14. H. Sun, R. Liu, C. Wen, Design and performance analysis of robust fusion filters for a class of continuous uncertain dynamic systems, in: Proceedings of the 26th Chinese Control Conference, Zhangjiajie, Hunan, China, pp.301-305, July 26-31, 2007.
15. ∞ fusion filter design in multi-sensor fusion system with state time-delays. IEEE Int. Conf. Autom. Logistics 2007, 2784-2789.
16. Wang J., Xue A. Robust guaranteed cost data fusion approach for uncertain systems. Fifth World Congress on Intelligent Control and Automation (WCICA) 2004, 4:3064-3066.
17. ∞ filtering for discrete stochastic time-delay systems with nonlinear disturbances. Nonlinear Dyn. Syst. Theory 2004, 4(3):285-301.
18. ∞ filtering for discrete nonlinear stochastic systems with time-varying delay. J. Math. Anal. Appl. 2008, 341(1):318-336.
19. Liu M. Delayed standard neural network models for control systems. IEEE Trans. Neural Networks 2007, 18(5):1376-1391.
20. Liu M.Q. Discrete-time delayed standard neural network model and its application. Sci. China: Ser. F Inf. Sci. 2006, 49(2):137-154.
21. Liu M.Q. Unified stabilizing controller synthesis approach for discrete-time intelligent systems with time delays by dynamic output feedback. Sci. China: Ser. F Inf. Sci. 2007, 50(4):636-656.
22. Nahi N.E. Optimal recursive estimation with uncertain observation. IEEE Trans. Inf. Theory 1969, IT-15(4):457-462.
23. Sinopoli B., Schenato L., Franceschetti M., Poolla K., Jordan M.I., Sastry S.S. Kalman filtering with intermittent observations. IEEE Trans. Autom. Control 2004, 49(9):1453-1464.
24. Boyd S.P., Ghaoui L.E., Feron E., Balakrishnan V. Linear Matrix Inequalities in System and Control Theory 1994, SIAM, Philadelphia, PA.
25. Gahinet P., Nemirovski A., Laub A.J., Chilali M. LMI Control Toolbox for use with Matlab 1995, The MATH Works, Inc., Natick, MA.
26. Zhang Y., Xu S., Zeng Z. Novel robust stability criteria of discrete-time stochastic recurrent neural networks with time delay. Neurocomputing 2009, 72(13-15):3343-3351.
27. ∞ control for uncertain discrete-time-delay fuzzy systems via output feedback controllers. IEEE Trans. Fuzzy Syst. 2005, 13(1):82-93.