Shaolin Lü and Rong Zhang
[1] R.E. Kalman, A new approach to linear filtering and predictionproblems, ASME Journal of Basic Engineering, 82(1), 1960,34–45. [2] M. Boutayeb, M. Darouach, & H. Rafaralahy, Generalizedstate-space observers for chaotic synchronization and securecommunications, IEEE Transactions on Circuits Systems: I,49(3), 2002, 345–349. [3] Z. Gao, D.C. Ho, & X. Wang, A parameterization of reduced-order function observers for singular systems, Control andIntelligent Systems, 27(2), 1999, 50–58. [4] Z. Gao & H. Wang, Descriptor observer approaches for mul-tivariable systems with measurement noises and applicationin fault detection and diagnosis, System and Control Letters,55(4), 2006, 304–313. [5] Z. Gao, H. Wang, & T. Chai, A robust fault detection filteringfor stochastic distribution systems via descriptor estimator andparametric gain design, IET Proceedings on Control TheoryApplications, 1(5), 2007, 1286–1293. [6] S.F. Schmidt, The Kalman filter: Its recognition and devel-opment for aerospace applications, Journal of Guidance andControl, 4(1), 1981, 4–7. [7] D. Simon, Optimal state estimation: Kalman, H∞, andnonlinear approaches (Hoboken, NJ: John Wiley & Sons, Inc.,2006). [8] M.S. Grewal & A.P. Andrews, Kalman filtering: Theory andpractice using MATLAB (Hoboken, NJ: John Wiley & Sons,Inc., 2001). [9] P.G. Kaminski, A.E. Bryson, Jr, & S.F. Schimidt, Discretesquare root filtering: A survey of current techniques, IEEETransactions on Automatic Control, 16(6), 1971, 727–736. [10] G.J. Bierman, A comparison of discrete linear filtering al-gorithms, IEEE Transactions on Aerospace and ElectronicsSystems, 9(1), 1973, 28–37. [11] G.J. Bierman, Factorization methods for discrete sequentialestimation (New York: Academic Press, 1977). [12] N.A. Carlson, Fast triangular formulation of the square rootfilter, AIAA Journal, 11(9), 1973, 1259–1265. [13] A. Andrews, A square root formulation of the Kalman covari-ance equations, AIAA Journal, 6(9), 1968, 1165–1166. [14] S.J. Julier, J.K. Uhlmann, & H.F. Durrant-Whyte, A newapproach for filtering nonlinear systems, Proc. of the AmericanControl Conference, 1995, 1628–1632. [15] S.J. Julier & J.K. Uhlmann, Unscented filtering and nonlinearestimation, Proceedings of the IEEE, 92(3), 2004, 401–422. [16] R. van der Merwe & E.A. Wan, The square-root unscentedKalman filter for state and parameter-estimation, IEEE Conf.on Acoustics, Speech, and Signal Processing, 2001, 3461–3464. [17] J.L. Crassidis & F.L. Markley, Unscented filtering for space-craft attitude estimation, Journal of Guidance, Control andDynamics, 26(4), 2003, 536–542. [18] S. S¨akk¨a, On unscented Kalman filtering for state estimationof continuous-time nonlinear systems, IEEE Transactions onAutomatic Control, 52(9), 2007, 1631–1641. [19] W. Press, S. Teukolsky, W. Vetterling, & B. Flannery, Numeri-cal recipes in C (Cambridge, New York: Cambridge UniversityPress, 1992). [20] G. Golub & C. Van Loan, Matrix computations (Baltimore:John Hopkins University Press, 1996). [21] P. Lancaster & M. Tismenetsky, The theory of matrices (NewYork: Academic Press, 1985). [22] P.E. Gill, G.H. Golub, W. Murray, & M.A. Saunders, Methodsfor modifying matrix factorizations, Mathematical Computa-tion, 28(126), 1974, 505–535. [23] S. L¨u, L. Cai, L. Ding, & J. Chen, Two efficient implementationforms of unscented Kalman filter, IEEE Conf. on Control andAutomation, Guangzhou, China, 2007, 761–764. [24] S.J. Julier & J.K. Uhlmann, Corrections to unscented filteringand nonlinear estimation, Proceedings of the IEEE, 92(12),2004, 1958.
Important Links:
Go Back