No abstract

No abstract

No abstract

No abstract

Abstract-State estimator design for a nonlinear discrete-time system is a challenging problem, further complicated when additional physical insight is available in the form of inequality constraints on the state variables and disturbances. One strategy for constrained state estimation is to employ online optimization using a moving horizon approximation. In this article we propose a general theory for constrained moving horizon estimation. Sufficient conditions for asymptotic and bounded stability are established. We apply these results to develop a practical algorithm for constrained linear and nonlinear state estimation. Examples are used to illustrate the benefits of constrained state estimation. Our framework is deterministic.

No abstract

performs better than the already classical balanced truncation method even when its static matrix gain is optimized, procedure which involves greater computational efforts. Our method performs particularly well when approximations of large scale flexible structures are considered and we believe that it is a real alternative to determine reduced order models of this important class of linear time invariant systems. [3] Y. Ebihara and T. Hagiwara, "On H model reduction using LMIs," REFERENCESIEEE Trans. Autom. Control, vol. 49, no. 7, pp. 1187-1191 J. C. Geromel, "Convex analysis and global optimization of joint actuator location and control problems," IEEE Trans. Autom. Control, vol. 34, no. 7, pp. 711-720, Jul. 1989. [5] , "Optimal linear filtering under parameter uncertainty," IEEE Trans. Signal Process., vol. 47, no. 1, pp. 168-175, Jan. 1999. [6] J. C. Geromel, F. R. R. Kawaoka, and R. G. Egas, "Model reduction of discrete time systems through linear matrix inequalities," Int. J. Control, vol. 77, no. 10, pp. 978-984, Jul. 2004. [7] K. Glover, "All optimal Hankel-norm approximations of linear multivariable systems and their L -error bounds," Int. J. Control, vol. 39, no. 6, pp. 1115Control, vol. 39, no. 6, pp. -1193Control, vol. 39, no. 6, pp. , 1984 [8] K. M. Grigoriadis, "Optimal H model reduction via linear matrix inequalities: Continuous and discrete-time cases," Syst. Control Lett., vol. 26, no. 5, pp. 321-333, 1995. [9] W. M. Haddad and D. S. Bernstein, "Combined L =H model-reduction," Int. J. Control, vol. 49, no. 5, pp. 1523Control, vol. 49, no. 5, pp. -1535Control, vol. 49, no. 5, pp. , 1989 [10] L. Meirovitch, H. Baruh, and H. Öz, "A comparison of control techniques for large flexible systems," J. Guid., vol. 6, no. 4, 1983. [11] C. Scherer, "Mixed H =H Abstract-This note provides results on approximating the minimal robust positively invariant (mRPI) set (also known as the 0-reachable set) of an asymptotically stable discrete-time linear time-invariant system. It is assumed that the disturbance is bounded, persistent and acts additively on the state and that the constraints on the disturbance are polyhedral. Results are given that allow for the computation of a robust positively invariant, outer approximation of the mRPI set. Conditions are also given that allow one to a priori specify the accuracy of this approximation.

No abstract