Bounding Approaches to System Identification [Paperback]

In response to the growing interest in bounding error approaches, the editors of this volume offer the first collection of papers to describe advances in techniques and applications of bounding of the parameters, or state variables, of uncertain dynamical systems. Contributors explore the application of the bounding approach as an alternative to the probabilistic analysis of such systems, relating its importance to robust control-system design.In response to the growing interest in bounding error approaches, the editors of this volume offer the first collection of papers to describe advances in techniques and applications of bounding of the parameters, or state variables, of uncertain dynamical systems. Contributors explore the application of the bounding approach as an alternative to the probabilistic analysis of such systems, relating its importance to robust control-system design.Overview of the Volume; J. Norton. Optimal Estimation Theory for Dynamic System with Set Membership Uncertainty: An Overview; M. Milanese, A. Vicino. Solving Linear Problems in the Presence of Bounded Data Perturbations; B.Z. Kacewicz. A Review and a Comparison of Ellipsoidal Bounding Algorithms; G. Favier, L.V.R. Arruda. On the Deadzone in System Identification; K. Forsman, L. Ljung. Recursive Estimation Algorithms for Linear Models with Set Membership Error; G. Belforte, T.T. Tay. Transfer Function Parameter Interval Estimation Using Recursive Least Squares in the Time and Frequency Domains; P.O. Gutman. Volume-optimal Inner and Outer Ellipsoids; L. Pronzato, E. Walter. Linear Interpolation and Estimation Using Interval Analysis; S.M. Markov, E.D. Popova. Adaptive Approximation of Uncertainty Sets for Linear Regression Models; A. Vicino, G. Zappa. Worstcase l1 Identification; M. Milanese. Recursive Robust Minimax Estimation; E. Walter, H. Piet-Lahanier. Robustness to Outliers of Bounded-error Estimators, Consequences on Experiment Design; L. Pronzato, E. Wal“.