Identification of Hybrid Systems: A Tutorial
暂无分享,去创建一个
René Vidal | Giancarlo Ferrari-Trecate | Simone Paoletti | Aleksandar Lj. Juloski | R. Vidal | S. Paoletti | A. Juloski | G. Ferrari-Trecate
[1] Eduardo Sontag. Nonlinear regulation: The piecewise linear approach , 1981 .
[2] Leon O. Chua,et al. Dynamics of a piecewise-linear resonant circuit , 1982 .
[3] Hung Man Tong,et al. Threshold models in non-linear time series analysis. Lecture notes in statistics, No.21 , 1983 .
[4] Leon O. Chua,et al. Canonical piecewise-linear analysis , 1983 .
[5] H. Tong,et al. ON ESTIMATING THRESHOLDS IN AUTOREGRESSIVE MODELS , 1986 .
[6] Lennart Ljung,et al. System Identification: Theory for the User , 1987 .
[7] S. Billings,et al. Piecewise linear identification of non-linear systems , 1987 .
[8] Jan-Erik Strömberg,et al. Trees as Black-Box Model Structures for Dynamical Systems , 1990 .
[9] Roy Batruni,et al. A multilayer neural network with piecewise-linear structure and back-propagation learning , 1991, IEEE Trans. Neural Networks.
[10] Antonio Vicino,et al. Optimal estimation theory for dynamic systems with set membership uncertainty: An overview , 1991, Autom..
[11] J.-N. Lin,et al. Canonical piecewise-linear approximations , 1992 .
[12] O. Mangasarian,et al. Robust linear programming discrimination of two linearly inseparable sets , 1992 .
[13] Lennart Ljung,et al. Construction of Composite Models from Observed Data , 1992 .
[14] Leo Breiman,et al. Hinging hyperplanes for regression, classification, and function approximation , 1993, IEEE Trans. Inf. Theory.
[15] Saul B. Gelfand,et al. A tree-structured piecewise linear adaptive filter , 1993, IEEE Trans. Inf. Theory.
[16] T. Johansen,et al. Identification of non-linear system structure and parameters using regime decomposition , 1994, Autom..
[17] Chong-Ho Choi,et al. Constructive neural networks with piecewise interpolation capabilities for function approximations , 1994, IEEE Trans. Neural Networks.
[18] O. Mangasarian,et al. Multicategory discrimination via linear programming , 1994 .
[19] Eduardo D. Sontag,et al. Interconnected Automata and Linear Systems: A Theoretical Framework in Discrete-Time , 1996, Hybrid Systems.
[20] Lennart Ljung,et al. Nonlinear black-box modeling in system identification: a unified overview , 1995, Autom..
[21] Gonzalo R. Arce,et al. Piecewise linear system modeling based on a continuous threshold decomposition , 1996, IEEE Trans. Signal Process..
[22] Arjan van der Schaft,et al. Complementarity modelling of hybrid systems , 1997 .
[23] A. J. van der Schaft,et al. Complementarity modeling of hybrid systems , 1998, IEEE Trans. Autom. Control..
[24] Vassilios Petridis,et al. Identification of switching dynamical systems using multiple models , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).
[25] Alfredo C. Desages,et al. Canonical piecewise-linear approximation of smooth functions , 1998 .
[26] S. Ernst,et al. Hinging hyperplane trees for approximation and identification , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).
[27] Domine M. W. Leenaerts,et al. Piecewise Linear Modeling and Analysis , 1998 .
[28] Don R. Hush,et al. Efficient algorithms for function approximation with piecewise linear sigmoidal networks , 1998, IEEE Trans. Neural Networks.
[29] P. Pucar,et al. On the Hinge-Finding Algorithm for Hinging Hyperplanes , 1998, IEEE Trans. Inf. Theory.
[30] P. Julián,et al. High-level canonical piecewise linear representation using a simplicial partition , 1999 .
[31] Kristin P. Bennett,et al. Multicategory Classification by Support Vector Machines , 1999, Comput. Optim. Appl..
[32] Erik I. Verriest,et al. Multi-mode system identification , 1999, 1999 European Control Conference (ECC).
[33] Arnold Neumaier,et al. Global Optimization by Multilevel Coordinate Search , 1999, J. Glob. Optim..
[34] Alberto Bemporad,et al. Control of systems integrating logic, dynamics, and constraints , 1999, Autom..
[35] Daniel E. Koditschek,et al. Piecewise linear homeomorphisms: the scalar case , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.
[36] Amir F. Atiya,et al. A new algorithm for learning in piecewise-linear neural networks , 2000, Neural Networks.
[37] Paul S. Bradley,et al. k-Plane Clustering , 2000, J. Glob. Optim..
[38] Alberto Bemporad,et al. Observability and controllability of piecewise affine and hybrid systems , 2000, IEEE Trans. Autom. Control..
[39] Bart De Schutter,et al. Optimal Control of a Class of Linear Hybrid Systems with Saturation , 1999, SIAM J. Control. Optim..
[40] W. P. M. H. Heemels,et al. Linear Complementarity Systems , 2000, SIAM J. Appl. Math..
[41] B. Schutter,et al. Model predictive control for max-min-plus-scaling systems , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).
[42] Frank L. Lewis,et al. Adaptive Control of Nonsmooth Dynamic Systems , 2001 .
[43] Bart De Schutter,et al. Equivalence of hybrid dynamical models , 2001, Autom..
[44] C. Fantuzzi,et al. Identification of piecewise affine models in noisy environment , 2002 .
[45] Eberhard Münz,et al. Identification of hybrid systems using a priori knowledge , 2002 .
[46] Edoardo Amaldi,et al. The MIN PFS problem and piecewise linear model estimation , 2002, Discret. Appl. Math..
[47] Neil J. Gordon,et al. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..
[48] M. Resende,et al. A Combinatorial Approach to Piecewise Linear Time Series Analysis , 2002 .
[49] Marco Muselli,et al. Single-Linkage Clustering for Optimal Classification in Piecewise Affine Regression , 2003, ADHS.
[50] Jakob Roll. Local and Piecewise Affine Approaches to System Identification , 2003 .
[51] Didier Maquin,et al. Parameter estimation of switching piecewise linear system , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).
[52] Manfred Morari,et al. A clustering technique for the identification of piecewise affine systems , 2001, Autom..
[53] Giancarlo Ferrari-Trecate,et al. Conditions of Optimal Classification for Piecewise Affine Regression , 2003, HSCC.
[54] S. Sastry,et al. An algebraic geometric approach to the identification of a class of linear hybrid systems , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).
[55] B. Anderson,et al. Recursive identification of switched ARX hybrid models: exponential convergence and persistence of excitation , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).
[56] R. Vidal. Identification of PWARX hybrid models with unknown and possibly different orders , 2004, Proceedings of the 2004 American Control Conference.
[57] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[58] Alberto Bemporad,et al. Identification of piecewise affine systems via mixed-integer programming , 2004, Autom..
[59] S. Paoletti. IDENTIFICATION OF PIECEWISE AFFINE MODELS , 2004 .
[60] A. Juloski,et al. Data-based hybrid modelling of the component placement process in pick-and-place machines , 2004 .
[61] Yi Ma,et al. Identification of hybrid linear time-invariant systems via subspace embedding and segmentation (SES) , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).
[62] M. Verhaegen,et al. Subspace identification of piecewise linear systems , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).
[63] W. P. M. H. Heemels,et al. A Bayesian approach to identification of hybrid systems , 2004, IEEE Transactions on Automatic Control.
[64] Eberhard Münz,et al. CONTINUOUS OPTIMIZATION APPROACHES TO THE IDENTIFICATION OF PIECEWISE AFFINE SYSTEMS , 2005 .
[65] W. P. M. H. Heemels,et al. Comparison of Four Procedures for the Identification of Hybrid Systems , 2005, HSCC.
[66] Alberto Bemporad,et al. A bounded-error approach to piecewise affine system identification , 2005, IEEE Transactions on Automatic Control.
[67] F. Rosenqvist,et al. Realisation and estimation of piecewise-linear output-error models , 2005, Autom..
[68] René Vidal,et al. Identification of Deterministic Switched ARX Systems via Identification of Algebraic Varieties , 2005, HSCC.
[69] Yasmin L. Hashambhoy,et al. Recursive Identification of Switched ARX Models with Unknown Number of Models and Unknown Orders , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.
[70] Kiyotsugu Takaba,et al. Identification of piecewise affine systems based on statistical clustering technique , 2004, Autom..
[71] René Vidal,et al. A Unified Algebraic Approach to 2-D and 3-D Motion Segmentation and Estimation , 2006, Journal of Mathematical Imaging and Vision.
[72] A. Juloski,et al. A BAYESIAN APPROACH TO THE IDENTIFICATION OF PIECEWISE LINEAR OUTPUT ERROR MODELS , 2006 .
[73] Alberto Bemporad,et al. An MPC/hybrid system approach to traction control , 2006, IEEE Transactions on Control Systems Technology.
[74] M. Verhaegen,et al. ITERATIVE SUBSPACE IDENTIFICATION OF PIECEWISE LINEAR SYSTEMS , 2006 .
[75] C. Abdallah,et al. Recent techniques for the identification of piecewise affine and hybrid systems , 2006 .
[76] Stefano Soatto,et al. Applications of hybrid system identification in computer vision , 2007, 2007 European Control Conference (ECC).
[77] Giancarlo Ferrari-Trecate,et al. Hybrid identification methods for the reconstruction of Genetic Regulatory Networks , 2007, 2007 European Control Conference (ECC).