Identification for Control: From the Early Achievements to the Revival of Experiment Design*

European Journal of Control - Tập 11 Số 4-5 - Trang 335-352 - 2005
Michel Gevers1
1Center for Systems Engineering and Applied Mechanics (CESAME), Université Catholique de Louvain, Bâtiment Euler, 4 Avenue Georges Lemaître, B-1348 Louvain-la-Neuve, Belgium

Tóm tắt

Từ khóa


Tài liệu tham khảo

Albertos, 2002

Anderson, 1998, Fundamental problems in adaptive control, 9

Åström, 1994, Analysis of a scheme for iterated identification and control, 171

Åström, 1965, Numerical identification of linear dynamic systems from normal operating records

Barenthin M, Hjalmarsson H. Identification and control: joint input design and H∞ state feedback with ellipsoidal parametric uncertainty. Submitted for publication 2005

Barenthin, 2005, Applications of mixed H2 and H∞ input design in identification

Bayard, 1994, High-order multivariable transfer function curve fitting: algorithms, sparse matrix methods and experimental results, Automatica, 30, 1439, 10.1016/0005-1098(94)90009-4

Bitmead, 1993, Iterative control design approaches, 381

Bombois, 2005, Quantification of frequency domain error bounds with guaranteed confidence level in prediction error identification, Systems Control Letters, 54, 471, 10.1016/j.sysconle.2004.09.011

Bombois, 2005, Least costly identification experiment for control, Submittted to Automatica

Bombois, 2004, Cheapest open-loop identification for control, 382

Bombois, 2004, Least costly identification experiment for control: a solution based on a high-order model approximation, 2818

Bombois, 2000, A measure of robust stability for an identified set of parametrized transfer functions, IEEE Trans Automatic Control, 45, 2141, 10.1109/9.887643

Bombois, 2001, Robustness analysis tools for an uncertainty set obtained by prediction error identification, Automatica, 37, 1629, 10.1016/S0005-1098(01)00104-2

Boyd, 1994, 15

Cooley, 1998, Integrated identification and robust control, J Process Control, 8, 431, 10.1016/S0959-1524(98)00027-4

Cooley, 2001, Control-relevant experiment design for multivariable systems described by expansions in orthonormal bases, Automatica, 37, 273, 10.1016/S0005-1098(00)00139-4

de Callafon, 1997, Suboptimal feedback control by a scheme of iterative identification and control design, Mathematical Modelling Systems, 3, 77, 10.1080/13873959708837050

de Callafon, 1993, Control-relevant identification of a compact disc pick-up mechanism, 2050

de Vries, 1995, Quantification of uncertainty in transfer function estimation: a mixed probabilistic – worst-case approach, Automatica, 31, 543, 10.1016/0005-1098(95)98483-M

Deistler, 2002, System identification and time series analysis: Past present, and future, 97

Douma, 2003, Controller tuning freedom under plant identification uncertainty: double Youla beats gap in robust stability, Automatica, 39, 325, 10.1016/S0005-1098(02)00223-6

Forssell, 1999, Closed-loop identification revisited, Automatica, 35, 1215, 10.1016/S0005-1098(99)00022-9

Forssell, 2000, Some results on optimal experiment design, Automatica, 36, 749, 10.1016/S0005-1098(99)00205-8

Gaikwad, 1997, Multivariable frequencyresponse curvefitting with application to controlrelevant parameter estimation problems, Automatica, 33, 1169, 10.1016/S0005-1098(97)00018-6

Gevers, 1991, Connecting identification and robust control: A new challenge, 1

Gevers, 1993, Towards a joint design of identification and control?, 111

Gevers, 1986, Optimal experiment designs with respect to the intended model application, Automatica, 22, 543, 10.1016/0005-1098(86)90064-6

Gevers, 1998, Issues in modeling for control, 1615

Gevers, 2003, Model validation for control and controller validation in a prediction error identification framework – Part I: theory, Automatica, 39, 403, 10.1016/S0005-1098(02)00234-0

Goodwin, 1977

Goodwin, 1992, Quantifying the error in estimated transfer functions with application to model order selection, IEEE Trans Automatic Control, 37, 913, 10.1109/9.148344

Hakvoort, 1997, Identification of probabilistic system uncertainty regions by explicit evaluation of bias and variance errors, IEEE Trans Automatic Control, 42, 1516, 10.1109/9.649691

Hansen, 1989, Closed-loop identification via the fractional representation: Experiment design, 1422

Hildebrand, 2003, Identification for control: optimal input design with respect to a worst-case ν- gap cost function, SIAM J Control Optimization, 41, 1586, 10.1137/S0363012901399866

Hjalmarsson H. From experiments to closed-loop control (plenary lecture). In: CD-ROM Proceedings of the 13th IFAC symposium on system identification, Rotterdam, The Netherlands, pp. 1-14

Hjalmarsson, 2005, From experiment design to closed-loop control, Automatica, 41, 393, 10.1016/j.automatica.2004.11.021

Hjalmarsson, 2003, Using a sufficient condition to analyze the interplay between identification and control, 45

Hjalmarsson, 1996, For model-based control design, closed-loop identification gives better performance, Automatica, 32, 1659, 10.1016/S0005-1098(96)80003-3

Hjalmarsson, 1995, Optimality and sub-optimality of iterative identification and control design schemes, 2559

Ho, 1965, Effective construction of linear state-variable models from input-output functions, Regelungstechnik, 12, 545

Holmberg, 2000, An identification-for-control procedure with robust performance, Control Eng Practice, 8, 1107, 10.1016/S0967-0661(00)00049-6

Jansson, 2004, A framework for mixed H∞ and H2 input design

Jansson, 2004, A general framework for mixed H∞ and H2 input design, Submitted for publication to IEEE Trans Automatic Control

Jansson, 2005, Optimal experiment design in closed loop

Jun, 1996, A computeraided design tool for robustness analysis and controlrelevant identification of horizon predictive control with application to a binary distillation column, J Process Control, 6, 177, 10.1016/0959-1524(95)00057-7

Kalman, 1960, Contributions to the theory of optimal control, Boletin de la Sociedad Matematica Mexicana, 5, 102

Kalman, 1960, A new approach to linear filtering and prediction problems, J Basic Eng Trans ASME Ser D, 82, 34, 10.1115/1.3662552

Kosut, 1994, Least-squares parameter set estimation for robust control design, 3002

Landau, 1999, From robust control to adaptive control, Control Eng Practice, 7, 1113, 10.1016/S0967-0661(99)00076-3

Lee, 1993, A new approach to adaptive robust control, Int J Adapt Control Signal Processing, 7, 183, 10.1002/acs.4480070303

Lindqvist, 2001, Identification for control: adaptive input design using convex optimization

Ljung, 1985, Asymptotic variance expressions for identified black-box transfer function models, IEEE Trans Automatic Control, AC-30, 834, 10.1109/TAC.1985.1104093

Ljung, 1999

Ljung, 2000, Model error modeling and control design

Mäkilä, 1995, Worst-case control-relevant identification, Automatica, 31, 1799, 10.1016/0005-1098(95)00106-3

Mehra, 1974, Optimal input signals for parameter estimation in dynamic systems – survey and new results, IEEE Trans Automatic Control, 19, 753, 10.1109/TAC.1974.1100701

Milanese, 1991, Optimal estimation theory for dynamic systems with set membership uncertainty: An overview, Automatica, 27, 997, 10.1016/0005-1098(91)90134-N

Morari, 1989

Murray, 2003, Future directions in control in an informationrich world, IEEE Control Systems Mag, 23, 20, 10.1109/MCS.2003.1188769

Nesterov, 1994, 13

Ninness, 1995, Estimation of model quality, Automatica, 31, 32, 10.1016/0005-1098(95)00108-7

Ninness, 2004, Variance error quantifications that are exact for finite model order, IEEE Trans Automatic Control, 49, 1275, 10.1109/TAC.2004.832202

Partanen, 1995, The application of an iterative identification and controller design to a sugar cane crushing mill, Automatica, 31, 1547, 10.1016/0005-1098(95)00077-A

Rivera, 2003, “Plant-friendly” system identification: a challenge for the process industries, 917

Rivera, 1995, Systematic techniques for determining modeling requirements for SISO and MIMO feedback control problems, J Process Control, 5, 213, 10.1016/0959-1524(95)00013-G

Schrama, 1993, Adaptive performance enhancement by iterative identification and control design, Int J Adapt Control Signal Processing, 7, 475, 10.1002/acs.4480070513

Shook, 1992, A control-relevant identification strategy for GPC, IEEE Trans Automatic Control, AC-37, 975, 10.1109/9.148352

Skelton, 1989, Model error concepts in control design, Int J Control, 49, 1725, 10.1080/00207178908559735

Skogestad, 1996

Tjärnström, 2000, Computing uncertainty regions with simultaneous confidence degree using bootstrap, 1133

Van den Hof, 1993, An indirect method for transfer function estimation from closed loop data, Automatica, 29, 1523, 10.1016/0005-1098(93)90015-L

Van den Hof, 1995, Identification and control – closed-loop issues, Automatica, 31, 1751, 10.1016/0005-1098(95)00094-X

Vinnicombe, 1993, Frequency domain uncertainty and the graph topology, IEEE Trans Automatic Control, AC-38, 1371, 10.1109/9.237648

Wahlberg, 1986, Design variables for bias distribution in transfer function estimation, IEEE Trans Automatic Control, 31, 134, 10.1109/TAC.1986.1104221

Xie, 2001, Asymptotic variance expressions for estimated frequency functions, IEEE Trans Automatic Control, AC-46, 1887

Zang, 1995, Iterative weighted least-squares identification and weighted LQG control design, Automatica, 31, 1577, 10.1016/0005-1098(95)00082-8

Zarrop, 1979, 21

Zhou, 1995