The unfalsified control concept and learning

Without a plant model or other prejudicial assumptions, a theory is developed for identifying control laws which are consistent with performance objectives and past experimental data-possibly before the control laws are ever inserted in the feedback loop. The theory complements model-based methods such as H/sup /spl infin//-robust control theory by providing a precise characterization of how the set of suitable controllers shrinks when new experimental data is found to be inconsistent with prior assumptions or earlier data. When implemented in real time, the result is an adaptive switching controller. An example is included.

[1]  I. W. Sandberg,et al.  On the L 2 -boundedness of solutions of nonlinear functional equations , 1964 .

[2]  Stephen P. Boyd,et al.  Identification of Systems with Parametric and Nonparametric Uncertainty , 1990, 1990 American Control Conference.

[3]  John Doyle,et al.  Model validation: a connection between robust control and identification , 1992 .

[4]  Richard Y. Chiang,et al.  Robust control toolbox , 1996 .

[5]  Munther A. Dahleh,et al.  A framework for robust control based model invalidation , 1994, Proceedings of 1994 American Control Conference - ACC '94.

[6]  Maciejowsk.  Multivariable Feedback Design , 1989 .

[7]  Roy S. Smith,et al.  An informal review of model validation , 1994 .

[8]  Robert Kosut.  Adaptive calibration: An approach to uncertainty modeling and on-line robust control design , 1986, 1986 25th IEEE Conference on Decision and Control.

[9]  K. Poolla,et al.  A time-domain approach to model validation , 1994, IEEE Trans. Autom. Control..

[10]  Michael G. Safonov,et al.  Stability and Robustness of Multivariable Feedback Systems , 1980 .

[11]  Stephen P. Boyd,et al.  Set-membership identification of systems with parametric and nonparametric uncertainty , 1992 .

[12]  K. Popper,et al.  Conjectures and refutations;: The growth of scientific knowledge , 1972 .

[13]  Pramod P. Khargonekar,et al.  Sufficient conditions for robust performance of adaptive controllers with general uncertainty structure , 1992, Autom..

[14]  B. Barmish,et al.  Adaptive stabilization of linear systems via switching control , 1986, 1986 25th IEEE Conference on Decision and Control.

[15]  G. Zames.  On the input-output stability of time-varying nonlinear feedback systems Part one: Conditions derived using concepts of loop gain, conicity, and positivity , 1966 .

[16]  J. Willems.  Paradigms and puzzles in the theory of dynamical systems , 1991 .

[17]  Michael G. Safonov,et al.  The unfalsified control concept: A direct path from experiment to controller , 1995 .