The Modeling Of Uncertainty In Control Systems: Proceedings Of The 1992 Santa Barbara Workshop (lecture Notes In Control And Information Sciences)

This book is a collection of work arising from a NSF/ AFOSR sponsored workshop held at the University of California, Santa Barbara, 18-20th June 1992. Sixty-nine researchers, from nine countries, participated. Twelve keynote essays give an overview of the field and speculate on future directions and nineteen technical papers delineate the state of the art in the field. This book serves both as in introduction to the topic and as a reference on the current technical problems and approaches. Identification and robust control....Pages 1-9 An essay on identification of feedback systems....Pages 11-13 Thoughts on identification for control....Pages 15-17 An essay on robust control....Pages 19-23 On the character of uncertainty for system identification and robust control design....Pages 25-28 Extensions of parametric bounding formulation of identification for robust control design....Pages 29-34 Connecting identification and robust control....Pages 35-37 On nominal models, model uncertainty and iterative methods in identification and control design....Pages 39-50 An informal review of model validation....Pages 51-59 From data to control....Pages 61-63 Is robust control reliable?....Pages 65-67 Modeling uncertainty in control systems: A process control perspective....Pages 69-75 A note on H ∞ system identification with probabilistic a priori information....Pages 77-92 A worst case identification method using time series data....Pages 93-104 Identification in H ∞ using time-domain measurement data....Pages 105-116 Identification of feedback systems from time series....Pages 117-126 Input-output extrapolation-minimization theorem and its applications to model validation and robust identification....Pages 127-137 Identification of model error bounds in l 1 - and H ∞ -norm....Pages 139-155 Asymptotic worst-case identification with bounded noise....Pages 157-170 Sequential approximation of uncertainty sets via parallelotopes....Pages 171-180 A robust ellipsoidal-bound approach to direct adaptive control....Pages 181-196 On line model uncertainty quantification: Hard upper bounds and convergence....Pages 197-219 A mixed deterministic-probabilistic approach for quantifying uncertainty in Transfer Function Estimation....Pages 221-233 Estimation for robust control....Pages 235-259 Non-vanishing model errors....Pages 261-274 Accuracy confidence bands including the bias of model under-fitting....Pages 275-287 Iterative identification and control design: A worked out example....Pages 289-302 Frequency domain identification for robust control design....Pages 303-335 Time domain approach to the design of integrated control and diagnosis systems....Pages 337-365 Identification of Ill-conditioned plants — A benchmark problem....Pages 367-376 Control design and implementation based on experimental wind turbine models....Pages 377-391