The Modeling of Uncertainty in Control Systems Proceedings of the 1992 Santa Barbara Workshop
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...
| Other Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
1994, 1994
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| Edition: | 1st ed. 1994 |
| Series: | Lecture Notes in Control and Information Sciences
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- Identification and robust control
- An essay on identification of feedback systems
- Thoughts on identification for control
- An essay on robust control
- On the character of uncertainty for system identification and robust control design
- Extensions of parametric bounding formulation of identification for robust control design
- Connecting identification and robust control
- On nominal models, model uncertainty and iterative methods in identification and control design
- An informal review of model validation
- From data to control
- Is robust control reliable?
- Modeling uncertainty in control systems: A process control perspective
- A note on H ? system identification with probabilistic a priori information
- A worst case identification method using time series data
- Identification in H ? using time-domain measurement data
- Identification of feedback systems from time series
- Input-output extrapolation-minimization theorem and its applications to model validation and robust identification
- Identification of model error bounds in l 1- and H ?-norm
- Asymptotic worst-case identification with bounded noise
- Sequential approximation of uncertainty sets via parallelotopes
- A robust ellipsoidal-bound approach to direct adaptive control
- On line model uncertainty quantification: Hard upper bounds and convergence
- A mixed deterministic-probabilistic approach for quantifying uncertainty in Transfer Function Estimation
- Estimation for robust control
- Non-vanishing model errors
- Accuracy confidence bands including the bias of model under-fitting
- Iterative identification and control design: A worked out example
- Frequency domain identification for robust control design
- Time domain approach to the design of integrated control and diagnosis systems.-Identification of Ill-conditioned plants — A benchmark problem
- Control design and implementation based on experimental wind turbine models