Model validation: a connection between robust control and identification
Roy S. Smith,John Doyle +1 more
TLDR
The model validation problem addressed is: given experimental data and a model with both additive noise and norm-bounded perturbations, is it possible that the model could produce the observed input-output data?Abstract:
The gap between the models used in control synthesis and those obtained from identification experiments is considered by investigating the connection between uncertain models and data. The model validation problem addressed is: given experimental data and a model with both additive noise and norm-bounded perturbations, is it possible that the model could produce the observed input-output data? This problem is studied for the standard H/sub infinity // mu framework models. A necessary condition for such a model to describe an experimental datum is obtained. For a large class of models in the robust control framework, this condition is computable as the solution of a quadratic optimization problem. >read more
Citations
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Proceedings ArticleDOI
A frequency domain approach to identification, uncertainty characterization and robust control design
D.S. Bayard,R.Y. Chiang +1 more
TL;DR: In this paper, an approach to frequency domain identification for the explicit purpose of designing robust H/sub /spl infin// controllers is presented. But the main feature of this approach is that the resulting controller is guaranteed to work as designed (when applied to the true system) to a prescribed statistical confidence.
Journal ArticleDOI
Hybrid systems in automotive electronics design
TL;DR: This paper identifies critical steps in the design flow and extracts a number of open problems where hybrid system technology might play an important role and takes a broad view of the development process for embedded control systems in the automotive industry.
Journal ArticleDOI
Unfalsified model reference adaptive control using the ellipsoid algorithm
TL;DR: The unfalsified control paradigm which uses as plant information, experimental trajectories of plant signals, is applied to the model reference adaptive control problem and the use of an ellipsoid algorithm overcomes the need of gridding the parameter space used in prior applications of unfalsifying control.
Improving driver comfort in commercial vehicles : modeling and control of a low-power active cabin suspension system
TL;DR: In this article, a low-power active cabin suspension design for semi-active and active suspensions for heavy vehicles has been investigated and validated using a reduced-order simulation model of a tractor semi-trailer.
Book ChapterDOI
Iterative Adaptive Control: Windsurfing with Confidence
TL;DR: The authors' speculations on this “windsurfing” approach to adaptive control was first expressed in [2] and subsequently filled out in a series of papers [24,25].
References
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Proceedings ArticleDOI
Structured uncertainty in control system design
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Journal ArticleDOI
Control oriented system identification: a worst-case/deterministic approach in H/sub infinity /
TL;DR: The authors formulate and solve two related control-oriented system identification problems for stable linear shift-invariant distributed parameter plants, each involving identification of a point sample of the plant frequency response from a noisy, finite, output time series obtained in response to an applied sinusoidal input.