Author
R.J.P. Schrama
Bio: R.J.P. Schrama is an academic researcher from Delft University of Technology. The author has contributed to research in topics: Adaptive control & System identification. The author has an hindex of 1, co-authored 1 publications receiving 232 citations.
Papers
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TL;DR: In this paper, a frequency-response identification technique and a robust control design method are used to set up such an iterative scheme, where each identification step uses the previously designed controller to obtain new data from the plant and the associated identification problem has been solved by means of a coprime factorization of the unknown plant.
Abstract: If approximate identification and model-based control design are used to accomplish a high-performance control system, then the two procedures must be treated as a joint problem. Solving this joint problem by means of separate identification and control design procedures practically entails an iterative scheme. A frequency-response identification technique and a robust control design method are used to set up such an iterative scheme. Each identification step uses the previously designed controller to obtain new data from the plant. The associated identification problem has been solved by means of a coprime factorization of the unknown plant. The technique's utility is illustrated by an example. >
237 citations
Cited by
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TL;DR: The new design method is direct and can be applied using a single set of data generated by the plant, with no need for specific experiments nor iterations, and it is shown that the method searches for the global optimum of the design criterion.
901 citations
TL;DR: It is argued that a guiding principle should be to model as well as possible before any model or controller simplifications are made as this ensures the best statistical accuracy.
500 citations
TL;DR: An overview is given of some current research activities on the design of high-performance controllers for plants with uncertain dynamics, based on approximate identification and model-based control design, in dealing with the interplay between system identification and robust control design.
478 citations
01 Jan 1993
TL;DR: The central message of this paper is to show that the global control performance criterion must determine the identification criterion, which leads to non standard identification criteria, which can be minimized by appropriate experimental set-ups.
Abstract: This paper aims at introducing the reader to the various issues that arise in the development of a coherent methodology for the development of robust control design on the basis of models identified from data. When a reduced complexity model is identified with the purpose of designing a robust controller, the model is just a vehicle for the computation of a controller. The design of the identification and of the controller must be seen as two parts of a joint design problem. The central message of this paper is to show that the global control performance criterion must determine the identification criterion. This leads to non standard identification criteria, which can be minimized by appropriate experimental set-ups.
330 citations
TL;DR: It is shown that, when the controller is a smooth function of the input-output dynamics and the disturbance spectrum, the best controller performance is achieved by performing the identification in closed loop with an operating controller that is the ideal controller.
261 citations