Control-relevance is a paradigm that interconnects identification with successive model-based control design. Hereby, the current controller, used to conduct identification experiments, is an important factor to success in the design of a new, improved controller. The aim of this paper is to investigate the role of the experimental controller in robust-control-relevant modeling. Such a study is sensible only when unnecessary conservatism is prevented in the construction of perturbed model sets. Hereto, this paper establishes a model uncertainty description that transparently connects to the imposed robust performance criterion. By confronting the developed approach with a next-generation industrial wafer stage, the important role of the exp...
This paper presents the author’s views on the development of identification for control. The paper r...
High-performance robust control hinges on explicit compensation of performance-limiting system pheno...
Abstract—In approximate identification, the goal of the model should be taken into account when eval...
Control-relevance is a paradigm that interconnects identification with successive model-based contro...
Control-relevance is a paradigm that interconnects identification with successive model-based contro...
Control-relevance is a paradigm that interconnects identification with successive model-based contro...
Control-relevance is a paradigm that interconnects identification with successive model-based contro...
The performance of robust controllers depends on the set of candidate plants, but at present this in...
The performance of robust controllers depends on the set of candidate plants, but at present this in...
The performance of robust controllers depends on the set of candidate plants, but at present this in...
The performance of robust controllers depends on the set of candidate plants, but at present this in...
This paper presents the author's views on the development of identification for control. The paper r...
Modern robust control synthesis techniques aim at providing robustness with respect to uncertainty i...
The gap between the models used in control synthesis and those obtained from identification experime...
High-performance robust control hinges on explicit compensation of performance-limiting system pheno...
This paper presents the author’s views on the development of identification for control. The paper r...
High-performance robust control hinges on explicit compensation of performance-limiting system pheno...
Abstract—In approximate identification, the goal of the model should be taken into account when eval...
Control-relevance is a paradigm that interconnects identification with successive model-based contro...
Control-relevance is a paradigm that interconnects identification with successive model-based contro...
Control-relevance is a paradigm that interconnects identification with successive model-based contro...
Control-relevance is a paradigm that interconnects identification with successive model-based contro...
The performance of robust controllers depends on the set of candidate plants, but at present this in...
The performance of robust controllers depends on the set of candidate plants, but at present this in...
The performance of robust controllers depends on the set of candidate plants, but at present this in...
The performance of robust controllers depends on the set of candidate plants, but at present this in...
This paper presents the author's views on the development of identification for control. The paper r...
Modern robust control synthesis techniques aim at providing robustness with respect to uncertainty i...
The gap between the models used in control synthesis and those obtained from identification experime...
High-performance robust control hinges on explicit compensation of performance-limiting system pheno...
This paper presents the author’s views on the development of identification for control. The paper r...
High-performance robust control hinges on explicit compensation of performance-limiting system pheno...
Abstract—In approximate identification, the goal of the model should be taken into account when eval...