Adaptation and regulation with signal detection implies internal model
By Eduardo D. Sontag. 2003
160 citations recorded by the source corpus.
This note provides a simple result showing, under suitable technical assumptions, that if a systemadapts to a class of external signals U, in the sense of regulation against disturbances or tracking signals in U, thenmust necessarily contain a subsystem which is capable of generating all the signals in U. It is not assumed that regulation is robust, nor is there a prior requirement for the system to be partitioned into separate plant and controller components. Instead, one assumes that a "signal detection" property holds. c � 2003 Elsevier Science B.V. All rights reserved.
Subfields: Control and Systems Engineering
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In Control and Systems Engineering
- Nir Ben-Zrihem
- Zhong-Ping Jiang
- Shie Mannor
- Tom Zahavy
- Weinan Gao
- Csaba Szepesvari
- Jan Peters
- Behnam Neyshabur
Citations in the corpus
- Graying the black box: Understanding DQNs (2016, methodology): “Our main observation in this work is that DQN is learning an internal model (Francis and Wonham, 1975; Sontag, 2003) of the domain without explicitly being trained to.”
- High‐gain control without identification: a survey (2008, unknown): “the internal model principle, see, e.g. [43, 8, 28, 41 ], is in voked).”
- Adaptive Dynamic Programming and Adaptive Optimal Output Regulation of Linear Systems (2016, background): “The problem of output regulation has attracted considerable attention since it is a general mathematical formulation that is applicable to numerous control problems arising from engineering, biology, and other disciplines; see, for instance, [8], [15], [18], [41], [43] and many references therein.”
- Visualizing Dynamics: from t-SNE to SEMI-MDPs (2016, background): “The internal model principle (Francis & Wonham, 1975), ”Every good key must be a model of the lock it opens”, was formulated mathematically for control systems by Sontag (2003), claiming that if a system is solving a control task, it must necessarily contain a subsystem which is capable of predictin”