Adaptive control
Polderman, J.W., Schuppen, J.H. (Jan) van · CWI's Institutional Repository (Centrum Wiskunde & Informatica) · 1988
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About 10,000 papers for “Adaptive control”
Polderman, J.W., Schuppen, J.H. (Jan) van · CWI's Institutional Repository (Centrum Wiskunde & Informatica) · 1988
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Eduardo D. Sontag, Eduardo D. Sontag · 1993
1993 European Control Conference (short course on “Neural Nets for Control”). The first part places neurocontrol techniques in a general learning control framework. The second part of the report, which is essentially independent of the first, briefly surveys several basic theoretical results regarding neural networks.
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Heuvelman, CJ, Veenstra, PC · TU/e Research Portal (Eindhoven University of Technology) · 1966
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Åström, Karl Johan · Lund University Publications (Lund University) · 1979
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Van Nostrand's Scientific Encyclopedia · 2005
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P. M. Swamidass · 2000
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Veenstra, PC, Heuvelman, CJ · Data Archiving and Networked Services (DANS) · 1966
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F. Jurie, P. Martinet, J. Gallice et al. · 2011
Abstract. This paper reports on recent developments of the PSA-LASMEA autonomous vehicle. Since 1993, a new vision module have been added, extending the scope of the perception system. It has been implemented on a speci c architecture based on DSP processors (96002). Both the algorithm and the architecture are described in this paper. Experimental results are also given.
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Ján Mikleš, Miroslav Fikar · 2007
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Landau, Yoan D. · 1979
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Cem Unsalan, Duygun Barkana, Hüseyin Gurhan · 2021
Adaptive control provides another perspective to design a controller for the system at hand. This chapter explains adaptive control concepts starting from general layout. An adaptive controller can be designed when parameters of the system to be controlled are known. The chapter introduces indirect self-tuning regulator (ISTR) and model-reference adaptive control (MRAC) as two different approaches in adaptive control. In ISTR, system parameters are estimated first. The controller is designed based on them. Thus, the controller parameters are updated indirectly via the estimated system parameters. The main idea in MRAC is to choose a reference model to represent the desired system behavior. The controller is set such that the overall system acts as the reference model. The chapter provides application as the real-time parameter estimation of a given system, the DC motor for our case.
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Karl Johan Åström · AccessScience · 2015
AccessScience is an authoritative and dynamic online resource that contains incisively written, high-quality educational material covering all major scientific disciplines. An acclaimed gateway to scientific knowledge, AccessScience is continually expanding the ways it can demonstrate and explain core, trustworthy scientific information that inspires and guides users to deeper knowledge.
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Richard B. Hetnarski, Richard B. Hetnarski · 2014
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O. L. R. JACOBS · Nature · 1967
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Veenstra, PC, Heuvelman, CJ · TU/e Research Portal (Eindhoven University of Technology) · 1966
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Aaström, Karl Johan, Wittenmark, Björn · CERN Document Server (European Organization for Nuclear Research) · 1989
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Pétros Ioannou · Automatica · 1997
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H. M. Kingston, M. L. Kingston · IUPAC Standards Online · 2016
These recommended terms have been prepared to help provide a uniform approach to terminology and notation in laboratory automation and robotics. Since the terminology used in laboratory automation and robotics has been derived from diverse backgrounds, it is often vague, imprecise, and in some cases, in conflict with classical automation and robotic nomenclature.
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Bernard Brogliato, Bernhard Maschke, Rogelio Lozano et al. · Communications and control engineering/Communications and control engineering series · 2006
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J.W. Polderman, J. H. Schuppen · Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands · 1988
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