Miguel A. Sotelo B · 2016
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Zi-Xing Cai · 1997
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A. Meystel · 2024
A new area of systems engineering endeavor has emerged, which can be considered an intersection of Artificial Intelligence, Operation Research, and Control Theory, and which is actively spurred and stimulated by the advances in Computer Science (see Fig. 1).
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2018
Intelligent control, the discipline where control algorithms are developed by emulating certain characteristics of intelligent biological systems, is an emerging area of control that is being fueled by the advancements in computing technology (Antsaklis and Passino, 1993; Passino, 2005). For instance, software development and validation tools for expert systems (computer programs that emulate the actions of a human who is proficient at some task) are being used to construct “expert controllers” that seek to automate the actions of a human operator who controls a system. Other knowledge-based systems such as fuzzy systems (rule-based systems that use fuzzy logic for knowledge representation and inference) and planning systems (that emulate human planning activities) are being used in a similar manner to automate the perceptual, cognitive (deductive and inductive), and action-taking characteristics of humans who perform control tasks. Artificial neural networks emulate biological neural networks and have been used to (1) learn how to control systems by observing the way that a human performs a control task, and (2) learn in an online fashion how to best control a system by taking control actions, rating the quality of the responses achieved when these actions are used, then adjusting the recipe used for generating control actions so that the response of the system improves. Genetic algorithms are being used to evolve controllers via off-line computer-aided-design of control systems or in an online fashion by maintaining a population of controllers and using survival of the fittest principles where “fittest” is defined by the quality of the response achieved by the controller.
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Willem de Lint, Alan Hall · University of Toronto Press eBooks · 2009
Investigating the ways in which police practices have evolved in relation to labour strikes and protests, Intelligent Control examines the means by which police forces have developed more coercive and consent-based approaches to regulating social unrest.
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IEEE Control Systems Magazine · 1986
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SpringerReference · 2011
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J. A. Cook, J. W. Grizzle Y, J. Sun · 1993
Automotive engine control systems must satisfy diverse and often con icting requirements. These include regulating exhaust emissions to meet increasingly stringent standards without sacri cing good drivability � providing increased fuel economy to satisfy customer desires and to comply with Corporate Average Fuel Economy (CAFE) regulations � and delivering
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C.J. Harris, Christopher Moore, Martin Brown · World Scientific series in robotics and intelligent systems · 1993
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Louis C. Westphal · 2001
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Fumio Hamano · 1991
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H Wang, D.A. Linkens · World Scientific series in robotics and intelligent systems · 1996
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Nital S. Patel · Digital Repository at the University of Maryland (University of Maryland College Park) · 1993
It is often observed that human experts can tune the parameters of a controller based on their knowledge and experience, rather than on complicated algorithms. In fact, more often than not, they have only a vague idea of the process model. An attempt is made here to create a fuzzy-logic based expert which would emulate such behavior. The expert is, specifically designed to tune the gains of a Proportional-Integral-Derivative (PID) controller, applied to stable dominant pole plants having large rise times. It is observed, that a number of plants found in the chemical process industry can be suitable modeled as such systems. a rule base for the expert was developed after analysis and simulation studies. Attempts have been made to keep the rules as few and simple as possible. At no point is any attempt made to estimate the parameters of the plant model. The expert observes only the output from the plant. Results of the application of the expert to a second order plant, to the separator temperature control loop of the Tennessee Eastman problem, and to a third order plant are presented. The expert is found to successfully tune the PID gains, and the results provide encouragement for the creation of such experts which can handle a class of plants.,
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none · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2019
Intelligent Load Control (ILC) is a PNNL-developed technology that enables buildings to manage energy consumption to a desired level. This video provides basic information about ILC and its applications.
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None, None · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2017
The ILC algorithm prioritizes available loads for curtailment in large and small/medium size commercial buildings.
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Karl Johan Åström · Lund University Publications (Lund University) · 1984
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École Centrale, De Lille, Luo Minzhi et al. · 2012
THÈSE présentée en vue d’obtenir le grade de DOCTEUR Spécialité: Automatique, génie informatique, traitement du signal et des images
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Panos Antsaklis, Panos Antsaklis Chair · 1993
Intelligent control describes the discipline where control methods are developed that attempt to emulate important characteristics of human intelligence. These characteristics include adaptation and learning, planning under large uncertainty and coping with large amounts of data. Today, the area of intelligent control tends to encompass everything that is not characterized as conventional control; it has, however, shifting boundaries and what is called "intelligent control " today, will probably be called "control " tomorrow. The main difficulty in specifying exactly what is meant by the term Intelligent control stems from the fact that there is no agreed upon definition of human intelligence and intelligent behavior and the centuries old debate of what constitutes intelligence is still continuing, nowadays among educators, psychologists, computer scientists and engineers. Apparently the term Intelligent control was coined in the 70's by K.S. Fu. Reference 1 is the main source of the several descriptions of intelligent control and its attributes discussed in this article. There are a number of areas related to the area of Intelligent control. Intelligent control is interdisciplinary as it combines and extends theories and methods from areas such as control, computer science and operations research. It uses theories from mathematics and seeks inspiration and ideas from biological systems. Intelligent control methodologies are being applied to robotics and automation, communications, manufacturing, traffic control, to mention but a few application areas. Neural networks, fuzzy control, genetic algorithms, planning systems, expert systems, hybrid systems are all areas where related work is taking place. The areas of computer science and in particular artificial intelligence provide knowledge representation ideas, methodologies and tools such as semantic networks, frames, reasoning techniques and computer languages such as prolog. Concepts and algorithms developed in the areas of adaptive control and machine learning help intelligent
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YUE PIK KONG · National University of Singapore · 1994
Master's
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A. Stephen Morse · 2012
Abstract : Here is a listing some of what this project has accomplished. We ve given a probabilistic explanation of why a previously proposed accelerated gossip algorithm works. We ve resolved the problem of automatically localizing a mobile autonomous agent using range-only measurements. We invented new tools for analyzing convergence rates for consensus and gossiping algorithms. We derived a complete solution to the problem of controlling a directed formation of triangular shape. We proved that for communication graphs which are trees, the rate at which periodic gossiping distributed algorithms converge does not depend on the order in which the individual gossips occur. We developed a new algorithm maintaining formations of mobile autonomous agents with cycle-free graphs. We developed request-based deterministic gossip protocols which are guaranteed not to deadlock.
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