The paper proposes a frequency-domain approach to the problem of fixed mode elimination in decentralized systems. systems having distinct or repeated fixed modes are considered and decentralized controllers requiring ...
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The paper proposes a frequency-domain approach to the problem of fixed mode elimination in decentralized systems. systems having distinct or repeated fixed modes are considered and decentralized controllers requiring minimum number of interconnection gains for the elimination of fixed modes are characterized.
Fundamental factors limiting the widespread application of current robotic systems are the requirements for precise control of the robot task environment, custom-designed fixtures and end-effectors, and on-site contro...
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Fundamental factors limiting the widespread application of current robotic systems are the requirements for precise control of the robot task environment, custom-designed fixtures and end-effectors, and on-site control program development. These requirements arise because current robotic systems do not have an understanding of the robot task environment. Further, these systems are not able to react intelligently to non-deterministic events which occur during task execution. This paper examines the nature of understanding and its use to resolve uncertainty as it relates to robot task execution. Then a research plan which is aimed at the systematic incorporation of understanding into the robot task environment is outlined.
Robot manipulators have highly nonlinear dynamics. Therefore the control of multi-link robot arms is a challenging and difficult problem. In this paper a nonlinear dynamic model is first presented for an n-axis robot ...
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The problem of designing intelligent machines operating in uncertain environments with minimum supervision or interaction with a human operator is examined. The structure of an intelligent machine is defined to De the...
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The problem of designing intelligent machines operating in uncertain environments with minimum supervision or interaction with a human operator is examined. The structure of an intelligent machine is defined to De the structure of a Hierarchically Intelligent Control System, composed of three levels hierarchically ordered according to the principle of "increasing intelligence with decreasing precision," namely: the organization, the coordination and the hardware control levels. The behavior of such a machine may be managed by controls with special considerations and its "intelligence" is directly related to the derivation or a compatible measure that associates the intelligence of the higher levels with the precision of execution of the lower levels. It is shown that the concept of entropy as defined in Information Theory and Theoretical Thermodynamics is a sufficient analytic measure that unifies the treatment of all the levels of an intelligent machine as the mathematical problem of finding the right sequence of internal decisions and controls for a system structured in the order of intelligence and inverse order of precision (constraint) such that it minimizes its total entropy
computer-aided design (CAD) has found a hew home in the control systems theory. Many control system's related problems such as analysis, design, estimation, filtering and simulation are now handled through CAD pac...
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computer-aided design (CAD) has found a hew home in the control systems theory. Many control system's related problems such as analysis, design, estimation, filtering and simulation are now handled through CAD packages and languages. Through these software tools, even a novice computer programmer can take advantage of powerful computational and numerical algorithms for control systems problems. In this paper a CAD language for control and Kalman filtering will be presented. The language, called CONTROL. lab is written in FORTRAN/77 and can run under UNIX or VMS on a DEC 11/780 VAX computer system.
This book and its sister volumes constitute the Proceedings of the Third International Symposium on Neural Networks (ISNN 2006) held in Chengdu in southwestern China during May 28–31, 2006. After a successful ISNN 20...
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ISBN:
(数字)9783540344407
ISBN:
(纸本)9783540344391
This book and its sister volumes constitute the Proceedings of the Third International Symposium on Neural Networks (ISNN 2006) held in Chengdu in southwestern China during May 28–31, 2006. After a successful ISNN 2004 in Dalian and ISNN 2005 in Chongqing, ISNN became a well-established series of conferences on neural computation in the region with growing popularity and improving quality. ISNN 2006 received 2472 submissions from authors in 43 countries and regions (mainland China, Hong Kong, Macao, Taiwan, South Korea, Japan, Singapore, Thailand, Malaysia, India, Pakistan, Iran, Qatar, Turkey, Greece, Romania, Lithuania, Slovakia, Poland, Finland, Norway, Sweden, Demark, Germany, France, Spain, Portugal, Belgium, Netherlands, UK, Ireland, Canada, USA, Mexico, Cuba, Venezuela, Brazil, Chile, Australia, New Zealand, South Africa, Nigeria, and Tunisia) across six continents (Asia, Europe, North America, South America, Africa, and Oceania). Based on rigorous reviews, 616 high-quality papers were selected for publication in the proceedings with the acceptance rate being less than 25%. The papers are organized in 27 cohesive sections covering all major topics of neural network research and development. In addition to the numerous contributed papers, ten distinguished scholars gave plenary speeches (Robert J. Marks II, Erkki Oja, Marios M. Polycarpou, Donald C. Wunsch II, Zongben Xu, and Bo Zhang) and tutorials (Walter J. Freeman, Derong Liu, Paul J. Werbos, and Jacek M. Zurada).
This book and its sister volumes constitute the Proceedings of the Third International Symposium on Neural Networks (ISNN 2006) held in Chengdu in southwestern China during May 28–31, 2006. After a successful ISNN 20...
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ISBN:
(数字)9783540344834
ISBN:
(纸本)9783540344827
This book and its sister volumes constitute the Proceedings of the Third International Symposium on Neural Networks (ISNN 2006) held in Chengdu in southwestern China during May 28–31, 2006. After a successful ISNN 2004 in Dalian and ISNN 2005 in Chongqing, ISNN became a well-established series of conferences on neural computation in the region with growing popularity and improving quality. ISNN 2006 received 2472 submissions from authors in 43 countries and regions (mainland China, Hong Kong, Macao, Taiwan, South Korea, Japan, Singapore, Thailand, Malaysia, India, Pakistan, Iran, Qatar, Turkey, Greece, Romania, Lithuania, Slovakia, Poland, Finland, Norway, Sweden, Demark, Germany, France, Spain, Portugal, Belgium, Netherlands, UK, Ireland, Canada, USA, Mexico, Cuba, Venezuela, Brazil, Chile, Australia, New Zealand, South Africa, Nigeria, and Tunisia) across six continents (Asia, Europe, North America, South America, Africa, and Oceania). Based on rigorous reviews, 616 high-quality papers were selected for publication in the proceedings with the acceptance rate being less than 25%. The papers are organized in 27 cohesive sections covering all major topics of neural network research and development. In addition to the numerous contributed papers, ten distinguished scholars gave plenary speeches (Robert J. Marks II, Erkki Oja, Marios M. Polycarpou, Donald C. Wunsch II, Zongben Xu, and Bo Zhang) and tutorials (Walter J. Freeman, Derong Liu, Paul J. Werbos, and Jacek M. Zurada).
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