Computer Intelligent Systems for Manufacture and Control

Author(s):  
Tetyana Baydyk ◽  
Ernst Kussul ◽  
Donald C. Wunsch II
1990 ◽  
Vol 5 (3) ◽  
pp. 147-166 ◽  
Author(s):  
Moonis Ali

AbstractAn overview of research in the areas of aerospace applications of artificial intelligence, expert Systems, neural networks and robotics is presented. Challenges associated with aerospace projects require increasingly complex aerospace Systems which in turn demand automation and fault tolerance. We have addressed these issues and provided a survey of the research on intelligent Systems that has been carried out in an attempt to meet these challenges. The application areas we have overviewed include fault monitoring and diagnosis, generation and management of power in space, efficient and effective command and control, operations and maintenance of space stations, planning and scheduling, automation, and cockpit management.


2005 ◽  
Vol 11 (1-2) ◽  
pp. 99-120 ◽  
Author(s):  
Rolf Pfeifer ◽  
Fumiya Iida ◽  
Josh Bongard

New robotics is an approach to robotics that, in contrast to traditional robotics, employs ideas and principles from biology. While in the traditional approach there are generally accepted methods (e.g., from control theory), designing agents in the new robotics approach is still largely considered an art. In recent years, we have been developing a set of heuristics, or design principles, that on the one hand capture theoretical insights about intelligent (adaptive) behavior, and on the other provide guidance in actually designing and building systems. In this article we provide an overview of all the principles but focus on the principles of ecological balance, which concerns the relation between environment, morphology, materials, and control, and sensory-motor coordination, which concerns self-generated sensory stimulation as the agent interacts with the environment and which is a key to the development of high-level intelligence. As we argue, artificial evolution together with morphogenesis is not only “nice to have” but is in fact a necessary tool for designing embodied agents.


2003 ◽  
Vol 40 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Francisco Jurado ◽  
Antonio Caño ◽  
Manuel Ortega

Control system education must include experimental exercises that complement the theory presented in lectures. These exercises include modelling, analysis and design of a control system. Key concepts and techniques in the area of intelligent systems and control have been discovered and developed over the past few decades. While some of these methods have significant benefits to offer, engineers are often reluctant to utilise new intelligent control techniques, for several reasons. In this paper fuzzy logic controllers have been developed using speed and mechanical power deviations, and a neural network has been designed to tune the gains of the fuzzy logic controllers. Student feedback indicates that theoretical developments in lectures on control systems were only appreciated after the laboratory exercises.


Author(s):  
D. Stylios ◽  
◽  
Peter P Groumpos ◽  
Voula C. Georgopoulos ◽  

We propose an approach to describe and control complex systems based on fuzzy cognitive map (FCM). A mathematical model of FCMs and a calculation method are described as well as a methodology for constructing and developing them that exploits experts who use fuzzy rules to explain cause and effect among concepts. We apply FCMs in a process control problem and demonstrate their effectiveness. We propose a two-level structure for supervisory control of the process, where the supervisor is modeled as an FCM used for failure detection and decision analysis. There is increasing demand for more autonomous, intelligent systems, and the application of FCMs in control and systems may contribute in developing such systems.


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