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IEEE International Conference on Evolutionary Computation

作者： G. Dozier S. McCullough A. Homaifar E. Tunstel L. Moore Department of Computer Science & Engineering Aubum University Auburn AL USA NASA Center for Autonomous Control Engineering North Carolina Agriculture and Technical State University Greensboro NC USA Jet Propulsion Laboratory Robotic Vehicles Group Pasadena CA USA

The paper introduces a new selection algorithm that can be used for evolutionary path planning systems. This new selection algorithm combines fuzzy inference along with tournament selection to select candidate paths (CPs) to be parents based on: (1) the Euclidean distance from origin to destination, (2) the sum of the changes in the slope of a path, and (3) the average change in the slope of a path. The authors provide a detailed description of the fuzzy inference system used in the new fuzzy tournament selection algorithm (FTSA) as well as some examples of its usefulness. They use 12 instances of the FTSA to rank a population of CPs using the above criteria. Based on its path ranking capability, they show how the FTSA can obviate the need for the development of an explicit multiobjective evaluation function. Finally, they use the FTSA to enhance the performance of an existing evolutionary path planning system called GEPOA.

关键词： Path planning Inference algorithms Fuzzy systems Euclidean distance Robots computer science NASA Automotive engineering Equations Propulsion

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Artificial potential field based robot navigation, dynamic constrained optimization and simple genetic hill-climbing

Artificial potential field based robot navigation, dynamic c...

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IEEE International Conference on Evolutionary Computation

作者： G. Dozier A. Homaifar S. Bryson L. Moore Department of Computer Science andEngineering Aubum University USA Center for Autonomous Control Engineering North Carolina Agriculture and Technical State University Greensboro NC USA Machine Intelligence Laboratory NC A&T State University Greensboro NC USA

The authors show a relationship between artificial potential field (APF) based motion planning/navigation and constrained optimization. They then present a simple genetic hill-climbing algorithm (SGHC) which is used to navigate a point robot through an environment using the APF approach. The motivation for the research is a robot that they are currently developing, named AGIE-3 (autonomous Guided Intelligent Equipment 3), which senses and navigates through the use of a stereo vision head. They compare the SGHC with steepest descent hill-climbing (SDHC), using two environments. The first environment is composed of stationary obstacles while the second environment is composed of non-stationary obstacles. In SDHC, candidate moves are evaluated within a 360 degree radius and the best candidate is selected by the robot. One would think that the SGHC would be at a disadvantage; however, the performance of the SGHC is comparable with SDHC even though it does not search 360 degrees for candidate moves. The SGHC has an advantage in that it is capable of evolving the appropriate step size as well as the appropriate angle of movement.

关键词： Navigation Constraint optimization Robot sensing systems Stereo vision Robot vision systems Magnetic heads Genetics Intelligent robots NASA computer science

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Robotic assistants for aircraft inspectors

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IEEE Instrumentation and Measurement Magazine 1998年第1期1卷 16-30页

作者： Siegel, Mel Gunatilake, Priyan Podnar, Gregg Intelligent Sensor Msrmt. C. Robotics Institute Carnegie Mellon University University of Colorado JILA University of Virginia SUNY Buffalo NY United States Extranuclear Laboratories ABB-Extrel Aircraft Diagnostics Corporation University of Alaska Fairbanks AK United States Elec. and Comp. Eng. Department Carnegie Mellon University CMU Vis. Lab. of the Robotics Institute CMU Mobile Robot Laboratory Engineering Design Research Center CMU Computer Science Department JiangXi University Robotics Institute Measurement and Control Laboratory

Various alternative aircraft inspection methods are first discussed and advantages of using robots are analysed. ANDI (Automated NonDestructive Inspector) and CIMP (Crown Inspection Mobile Platform) are then described. Remote 3D stereoscopic visual inspection is outlined and algorithms developed for crack detection and surface and subsurface corrosion detection are described. Future development trends are also outlined.

关键词： Robots Aircraft Aerospace electronics Instruments

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Royal Academy of Medicine in Ireland - Section of Bioengineering - Proceedings of meeting held in Dundalk, Co. Louth, in February 1998.

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IRISH JOURNAL OF MEDICAL science 1998年第4期167卷 256-276页

作者： [Anonymous] Orthopaedic Research Unit The Queen’s University of Belfast School of Biomedical Sciences The Queen’s University of Belfast Howmedica International Ltd. Raheen Industrial Estate Limerick Department of Mechanical Engineering Trinity College Dublin 2 Mater Hospital Dublin 7 Orthopaedic Research Laboratory Århus University Hospital Denmark University of Limerick Limerick Limerick Regional Hospital Raheen Limerick Boston Scientific Ireland Ltd. Galway Department of Mechanical Engineering University College Dublin Dublin Department of Electrical and Electronic Engineering University College Dublin Dublin Bioengineering Research Centre Department of Mechanical Engineering University College Dublin Dublin Northern Ireland Bio-Engineering Centre (NIBEC) School of Electrical and Mechanical Engineering University of Ulster Newtownabbey Department of Mechanical & Manufacturing Engineering The Ashby Building The Queen’s University of Belfast Johnson and Johnson Professional Orthopaedic Division Queensway England Department of Cardiology and Department of Medical Physics & Bioengineering St. James’s Hospital Dublin 8 Burke House Ellison Street Castlebar Royal College of Surgeons in Ireland Department of Surgery Beaumont Hospital Dublin Department of Electronic and Electrical Engineering Trinity College Dublin 2 Department of Aeronautical Engineering The Queen’s University of Belfast Vascular Unit Belfast City Hospital Department of Medical Physics and Bioengineering St. James’s Hospital Dublin 8 Centre for Biomedical Electronics Department of Electronic and Computer Engineering University of Limerick Limerick Department of Mechanical and Aeronautical Engineering University of Limerick Limerick School of Health Sciences University of Ulster Ireland School of Physiotherapy University of Ulster Newtownabbey Clinical Engineering NI Medical Physics Agency Belfast and Radiology Royal Victoria Hospital Musgrave Park Hospital University of Limerick Biomedical Institute (ULBMI) Uni

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A 2.4-GHz silicon-on-sapphire CMOS low-noise amplifier

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IEEE MICROWAVE AND GUIDED WAVE LETTERS 1997年第10期7卷 350-352页

作者： Johnson, RA Chang, CE delaHoussaye, PR Wood, ME Garcia, GA Asbeck, PM Lagnado, I IEEE Department of Electrical and Computer Engineering University of California Rockwell Science Center Naval Command Control and Ocean Surveillance Center RDT&E Division (NRaD)

A low-noise amplifier operating at 2.4 GHz has been fabricated with MOSFET's in silicon-on-sapphire technology, The amplifier has a 2.8-dB noise figure, IO-dB gain, and 14-dBm output referred IP3 with 14-mW power ... 详细信息

关键词： microwave FET amplifiers noise MMIC's

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Fuzzzy constraint network topology and evolutionary hill-climbing 35

Fuzzzy constraint network topology and evolutionary hill-cli...

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35th ACM Annual Southeast Regional Conference, ACM-SE 1997

作者： Dozier, Gerry Homaifar, Abdollah Bowenf, James Esterline, Albert NASA Center for Autonomous Control Engineering North Carolina a and T State University GreensboroNC27411 United States Department of Computer Science National University of Ireland at Cork Cork Ireland

ISBN: (纸本)0897919254

Tematic hybrid which combines the concept of evolutionary hill-climbing search with the systematic search concept of arc revision to form a hybrid that quickly find solutions to Fuzzy Constraint Satisfaction Problems (FCSPs). The performance of this hybrid on 250 randomly generated FCSPs in which th e fuzzy co n stra in ts are evenly d is trib u ted amongst th e variables of th e FCSP is compared with its p e rformance on 250 randomly generated FCSPs where the fuzzy constraints are unevenly dis trib u ted . The results provide some interes ting insights in th e role th a t Fuzzy C ons tra in t Network Topology has on Evolutionary Search. copy;1997 ACM 0-89791-925-4.

关键词： Network topology

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Solving static and dynamic fuzzy constraint networks using evolutionary hill-climbing 6th

Solving static and dynamic fuzzy constraint networks using e...

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6th International Conference on Evolutionary Programming, EP 1997

作者： Dozier, Gerry Bowen, James Homaifar, Abdollah Esterline, Albert NASA Center for Autonomous Control Engineering North Carolina A and T State University GreensboroNC27411 United States Department of Computer Science National University of Ireland at Cork Cork Ireland

ISBN: (纸本)9783540627883

In this paper we combine the concept of evolutionary hillclimbing search with the systematic search concept of arc revision to form a hybrid system that quickly finds solutions to static and dynamic Fuzzy Constraint Truth Optimization Problems (FCTOPs). We compare the static and dynamic methods for solving FCTOPs using a test suite of an additional 250 randomly generated FCTOPs. In the static method, all the constraints of a FCTOP are known by the hybrid system at runtime. In the dynamic method, only half of the constraints of a FCTOP are known at run-time. Each time our hybrid system discovers a solution that satisfies all of the constraints of the the current network, one additional constraint is added. Results show that our algorithm performs exceptionally well in the presence of dynamic (incremental) constraints. © Springer-Verlag Berlin Heidelberg 1997.

关键词： Hybrid systems

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Neural network based identification of robot dynamics used for neuro-fuzzy controller

Neural network based identification of robot dynamics used f...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： K.K. Kumbla M. Jamshidi NASA Center for Autonomous Control Engineering Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

A technique of identifying the dynamics of a robotics system using neural network is presented. The identified model is used by a fuzzy controller to evaluate the range of the control variables and also the performance of the adaptive control laws on the identified model. An overview of the neuro-fuzzy control architecture is also discussed. This architecture uses two neural networks, one which identifies the system dynamics and another classifies the temporal response of the robotic system. The information from the neural networks is used to make suitable adjustments in the parameter of the fuzzy controller. This paper however concentrates on the theory and operation of identifying the dynamics of a Adept-Two industrial robot. Simulation results are presented.

关键词： Neural networks Robots Fuzzy control Fuzzy neural networks Automatic control Adaptive control System identification control systems NASA Electric variables control

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Real time control of a direct drive motor by a learning neuro-fuzzy controller

Real time control of a direct drive motor by a learning neur...

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IEEE International Conference on Systems, Man and Cybernetics

作者： K.K. Kumbla M. Jamshidi NASA Center for Autonomous Control Engineering Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

A neuro-fuzzy controller is presented which uses neural networks to modify the parameters of an adaptive fuzzy logic controller. The adaptiveness of the fuzzy controller is derived from a rule generation mechanism and changing the scaling factor or the shape of the membership functions. The neural network functions as a classifier of the system's temporal responses. A multilayer perceptron is used to classify the temporal response of the system into different patterns. Depending on the type of pattern such as "response with overshoot", "damped response", "oscillating response", etc. the scaling factor of the input and output membership functions are adjusted to make the system respond in a desired manner. The rule generation mechanism also utilizes the temporal response of the system to evaluate new fuzzy rules. The non-redundant rules are appended to the existing rule base during the tuning cycles. This controller architecture is used in real-time to control a direct drive motor. The control system hardware utilizes a digital signal processor and a PC to implement the controller architecture. Experimental results are illustrated.

关键词： Neural networks Shape control control systems Programmable control Adaptive control Fuzzy logic Fuzzy control Multilayer perceptrons Fuzzy systems Hardware

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Fuzzy observer-based control of nonlinear systems

Fuzzy observer-based control of nonlinear systems

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IEEE Conference on Decision and control

作者： A. Jadbabaie A. Titli M. Jamshidi NASA Center of Autonomous Control Engineering Electrical and Computer Engineering Department University of New Mexico Albuquerque NM USA LAAS du CNRS and INSA Toulouse France

In this paper, some recent results on systematic design of model based fuzzy controllers for nonlinear systems with Takagi-Sugeno (T-S) fuzzy models are discussed. These methods are based on finding a common Lyapunov matrix and state feedback gains for the closed loop T-S fuzzy model using linear matrix inequalities. However, all of these methods assume that the states are available for measurement, while in reality this is not the case. To solve this problem, the notion of fuzzy observer is introduced and a separation theorem for the observer/controller system is stated and proof sketch is presented.

关键词： Fuzzy control Fuzzy systems Nonlinear control systems control systems Nonlinear systems Linear matrix inequalities Fuzzy sets Takagi-Sugeno model Stability analysis State feedback

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