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Protected Area Systems and Project Management in Protected Area Systems

IFAC Proceedings Volumes 2001年第3期34卷 195-202页

作者： Richard Clarke Georgi Dimirovski University of London School of Social and Natural Sciences Centre for European Protected Area Research 26 Russell Square London WC1B 5DQ United Kingdom FAX#: +44-171-631-6688 DOGUS University Faculty of Engineering Department of Computer Engineering Acibadem Kadikoy TR-81010 Istanbul Republic of Turkey FAX#: +90-216-327-9631 SS Cyril and Methodius University Faculty of Electrical Engineering Institute of Automation & Systems Engineering Karpos 2 BB MK-1000 Skopje Republic of Macedonia

Applications of information technology and systems engineering in the management of protected areas range from simple 'off the shelf project management and work scheduling software, to complex bespoke distributed management systems in which project management is just one element of an integrated IT system encompassing virtually every function (including administration and finance) of a large organisation. The Countryside Management System is a relatively successful system conceived 'bottom up' as a modest experiment by site managers to solve their immediate problems of project control but has significant limitations. The National Trust's Property Management and Information System in the UK is, by contrast, the most ambitious attempt to date of any conservation organisation to computerise its activities and was abandoned prior to full implementation. It seems likely to be some time before the full potential of information technologies such as Geographical Information Systems can be harnessed to the management of protected sites and landscapes, yet it is a promising prospect.

关键词： Countryside management systems ecosystems management protected areas project planning control & recording

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A Lorentz-group based adaptive control for electro-mechanical systems

A Lorentz-group based adaptive control for electro-mechanica...

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Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180)

作者： J.K. Tar I.J. Rudas K. Jezernik J.F. Bito S.J. Torvinen Institute of Mathematical and Computational Sciences Budapest Polytechnic Budapest Hungary Centre of Robotics and Automation Budapest Polytechnic Hungary Faculty of Electrical Engineering and Computer Science Institute of Robotics University of Maribor Maribor Slovenia Dept. of Mechanical Eng. Institute of Production Engineering Tampere University of Technology Tampere Finland

An efficient approach for the adaptive control of approximately and partially known mechanical systems, like traditional soft computing, uses "uniform structures" for modeling, but these structures are obtained from certain Lie groups as the symplectic group or the generalized Lorentz group. This approach considerably reduces the number of free parameters in the model. Until now its efficiency was investigated for mechanical uncertainties and external dynamic interactions. In this paper the behavior of the electric drives are also included in the investigations. A 1-DOF mechanical system, a pendulum driven by a DC motor in a computed torque control, is investigated via simulation. The necessary torque is calculated from a formal primitive mechanical model and an adaptivity rule. For adaptivity real number scaling and the generalized Lorentz group elements are used. It is concluded that a single adaptive loop can compensate for the mechanical and the electrical uncertainties simultaneously.

关键词： Adaptive control Mechanical systems Uncertainty Convergence Robotics and automation DC motors Robots computer science Production engineering Neural networks

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Fuzzy Adaptive Output Tracking Control of a Class of Composite Systems

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IFAC Proceedings Volumes 2001年第3期34卷 81-84页

作者： Bin Liu Yuanwei Jing Siying Zhang G.M. Dimirovski T.D. Kolemishevska Inst. of Control Science School of Information Science & Engg. Northeastern University Po. Box 321 Shenyang Liaoning 110006 P R. of China Department of Computer Engineering Faculty of Engineering DOGUS University Acibadem Kadikoy TR-81000 Istanbul Rep. of Turkey FAX#: + 90-216-327-9631 Inst.of Automation & Systems Engg. Faculty of EE SS Cyril #x0026 Methodius University Karpos 2 b.b. MK-91000 Skopje Rep. of Macedonia

In this paper the output-tracking problem of a class of composite nonlinear systems is studied. Composite system can be represented solely by models on the grounds of its inputs and measurable outputs. It is assumed that (i) the plant system belongs to aclass of composite non linear systems, and that the fuzzy logic control system applied can efficiently use adjustable parameters to approximate its non linear system function. The new theorem guarantees the synthesized indirect fuzzy adaptive control does ensure stable output tracking and possesses the ability to reduce the number of fuzzy rules.

关键词： Adaptive control composite systems fuzzy control MIMO systems nonlinear systems

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Optimal Pricing Strategies Based on Time Delay in Multi-Service Networks

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IFAC Proceedings Volumes 2001年第3期34卷 105-110页

作者： Fude Jin Yuanwei Jing Zhianhua Zhou G.M. Dimirovske K. Sohraby Institute of Control Science School of Information Science & Engineering Northeastern University Shenyang Liaoning 110006 P.R. of CHINA +86-24/2389-3138 Inst. of Automation & Systems Engg. Faculty of EE SSs. Cyril & Methodius University Karpos 2 B.B. P.D.Box 574:MK-1000 Skopje Rep.of Macedonia Fax# +90-216/327-9631 Dept. of Computer Science & Telecommunications University of Missouri-Kansas Kansas City M064110 USA

The problem of the pricing equilibrium in multi-service priority-based networks isstudied by using Stackelberg game theory. Some concepts of the game theory were revisited first. Then, the existing results on two-user, twolevel Nash problem was reviewed briefly. Following this background, a new one-leader, two-level, two-user incentive Stackelberg strategy was derived and proved by employing the time delay involved.

关键词： Communication networks game theory incentives optimal systems priority Stackelberg game

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Regularization and validation of neural network models of nonlinear systems

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e & i Elektrotechnik und Informationstechnik 2000年第1期117卷 24-31页

作者： I. Petrović M. Baotić N. Perić Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation University of Zagreb Zagreb Croatia

A characteristic feature of the neural network models is the large number of parameters. A model offering many parameters usually gives rise to problems, and the variance contribution to the modeling error might be very high. Therefore, it is crucial to find the model with the optimal number of parameters. In this paper two techniques of selection of the optimal number of model parameters are described and compared: explicit and implicit regularization techniques. Model validation forms the final stage of an identification procedure with the aim of assessing objectively whether the identified model agrees sufficiently well with the observed data. In this paper the reliability of the correlation-based validation tests and the χ2-test is analyzed.

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Adaptive Neuro Controller for a Precise Maneouvring of Underwater Vehicle

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IFAC Proceedings Volumes 2000年第21期33卷 173-178页

作者： Zoran Vukić Bruno Borović Boris Tovornik Department of Control and Computer Engineering in Automation University of Zagreb Control Engineering Department Brodarski institute d.o.o. Institute of Automation University of Maribor Faculty of Electrical Engineering and Computer Science

A neuro controller for high precision manoeuvring of underwater vehicles require special attention to a number of factors including thruster and vehicle’s nonlinearities, couplings which exist between various degrees of freedom as well as effects of the sea currents. The neuro control system for underwater vehicle maneouvring described here is based on the conventional controller supported with the so called adaptive neural network.

关键词： neural networks underwater vehicle trajectory guidance

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Evaluating intelligence: a computational semiotics perspective

Evaluating intelligence: a computational semiotics perspecti...

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IEEE International Conference on Systems, Man and Cybernetics

作者： R.R. Gudwin Department of Computer Engineering and Industrial Automation Faculty of Electrical and Computer Engineering State University of Campinas Brazil

This paper discusses methods for evaluating the intelligence of intelligent systems by means of computational semiotics. Instead of looking at the system as a black box and testing its behavior, the process described focuses on architectural details of structures, organizations, processes and algorithms used in the construction of the intelligent system, evaluating the impact of using these elements in the overall intelligent behavior exhibited by the system. It proposes "insider" metrics that, coupled to "outsider" metrics, will be important for the determination of general metrics for intelligence in intelligent systems.

关键词： Computational intelligence Intelligent systems Intelligent structures Intelligent actuators System testing Algorithm design and analysis computer industry automation Application software Decision making

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Pole Placement Controller Design Based on Fuzzy Process Model

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IFAC Proceedings Volumes 2000年第28期33卷 219-224页

作者： Robert Cupec Nedjeljko Perić Ivan Petrović Department of Control and Computer Engineering in Automation Faculty of Electrical Engineering and Computing university of Zagreb Unska 3 10000 Zagreb Croatia

An explicit self-tuning controller based on the Takagi-Sugeno fuzzy model of the process is proposed. The fuzzy model is represented as a linear regression model whose parameters are functions of some of the process variables. Such a model can be considered as a linear time-varying model whose parameter values are known at every moment. The pole placement design procedure modified for time-varying systems is applied to obtain the polynomial controller parameters that provide the desired closed-loop poles. The proposed algorithm is very simple, and thus suitable for on-line controller design in adaptive control systems.

关键词： fuzzy control fuzzy modeling adaptive control

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A Knowledge-Base Generating Fuzzy-Neural Controller

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IFAC Proceedings Volumes 2000年第28期33卷 207-212页

作者： Ivan Petrović Kristijan Maček Nedjeljko Perić Department of Control and Computer Engineering in Automation Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 10000 Zagreb Croatia

This paper presents a modification to the Kandadai and Tien’s learning algorithm for tuning a fuzzy-neural controller that is able to automatically generate a knowledge base. Tuning is based on reinforcements from a dynamical system, thus giving a pseudosupervised learning scheme using error backpropagation. Originally, a weak reinforcement in the form of a binary failure signal was assumed which proved to be insufficient in terms of steady-state error. Therefore, a continuous reinforcement signal is applied enabling the system to correct the error as well as decreasing the overall control effort in the learning phase.

关键词： expert systems intelligent control fuzzy logic neural networks

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Model structure selection for nonlinear system identification using feedforward neural networks

Model structure selection for nonlinear system identificatio...

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International Joint Conference on Neural Networks (IJCNN)

作者： I. Petrovic M. Baotic N. Peric Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation University of Zagreb Zagreb Croatia

The majority of nonlinear models based on neural networks are of the black-box structure. A nonlinear system can be nonlinear in many different ways, thus the nonlinear black-box model structure must be very flexible. This means that it must have many parameters. A model offering many parameters usually creates problems, and the variance contribution to the error might be high. For a particular identification problem, only a subset of the parameters may be necessary, and the main topic in nonlinear system identification is how to select a model structure that describes the system dynamics with the minimum number of parameters. This paper discusses nonlinear input-output models that are suitable for implementation of feedforward neural networks. The proposed model structures were tested and compared using the identification procedure of a pH process. The results indicated that a simplest model structure can satisfactorily represent the investigated process.

关键词： Nonlinear systems Neural networks Feedforward neural networks Nonlinear dynamical systems Control engineering computing computer networks Predictive models Automatic control Nonlinear control systems automation

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