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A Fuzzy Adaptive - Predictive Scheme for the Decentralized Control of a Class of Interconnected Systems

IFAC Proceedings Volumes 1998年第20期31卷 1097-1102页

作者： Spyros Tzafestas Efthimios Kyriannakis George Apostolikas Intelligent Robotics and Automation Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Zographou 15773 Athens Greece.

This paper proposes an approach for the design of discrete-time decentralized control systems with m-step delay sharing information pattern, employing the modelbased predictive control (MBPC) scheme combined with fuzzy prediction for the interconnections among the subsystems. A state-space model is used at each control station to predict the corresponding subsystem output over a long-range time period. The interaction trajectories are considered to be non-linear functions of the states of the subsystems. For all cases the interconnections and the necessary predictions for them are estimated by an appropriate adaptive fuzzy identifier based on the generation of linguistic IF-THEN rules and the on-line construction of a common fuzzy rule base. Representative computer simulation results are provided and compared for nontrivial example systems.

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A neural network approach to real-time trajectory generation [mobile robots]

A neural network approach to real-time trajectory generation...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Max Meng Xianyi Yang ART Advanced Robotics & Teleoperation Laboratory Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

ISBN: (纸本)078034300X

A neural network approach is proposed for real-time collision free trajectory generation in an environment with varying obstacles and moving target. This biologically inspired neural network is topologically organised. The dynamics of each neuron is characterised by a shunting equation or an additive equation. Each neuron has only local connections, and the optimal trajectories are generated without any explicitly optimising cost functions and without learning. Therefore the model is computationally efficient. The stability of the network is analytically proved using a Lyapunov function candidate. As examples, the proposed neural network is applied to trajectory formation for a mobile robot in solving maze-type problems, dynamically tracking moving target, and avoiding varying obstacles. The efficiency of the proposed approach is demonstrated through simulation and comparison studies.

关键词： Neural networks Trajectory Neurons Equations Cost function Biological system modeling Computational modeling Biology computing Stability analysis Lyapunov method

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A neural network approach to real-time path planning with safety consideration

A neural network approach to real-time path planning with sa...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Xianyi Yang M. Meng ART Advanced Robotics & Teleoperation Laboratory Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

In this paper, a neural network approach is proposed for real-time path planning of robots with safety consideration. The neural network is topologically organised, which is based on a previous biologically inspired model for dynamical trajectory generation of a mobile robot in a nonstationary environment. The state space of the neural network can be the joint space of multilink robot manipulators or the Cartesian workspace. This model is capable of dealing with multiple target problems as well. The target globally attracts the robot, while the obstacles push the robot away locally to avoid collisions. By taking into account of the clearance from obstacles, the planned "comfortable" path does not suffer either the "too close" or the "too far" problems. Each neuron has only local lateral connections. The optimal path is generated in real-time through the dynamics of the neural activity landscape without explicitly optimising any cost function. Therefore, it is computationally efficient. The stability of the network is guaranteed by the existence of a Lyapunov function. The effectiveness and efficiency are demonstrated through simulation studies.

关键词： Neural networks Path planning Safety Orbital robotics Biological system modeling Mobile robots State-space methods Manipulator dynamics Neurons Cost function

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An Efficient PC-Based Environment for Power System Studies - Application to the Restoration Problem

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IFAC Proceedings Volumes 1998年第20期31卷 659-664页

作者： N.A. Fountas N.D. Hatziargyriou K.P. Valavanis Electric Energy Systems Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Greece Robotics and Automation Laboratory The Center for ACS The University of Southwestern Louisiana Lafayette

Advanced powerful tools are sought for in order to conduct power system studies, especially for large scale systems. In this paper, an efficient PC-based environment for power system studies is presented. It is based on both analytical and artificial intelligence techniques. To demonstrate its effectiveness, this environment has been used for restoration studies following a recent blackout in the Hellenic power system, with very promising results.

关键词： computer environment analytic approximations Timed Petri-nets Power system

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New generation of multirobot systems

New generation of multirobot systems

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IEEE International Conference on Systems, Man and Cybernetics

作者： M.M. Trivedi K.C. Ng N. Lassiter R. Capella Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of California San Diego La Jolla CA USA

This paper presents a summary of a comprehensive research project involving development of a completely autonomous multirobot system for railway track maintenance applications. The specifications of this "real-world" application required us to consider a multirobot system conceptualization, rather than a single robot system.

关键词： Multirobot systems Rail transportation Robot sensing systems robotics and automation Sensor arrays Fasteners computer vision Application software Sensor systems Intelligent robots

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An Overview and Critical Issues for Research and Education of Intelligent Manufacturing Systems

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IFAC Proceedings Volumes 1998年第15期31卷 679-687页

作者： Peter P. Groumpos Laboratory for Automation and Robotics Department of Electrical and Computer Engineering University of Patras Rion 26500 GREECE Tel. +3061 997295 Fax. +3061 997309

Intelligent Manufacturing Systems is the major challenge that must be met by scientific community in order to develop the next generation sophisticated manufacturing systems. This paper presents an overview of new promising domains, such as fuzzy logic, neural networks and hybrid intelligent control systems, that could be utilised to achieve human intention for more advanced manufacturing systems. The modelling of the supervisor of manufacturing systems using fuzzy cognitive map is proposed and system functionalization architecture is presented. Finally, conclusions of an international symposium on issues and challenges of Manufacturing and Control Education for the 21 st Century are presented.

关键词： Modelling Supervisory Control Fuzzy Neural Systems Intelligent Manufacturing Systems

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Analysis of nonlinear neural network impedance force control for robot manipulators

Analysis of nonlinear neural network impedance force control...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Seul Jung T.C. Hsia Robotics and Computational Intelligence Laboratory Department of Mechatronics Engineering Chungnam National University Taejon South Korea Robotics Research Laboratory Department of Electrical and Computer Engineering University of California슠Davis Davis CA USA

A force tracking nonlinear impedance control scheme using a neural network is introduced. Due to the nonlinear characteristics of the proposed control law, stability has been analyzed. The numerical bound of environment position uncertainty for ensuring robot contact with the environment and to perform desired force tracking has been found. Intensive simulation studies with a three link rotary robot manipulator tracking the surface with a desired force are carried out to confirm the boundary solutions of the proposed scheme under no knowledge of environment surface position and environment stiffness.

关键词： Neural networks Impedance Force control Robots Manipulators Iron Orbital robotics Nonlinear equations Uncertainty Nonlinear control systems

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Algorithmic navigation to train deictic mobile robot operators

Algorithmic navigation to train deictic mobile robot operato...

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IEEE International Conference on robotics and Automation (ICRA)

作者： M.E. Cleary J.D. Crisman College of Computer Science Robotics and Vision Systems Laboratory Boston MA USA Department of Electrical and Computer Engineering Northeastern University Boston MA USA

Presents an algorithm for a simulator to train mobile robot operators in the use of deictic commands. It shows that robots can be deictically controlled in any reasonable environment. Deictic control is a technique which directs the robot by visually servoing on targets pointed out to the robot by its operator. This provides a direct, intuitive control method which any sighted operator can use. Previous work has formally defined canonical targets required for deictic control, and has described a training system for prospective users. This paper extends that work by providing a specific algorithm for the construction of deictically controlled paths. The algorithm is described in detail and results are presented. This algorithm shows that deictic commands and their targets can be simply determined by an agent able to sense the surrounding environment.

关键词： Navigation Mobile robots Robot control Automatic control Control systems Robot vision systems Machine vision Object recognition Humans robotics and automation

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Application of Fuzzy Cognitive Maps in Large Manufacturing Systems

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IFAC Proceedings Volumes 1998年第20期31卷 521-526页

作者： Chrysostomos D. Stylios Peter P. Groumpos Laboratory for Automation and Robotics Department of Electrical and Computer Engineering University of Patras Rion 26500 GREECE Tel. +30 61 997293 Fax. +30 61 997309

In this paper the application of Fuzzy Cognitive Map (FCM) in controlling a process problem and its use in modelling Supervisory Manufacturing Systems is presented. The description, construction and the mathematical model of Fuzzy Cognitive Map are examined. Then, a chemical process is modelled with FCM and its behaviour is simulated and the application of Fuzzy Cognitive Maps in the mode ling of the Supervisor of Manufacturing Systems is discussed.

关键词： Cognitive Systems Supervision Manufacturing Systems

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Dynamic fuzzy control and system stability for the Acrobot

Dynamic fuzzy control and system stability for the Acrobot

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： M.H. Smith T. Zhang W.A. Gruver Department of Electrical Engineering and Computer Science University of California Berkeley CA USA Intelligent Robotics and Manufacturing Systems Laboratory Manufacturing Systems Laboratory Simon Fraser University Burnaby Canada

This paper discusses the swing-up control of a two link robot mechanism known as the Acrobot. Previously, a technique using meta-rules was proposed to compensate for external disturbances when using a dynamic fuzzy controller. In this paper, stability of the meta-rule system is analyzed from a global asymptotic stability viewpoint based on fuzzy characteristic matrices. These matrices are generated from the first phase of a three phase learning process involving the combination of genetic algorithms, dynamic switching fuzzy systems, and meta-rule techniques with the purpose of developing a better performing fuzzy controller.

关键词： Fuzzy control Stability Fuzzy systems Automatic control Fuzzy reasoning Robot kinematics Control systems Leg PD control Genetic algorithms

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