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International Conference on Neural Networks

作者： Il Hong Suh Jae-Hyun Kim F.C.-H. Rhee Intelligent Control and Robotics Laboratory Department of Electronic Engineering Hanyang University Ansan South Korea Computational Vision and Fuzzy Systems Laboratory Hanyang University Ansan South Korea

It is desirable for autonomous robot systems to posses the ability to behave in a smooth and continuous fashion when interacting with an unknown environment. Since Q-learning is normally used for optimizing a series of discrete actions, it may be undesirable when applied to a real environment which involves continuous states and actions. In this paper, we propose a new method of Q-learning that incorporates a fuzzy interpolation technique which is used to approximate a continuous state. Our learning method can estimate current state by its neighboring states and has the ability to learn its actions similar to that of Q-learning. Thus, our method can enable robots to react smoothly in a real environment. Simulation results involving an autonomous robot are given to show the validity of our method.

关键词： Robot sensing systems control systems Laboratories Interpolation State estimation intelligent robots Learning Robot control Robot vision systems Machine vision

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Fuzzy modeling and control of a nonlinear magnetic bearing system

Fuzzy modeling and control of a nonlinear magnetic bearing s...

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IEEE Conference on control Technology and Applications (CCTA)

作者： Sung-Kyung Hong R. Langari Joongseon Joh Department of Mechanical Engineering and Center for Fuzzy Logic Roboticsand Intelligent Systems Research Texas A and M University College Station TX USA Department of Control and Instrumentation engineering Changwon NatE28099l University South Korea

This paper presents an approach, called fuzzy model based nonlinear fuzzy control, that overcomes position dependent nonlinearity of magnetic bearing systems. We represent the nonlinear magnetic bearing by the Takagi-Sugeno-Kang fuzzy model. Based on such model, nonlinear fuzzy controllers can be derived by means of a systematic synthesis approach. Moreover, the stability analysis of the fuzzy control system can be done efficiently by using linear matrix inequality method. Simulation results demonstrate that the proposed fuzzy controller yields not only maximized stability boundary but also better performance than a single operating point linear controller.

关键词： Fuzzy control Fuzzy systems Nonlinear control systems Magnetic levitation Fuzzy logic control systems Nonlinear dynamical systems Nonlinear magnetics Rotors Magnetic forces

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Design of a supervisory control system for multiple robotic systems

Design of a supervisory control system for multiple robotic ...

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IEEE International Workshop on intelligent Robots and systems (IROS)

作者： I.H. Suh H.J. Yeo J.H. Kim J.S. Ryoo S.R. Oh C.W. Lee B.H. Lee Intelligent Control and Robotics Laboratory Department of Electronics Engineering Hanyang University Ansan Kyunggi South Korea Advanced Robotics Research Center KIST Seoul South Korea Department of Control and Instrumentation Engineering Seoul National University South Korea

This paper presents a design experience of a supervisory control system for coordination of multiple robotic devices. To effectively program job commands, a Petri net-type graphical robot language(PGRL) is proposed, where some functions for coordination among tasks such as concurrency and synchronization, can be easily programmed. Each task of PGRL is described by employing formal model languages, which are composed of three modules, sensory, data handling, and action module. It is expected that by using our proposed PGRL and formal model languages, one can efficiently describe a job or task, and hence can easily operate a complex real-time concurrent system. The proposed control system has been implemented by using VME-based 32-bit microprocessor boards and a real-time multitasking operating system (VxWorks), and is shown to successfully work for robotic jobs.

关键词： Supervisory control Robot kinematics Robot sensing systems Real time systems Concurrent computing Data handling control systems Microprocessors Multitasking Operating systems

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An intelligent coordinated control system for steering and traction of electric vehicles

An intelligent coordinated control system for steering and t...

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International Conference on Industrial Electronics, control and instrumentation

作者： M.K. Park I.H. Suh S.J. Byoun S.R. Oh Intelligent Control and Robotics Laboratory Department of Electronics Engineering Hanyang University Seoul South Korea Department of Control and Instrumentation Engineering Dong Yang University Youngju South Korea Division of Electronics Information Technology India

An intelligent coordinated control system is designed for the active steering and the left/right traction force distribution control of 2-wheel-drive and 2-wheel-steering (2WD/2WS) electric vehicles, where input-output linearization is employed. Also, a fuzzy-rule-based cornering force estimator is suggested to avoid using an uncertain highly nonlinear expression, and a neural network compensator is additionally utilized for the estimator to correctly find cornering force. With these techniques, the proposed control system is shown by simulation results to be robust against drastic change of the external environments such as road conditions.

关键词： intelligent systems intelligent control control systems Force control intelligent vehicles Electric vehicles Neural networks control system synthesis Robust control Roads

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Measuring the distance and orientation of a planar surface using nonstructured lighting

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systems AND COMPUTERS IN JAPAN 1996年第8期27卷 83-92页

作者： Tsukiyama, T Member Electrotechnical Laboratory Tsukuba Japan 305 Tosbifumi Tsukiyama:graduated in 1972 from the Biological Engineering Department Osaka University where he also received his Dr. of Eng. degree. He joined Electrotechnical Laboratory Ministry of Tread and Industry (Japan) in 1972. At present he is Senior Researcher at Computer Vision Section Intelligent Systems Division ETL. He was a Visiting Researcher at University of Illinois during 1984–1985. He has been interested in vision system for mobile robots and image processing architectures. He is a member of the Society of Instrumental and Control Engineers Japan Robotics Society of Japan and Information Processing Society of Japan.

This paper proposes a method of 3-dimensional measurement of a planar surface by using two fixed light sources and a TV camera. A set of two images is recorded by the camera switching on each light alternately. The peak of the luminance distribution in each image is detected, and the orientation and distance of the planar surface are calculated. The position of the peak of a luminance distribution can be estimated accurately by using an image processing. The light sources can be conventional apparatus with no particular structure. The method is simple and suitable for a vision system on an indoor mobile robot.

关键词： distance to surface orientation of planar surface point light source luminance distribution ring light

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Explicit fuzzy force control of industrial manipulators with position servo drives

Explicit fuzzy force control of industrial manipulators with...

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IEEE International Workshop on intelligent Robots and systems (IROS)

作者： I.H. Suh K.S. Eom H.J. Yeo B.H. Kang S.-R. Oh B.H. Lee Intelligent Control and Robotics Laboratory Department of Electrvnics Engineering Hanyang University South Korea Samsung Data System Company Limited South Korea Division of Electronics and Infonmation technology KIST Seoul South Korea Robotics and Intelligent Systems Laboratory Department of Control and Instrumentation Engineering Seoul National University South Korea

In this paper, a fuzzy force control algorithm is suggested for commercialized industrial robots equipped with the position servo drives, where control rules of the proposed fuzzy controller are changed according to the magnitude of environmental stiffness in such a way that good force response is maintained regardless of changes of environmental stiffness. Specifically, some fuzzy control rules are designed for several representative environmental stiffness values, and then a control action for a given arbitrary environmental stiffness value is decided by a fuzzy interpolation method. To show the validity of the proposed fuzzy controller, several experimental results are illustrated, where a 5-axis articulated robot manipulator equipped with the wrist force/torque sensor system and our prototype dual robot controller are employed.< >

关键词： Fuzzy control Force control Industrial control Manipulators Torque control control systems Robot sensing systems Commercialization Service robots Servomechanisms

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A KNOWLEDGE-BASED APPROACH TO MODELING OF ROBOTIC ASSEMBLY CELLS

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ROBOTICA 1991年第1期9卷 31-42页

作者： KIM, DW LEE, BH KO, MS Robotics and Intelligent Systems Laboratory Department of Control and Instrumentation Engineering Seoul National University Seoul 151–742 (Korea)

In this paper, an approach to modelling of a robotic assembly cell is proposed and a method for managing the cell operation is described using a knowledge base. Since the modelling structure is based on the concept of the state variable, the relationships between states are described by the state transition map (STM). The knowledge-bases for state transition and assembly job information are obtained from the STM and the assembly job tree (AJT), respectively. Using the knowledge-base, the system structure is discussed in relation to both managing the cell operation and evaluating the performances. Finally, a simulation algorithm is presented with the simulation results to show the significance of the proposed modelling approach.

关键词： MODELING ASSEMBLY CELLS robotics KNOWLEDGE-BASE STATE TRANSITION

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An adaptive learning control approach

An adaptive learning control approach

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IEEE Conference on Decision and control

作者： Z. Geng M. Jamshidi R. Carroll R. Kisner Intelligent Automation Inc. Rockville MD USA CAD Laboratory of Robotics University of New Mexico Albuquerque NM USA Department of Electrical Engineering George Washington University DC USA Control & Instrumentation Division Oak Ridge National Laboratory Oak Ridge TN USA

An adaptive learning control approach is proposed which combines a mechanism to improve the control input sequence as well as to improve the learning control scheme based on the knowledge learned about the unknown system and environment. The iterative learning control problem is treated from the 2D system point of view. A 2D model for a class of iterative learning control system is formulated. A learning gain estimator algorithm based on the 2D model is presented. The overall learning control system structure is given. The proposed learning control scheme does not require prior knowledge of the controlled system and has the ability to generalize the knowledge learned from one task operation to other tasks. This scheme can be applied to nonlinear system control problems. To demonstrate the feasibility of the proposed learning algorithm, simulation results on learning control for a three-water-tank system are given. The results show an excellent learning performance, even for nonrepetitive tasks.< >

关键词： Programmable control Adaptive control control systems Nonlinear control systems Error correction control system synthesis Automatic control robotics and automation Iterative algorithms Three-term control

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A learning control scheme with gain estimator

A learning control scheme with gain estimator

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IEEE International Symposium on intelligent control (ISIC)

作者： Z. Geng M. Jamshidi R. Carroll R. Kisner Intelligent Automation Inc. Rockville MD USA CAD Laboratory of Robotics University of New Mexico Albuquerque NM USA Department of Electrical Engineering George Washington University Washington D.C. DC USA Control and Instrumentation Division Oak Ridge National Laboratory Oak Ridge TN USA

An adaptive learning control approach is proposed that combines a mechanism to improve control input sequence as well as to improve the learning control scheme based on the knowledge learned about unknown system and environment. First, the iterative learning control problem is treated from the 2-D system point of view. A 2-D model for a class of iterative learning control systems is formulated. Then a learning gain estimator algorithm based on the 2-D model is presented. The overall learning control system structure is given.< >

关键词： control systems Automatic control Three-term control Inverse problems intelligent robots robotics and automation Service robots Laboratories Electrical equipment industry Industrial control

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control of induction motors for high dynamic performance and maximal power efficiency via feedback linearization with input-output decoupling

Control of induction motors for high dynamic performance and...

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Annual Conference of Industrial Electronics Society

作者： Dong-Il Kim In-Joong Ha Myoung-Sam Ko Jae-Wha Park Robotics and Intelligent Systems Laboratory Department of Control and Instrumentation Eng. Seoul National University South Korea

The authors attempt to achieve both high dynamic performance and maximal power efficiency for induction motors by means of linear decoupling of rotor speed (or motor torque) and rotor flux. The induction motor with the proposed controller possesses the input-output dynamic characteristics of a linear system such that the rotor speed (or motor torque) and the rotor flux are decoupled. The rotor speed (or motor torque) responses are not affected by abrupt changes in the rotor flux, and vice versa. The rotor flux need not be measured but is estimated by the well-known flux simulator. The effect of large variation in the rotor resistance on the control performances is minimized by using a parameter adaptation method. The authors present simulation and experimental results as well as mathematical performance analyses.< >

关键词： Induction motors Feedback Rotors DC motors Linear systems Equations control systems Torque Electrical resistance measurement Performance analysis

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