• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.443-446
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• 2003

Conventional disturbance rejection methods have to derive the inverse model of a system. However, the inverse model of n nonholonomic system is not unique, because an inverse it changes depending on initial conditions and desired values. A kind of internal model control (IMC) using feedback error learning is discussed for the motion control of nonholonomic mobile robots in this paper, The present method is different from a conventional IMC whose control system consists of an inverse model, a direct model and a filter. The present disturbance rejection method need not use a direct model, where the remaining two elements are composed of the same inverse model based on neural networks.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.65-70
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• 2011

The increased disk rotational velocity to improve the data transfer rate has raised up many serious problems in its servo control system which should control the position and velocity of a spot relative to a rotating disk. This paper proposes gain-scheduling-based track-seek control for single stage actuator of hard disk drives. Gain scheduling is a technique that can extend the validity of the linearization approach to a range of operating points and one of the most popular approaches to nonlinear control design. The proposed method schedules controller gains to improve the transient response and minimize overshoot during the functions of the read/write head positioning servomechanism for the seek control. The validity of the proposed method is demonstrated through stability analysis and simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.31-36
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• 2005

Intelligent Space (iSpace) is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment comes to have intelligence. In iSpace, the locations of multiple humans and other objects are obtained and tracked by using multiple camera and color-based method. In addition, we describe a context-aware information system which is based on Spatial-Knowledge-Tags (SKT). SKT system enables humans to access information and data by using spatial location of human and stored information in storage. The proposed tracking method is applied to the intelligent environment and its performance is verified by the experiments.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2573-2576
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• 2003

This paper proposes the controller for biped robot using intelligent control algorithm. The main purpose of this paper is to design the robot controller using Hierarchical Mixture of Experts(HME). The neural network direct control method will be applied to the control scheme for the biped robot and neural network will learn the dynamics of biped robot. The teaming scheme using a intelligent controller to biped robot is developed. The teaming scheme uses a HME controller combined with a inverse biped robot model. The controller provides the control signals at each control time instant. Simulation results are reported for a seven-link biped robot.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.984-990
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• 2005

The aim of this paper is to investigate a control framework for mobile robots, operating in shared environment with humans. The Intelligent Space (iSpace) can sense the whole space and evaluate the situations in the space by distributing sensors. The mobile agents serve the inhabitants in the space utilizes the evaluated information by iSpace. The iSpace evaluates the situations in the space and learns the walking behavior of the inhabitants. The human intelligence manifests in the space as a behavior, as a response to the situation in the space. The iSpace learns the behavior and applies to mobile agent motion planning and control. This paper introduces the application of fuzzy-neural network to describe the obstacle avoidance behavior teamed from humans. Simulation results are introduced to demonstrate the efficiency of this method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.690-696
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• 2004

This paper is proposed a hybrid intelligent controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neural network-fuzzy(NNF) control and speed estimation using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.1
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• pp.44-49
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• 2003

This paper describes a method of estimating miniature train location by color vision for development of an intelligent railway system model. In the teal world, to control trains automatically, GPS(Global Positioning System) is indispensable to determine the location of trains. A color vision system was used for estimating the location of trains in an indoor experiment. Two different rectangular color bars were attached to the top of each train as a means of identifying them. Several trains were detected where they were located on the track by color feature, geometric features and moment invariant, and tracked simultaneously. In the experiment the identity, location and direction of each train were estimated and transferred to the control computer using serial communication. Processing speed of up to 8 frames/sec could be achieved, which was enough speed for the real-time train control.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.5
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• pp.51-59
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• 1997

In this paper, we perform the position control of a DC servo motor using fuzzy neural controller. We use the Fuzzy controller for the position control, because the Fuzzy controller is designed simpler than other intelligent controller, but it is difficult to design for the triangle membership function format. Therefore we solve the problem using the BP learning method of neural network. The proposed Fuzzy neural network controller has been applied to the position control of various virtual plants. And the DC servo motor position control using the fuzzy neural network controller is performed as a real time experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.139-143
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• 2005

As increasing gastrointestinal pathologies, general and thoracic surgeries using circular staplers have been dramatically increased. Because of convenience for surgical procedure, recently, various circular staplers for anastomosis have been used widely. Since the circular staplers conventional have used the displacement control method, however, the anastomosis could have various biomechanical conditions. To do that, biomechanical system of gastrointestinal soft tissue should be examined to control the anastomotic condition. In this study, a new intelligent robot used in circular anastomosis. The intelligent robot driven by a stepper motor and controlled by a digital signal processor.

• Structural Engineering and Mechanics
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• v.15 no.2
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• pp.239-248
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• 2003

The dynamic response analysis of closed loop control system based on probability for the intelligent truss structures with random parameters is presented. The expressions of numerical characteristics of structural dynamic response of closed loop control system are derived by means of the mode superposition method, in which the randomness of physical parameters of structural materials, geometric dimensions of active bars and passive bars, applied loads and control forces are considered simultaneously. The influences of the randomness of them on structural dynamic response are inspected by several engineering examples and some significant conclusions are obtained.