• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.2
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• pp.157-163
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• 2014

In this paper, a robust MRAC (model reference adaptive control) scheme is applied to control an electrohydraulic positioning system under various loads. The inverse dead-zone compensator in the control system cancels out the dead-zone response, and an integrator added to the controller provides good position-tracking ability. LQG/LTR (linear quadratic Gaussian control with loop transfer recovery) closed-loop model is used as the reference model for learning the MRAC system. LQG/LTR provides a systematic technique to design the linear controller that optimizes the objective function using some compromise between the control effort and the system performance in the frequency domain. Different external load tests are performed to investigate the effectiveness of the designed MRAC system in real time. The experimental results show that the tracking performance of the proposed system is highly accurate, which offers considerable robustness even with a large change in the load.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.807-814
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• 2014

In this paper, we proposed a haptic navigation system which used the tactile data for the user guides of the mobile robot to the reference point via tele-operation in unknown blind environment. This navigation system can enable a mobile robot to avoid obstacles and move to the reference point, according to the direction provided by the device guides through a haptic device consisting of a vibration motor in a blind environment. There are a great deal of obstacles in real environments, and so mobile robots can avoid obstacles by recognizing the exact position of each obstacle through the superposition of an ultrasonic sensor. The navigation system determines the direction of obstacle avoidance through an avoidance algorithm that uses virtual impedance, and lets users know the position of obstacles and the direction of the avoidance through the haptic device consisting of 5 vibration motors. By letting users know intuitionally, it lets the mobile robot precisely reach the reference point in unknown blind environment. This haptic device can implement a haptic navigation system through the tactile sensor data.

• Journal of Power Electronics
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• v.16 no.2
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• pp.564-571
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• 2016

This study proposes an adaptive neuro-fuzzy inference system (ANFIS)-based rotor position controller for brushless direct current (BLDC) motors to improve the control performance of the drive under transient and steady-state conditions. The dynamic response of a BLDC motor to the proposed ANFIS controller is considered as standard reference input. The effectiveness of the proposed controller is compared with that of the proportional integral derivative (PID) controller and fuzzy PID controller. The proposed controller solves the problem of nonlinearities and uncertainties caused by the reference input changes of BLDC motors and guarantees a fast and accurate dynamic response with an outstanding steady-state performance. Furthermore, the ANFIS controller provides low torque ripples and high starting torque. The detailed study includes a MATLAB-based simulation and an experimental prototype to illustrate the feasibility of the proposed topology.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.4
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• pp.161-167
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• 2001

Camera calibration is very important problem in 3D measurement using vision system. In this paper is proposed the simple method for camera calibration. It is designed that uses the principle of vanishing points and the concept of corresponding points extracted from the parallel line pairs. Conventional methods are necessary for 4 reference points in one frame. But we proposed has need for only 2 reference points to estimate vanishing points. It has to calculate camera parameters, focal length, camera attitude and position. Our experiment shows the validity and the usability from the result that absolute error of attitude and position is in $10^{-2}$.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.3
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• pp.124-130
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• 1999

Speed and position sensors require the additional mounting space, reduce the reliability in harsh environments and increase the cost of motor. Various control algorithms have been proposed for the elimination of speed senor. This paper investigates a novel speed sensorless control of induction motor. The proposed control strategy is based on MRAS(Model Reference Adaptive System) using state observer as a reference model for flux estimation. This algorithm may overcome several shortages of conventional MRAS: integrator problems, small EMF at low speed and relatively large sensitivity to resistance variation. The proposed algorithm is verified through simulation and experiment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.43-48
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• 2010

This article presents the experimental studies of controlling angle and position of the inverted pendulum system using neural network to compensate for errors caused due to fuzzy controller. Although fuzzy control method can deal with nonlinearities of the system, fixed fuzzy rules may not work and result in tracking errors in some cases. First, a nominal Takagi-Sugeno (TS) type fuzzy controller with fixed weights is used for controlling the inverted pendulum system. Then the neural network is added at the reference input to form the reference compensation technique (RCT)control structure. Neural network modifies the input trajectories to improve system performances by updating internal weights in on-line fashion. The back-propagation learning algorithm for neural network is derived and used to update weights. Control hardware of a DSP 6713 board to have real time control is implemented. Experimental results of controlling inverted pendulum system are conducted and performances are compared.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.930-935
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• 2005

In this paper, position tracking control of an autonomous helicopter is presented. Combining an LQR method and a proportional control forms a simple PD control. Since LQR control gains are set for the velocity control of the helicopter, a position tracking error occurs. To minimize a position tracking error, neural network is introduced. Specially, in the frame of the reference compensation technique for teaming neural network compensator, a position tracking error of an autonomous helicopter can be compensated by neural network installed in the remotely located ground station. Considering time delay between an auto-helicopter and the ground station, simulation studies have been conducted. Simulation results show that the LQR with neural network performs better than that of LQR itself.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.1
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• pp.49-59
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• 2011

Recently, ToA and TDoA estimation are favorable among all of estimation techniques because they have the best accuracy in estimating position. ToA and TDoA estimation are typical techniques based on time. So, it is important to have the time syncronization and offset between a target node and several reference nodes. If they don't have the time syncronization between a reference node and target node or have a time offset among reference nodes, the positioning error will increase due to the ranging error. The conventional positioning algorithm does not have a accurate device's position because ranging error is added the calc dation of the position. In this paper, we propose a hybrid method of ToA and TDoA ll increase due. We use MHP pulse that has orthogonal pulse instead of the existing pulse to transmit and receive pulses between a target node and reference nodes. We can estimate the target node's position by ToA and TDoA estimation to transmit and receive MHP pulses only once. When the proposed Hybrid method iteratively calculate the distance, we can select the ranging technique to have more accurate position. The simulation results confirm the enhancement of the Hybrid method.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.1
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• pp.71-80
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• 2009

The response characteristics of EHA systems are sensitive to the temperature change of working fluid because the temperature of working fluid causes the variation of system parameters such as effective bulk modulus and viscous friction coefficient. In this paper, a precise position control of EHA system using the adaptive sliding mode control system is suggested. The adapted system parameters such as effective bulk modulus and viscous friction coefficient can be used for monitoring failures in the EHA system which has potential applications in the industrial fields. Not only the accuracy of adapted system parameters but also the improved performance and robustness in a given reference position of the cylinder are verified by computer simulation using AMESim software.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.994-1000
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• 2003

A new relative motion control methodology for a following system to an independent leading system is proposed for controlling relative position, velocity, and tension etc. It is based on maintaining minimum relative error between two independent systems. The control command of the following system to a leading system is generated by adding the current command and the output of the relative error compensation. The proposed control method is implemented on the experimental equipment which is a wire winding-unwinding system to control the tension of the line. The results show the unwinding system(follower) following the independent motion of the winding system(leader) to control the constant tension of the line in order to keep the roller dancer in reference position. The relative motion control method proposed in this paper can be applied to high precision equipment for unwinding and winding fine wire, fine fiber, and tape etc.