• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.613-620
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• 2013

A new remote control algorithm for a mobile robot is proposed, where a remote controller consists of a camera and inertial sensors. Initially the relative position and orientation of a robot is estimated by capturing four circle landmarks on the plate of the robot. When the remote controller moves to point to the destination, the camera pointing trajectory is estimated using an inertial navigation algorithm. The destination is transmitted wirelessly to the robot and then the robot is controlled to move to the destination. A quick movement of the remote controller is possible since the destination is estimated using inertial sensors. Also unlike the vision only control, the robot can be out of camera's range of view.

• Journal of Mechanical Science and Technology
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• v.14 no.5
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• pp.508-517
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• 2000

For shift quality improvement, torque sensors are currently too expensive to be used on production vehicles. To achieve smooth acceleration shift, the reference trajectory of the clutch slip speed for accomplishing the shift process within a designated shift completion time and its relationship with the clutch actuating torque were suggested by Jeong and Lee (1999). In order to facilitate the proposed algorithm, nonlinear estimators for necessary information such as the axle shaft torque, clutch friction and turbine torque were designed using only speed sensors. Accounting for the modeling error, a control law for this indirect smooth shift was proposed based on the above mentioned suggestions. Simulation results of the proposed estimators and shift controller were presented and further considerations for practical applications are discussed.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.384-387
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• 1998

This paper presents a newly developed speed sensorless drive using RLS(Recursive Least Squares) based on Neural Network Training Algorithm. The proposed algorithm based on the RLS has just the time-varying learning rate, while the well-known back-propagation (or generalized delta rule) algorithm based on gradient descent has a constant learning rate. The number of iterations required by the new algorithm to converge is less than that of the back-propagation algorithm. The RLS based on NN is used to adjust the motor speed so that the neural model output follows the desired trajectory. This mechanism forces the estimated speed to follow precisely the actual motor speed. In this paper, a flux estimation strategy using filter concept is discussed. The theoretical analysis and experimental results to verify the effectiveness of the proposed analysis and the proposed control strategy are described.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.4-4
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• 2000

In this paper, the backstepping control method that is useful for cascade systems is applied to the slew maneuver of the spacecraft. The quaternion is used for representing the attitude of the spacecraft, because the reference trajectory of angular velocity has simple mathematical form. The conventional backstepping control has severa] problems such as slow convergence, trivial cancelling of nonlinear terms, and excessive control input. To overcome these problems, the modified backstepping control method which is redesign of Lyapunov function is proposed. To design a tracking function for angular velocity, it is necessary to estimate the process of maximum angular velocity, and therefore the estimation procedure using Bellman-Gronwall inequality is developed. To verify the effectiveness of the proposed control law, numerical simulation is performed and the results are compared with the exiting control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.244-244
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• 2000

We proposed the above-knee prosthesis using rotary MR damper in which knee joint is semi-actively controlled by microprocessor. Dissipation torque in the knee joint can be controlled by the magnetic field which is induced by applying current to a solenoid, Tracking control of knee joint angle was tested by 3-DOF Leg simulator. The experimental results show that the proposed above-knee prosthesis system had good performance in swing phase tracking and repetitive controller in conjunction with a computed control law and PD control law, reduced RMS tracking error as the repetitions of tracking. Moreover, desired knee angle trajectory was generated based on the estimation of gait period with the gyro signal and the tracking control was performed.

• ETRI Journal
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• v.28 no.2
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• pp.131-144
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• 2006

This work demonstrates a dead-reckoning (DR) scheme for a low-cost land navigation system and a DR/GPS system design using the sigma point Kalman filter (SPKF). T hrough an observability analysis and some simulations, it is shown that the performances of a stand-alone DR system and DR/GPS system can be improved by employing the proposed DR scheme and SPKF. By using the designed DR scheme and filter, the stand-alone DR system does not have any undetectable errors occurring on the curve trajectory. And the DR/GPS system can provide a stable and seamless navigational solution even in the case where the initial heading estimation error is large, such as 160 degrees, or when the GPS signal is unavailable due to tunnels, buildings, and so on. Simulation results indicate a satisfactory performance of the proposed system.

• Proceedings of the KIEE Conference
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• summer
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• pp.1334-1336
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• 2004

The existing problems of the Electro-Magnetic Suspension system such as air-gap disturbance, mass variation and actuator/sensor failure are described in amore specific manner. These problem can not be solved by conventional state-feedback and output-feedback control. Extended Kalman Filter is to linearize about a trajectory that is continually updated with the state estimates resulting from the measurements. In this paper, first, the physical properties of the EMS system are described. second, Extended Kalman Filer designed as form appliable EMS system. It is shown that state estimation performance can be obtained with the use of Extended Kalman filter, and that results from simulation, stability analyze.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1037-1041
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• 1996

Input-output linearization technique in nonlinear control does not guarantee the robustness in the presence of parameter uncertainty or unmodeled dynamics, etc. However, it has been used as an important preliminary step in achieving additional control objectives, for instance, robustness to parameter uncertainty and disturbance attenuation. An indirect adaptive control scheme based on input-output linearization is proposed in this paper. The scheme consists of a Hopfield network for process parameter identification and an adaptive sliding mode controller based on input-output linearization, which steers the system response into a desired configuration. A numerical example is presented for the trajectory tracking of uncertain nonlinear dynamic systems with slowly time-varying parameters.

• International Journal of Aeronautical and Space Sciences
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• v.3 no.1
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• pp.39-49
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• 2002

This paper presents a robust tracker design method that is specific to the trajectories of target aircraft. This method assumes that representative trajectories of the target aircraft are available. The exact trajectories known to the tracker enables the incorporation of the exact data in the tracker design instead of the measurement data. An estimator is designed to have acceptable performance in tracking a finite number of different target trajectories with a capability to trade off the mean and maximum errors between the exact trajectories and the estimated or predicted trajectories. Constant estimator gains that minimize the cost functions related to the estimation or prediction error are computed off-line from an iterative algorithm. This tracker design method is applied to the longitudinal motion tracking of target aircraft.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.1
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• pp.75-81
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• 2019

This study presents an automatic collision avoidance algorithm for autonomous navigation of unmanned surface vessels. The performance of the collision avoidance algorithm is heavily dependent on the estimation quality of the course and speed of traffic ships because collision avoidance maneuvers should be determined based on the predicted motions of the traffic ships and their trajectory uncertainties. In this study, the collision avoidance algorithm is implemented based on the Probabilistic Velocity Obstacle (PVO) approach considering the maritime collision regulations (COLREGs). In order to demonstrate the performance of the proposed algorithm, an extensive set of simulations was conducted and the results are discussed.