• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.584-589
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• 1988

Tuning of digital STC parameters for the system with unknown and time varying parameters as well as delays presents many preconditions and difficulties. In order to eliminate these difficulties and to enhance STC control functions, the present study employs the metbod of expert control for STC and to implement it in nod-minimum phase plants. In this paper, implimedtation of the Expert STC for process control, STC. parameters is carried out by tuning systematically and by applying these parameters to non-minimum phase plant. This controller supervises a status of the plant, and robust control function for time delay or change of the plant is demonstrated by computer simulations.

• Journal of the Korean Mathematical Society
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• v.37 no.4
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• pp.625-643
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• 2000

In this paper we formulate an optimal control problem governed by time-delay Volterra integral equations; the problem includes control constraints as well as terminal equality and inequality constraints on the terminal state variables. First, using a special type of state and control variations, we represent a relatively simple and self-contained method for deriving new necessary conditions in the form of Pontryagin minimum principle. We show that these results immediately yield classical Pontryagin necessary conditions for control processes governed by ordinary differential equations (with or without delay). Next, imposing suitable convexity conditions on the functions involved, we derive Mangasarian-type and Arrow-type sufficient optimality conditions.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.5
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• pp.609-617
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• 2013

This paper presents a near-minimum time path planning algorithm for autonomous driving. The problem of near-minimum time path planning is an optimization problem in which it is necessary to take into account not only the geometry of the circuit but also the dynamics of the vehicle. The path planning algorithm consists of a candidate path generation and a velocity optimization algorithm. The candidate path generation algorithm calculates the compromises between the shortest path and the path that allows the highest speeds to be achieved. The velocity optimization algorithm calculates the lap time of each candidate considering the vehicle driving performance and tire friction limit. By using the calculated path and velocity of each candidate, we calculate the lap times and search for a near-minimum time path. The proposed algorithm was evaluated via computer simulation using CarSim and Matlab/Simulink.

• Journal of Mechanical Science and Technology
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• v.19 no.9
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• pp.1695-1705
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• 2005

Reaction wheels and thrusters are commonly used for the satellite attitude control. Since satellites frequently need fast maneuvers, the minimum time maneuvers have been extensively studied. When the speed of attitude maneuver is restricted due to the wheel torque capacity of low level, the combinational use of wheel and thruster is considered. In this paper, minimum time optimal control performances with reaction wheels and thrusters are studied. We first identify the features of the maneuvers of the satellite with reaction wheels only. It is shown that the time-optimal maneuver for the satellite with four reaction wheels in a pyramid configuration occurs on the fashion of single axis rotation. Pseudo control logic for reaction wheels is successfully adopted for smooth and chattering-free time-optimal maneuvers. Secondly, two different thrusting logics for satellite time-optimal attitude maneuver are compared with each other: constant time-sharing thrusting logic and varying time-sharing thrusting logic. The newly suggested varying time-sharing thrusting logic is found to reduce the maneuvering time dramatically. Finally, the hybrid control with reaction wheels and thrusters are considered. The simulation results show that the simultaneous actuation of reaction wheels and thrusters with varying time-sharing logic reduces the maneuvering time enormously. Spacecraft model is Korea Multi-Purpose Satellite (KOMPSAT)-2 which is being developed in Korea as an agile maneuvering satellite.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.147-151
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• 1991

In this paper a time-optimal path planning scheme for the multiple robot manipulators will be proposed by using hopfield neural network. The time-optimal path planning, which can allow multiple robot system to perform the demanded tasks with a minimum execution time and collision avoidance, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computational burden and thus limits the on-line application. One way to avoid such a difficulty is to rearrange the problem as MTSP(Multiple Travelling Salesmen Problem) and then apply the Hopfield network technique, which can allow the parallel computation, to the minimum time problem. This paper proposes an approach for solving the time-optimal path planning of the multiple robots by using Hopfield neural network. The effectiveness of the proposed method is demonstrated by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1876-1879
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• 1997

This paper developes an efficient algorithm for the minimum distance calculation between general polyhedra(convex and/or concave). The polyhedron approximates and object using flat polygons which composed of more than three veritices. The algorithm developed in this paper basically computes minimun distance betwen two convex polygons and finds a set of polygons whcih makes a global minimum distance. The advantage of the algorithm is that the global minimum distance can be computed in any cases. But the big disadvantage is that minimum distance computing time is repidly increased with the number of polygons which used to approximate an object. This paper developes a method to eliminate unnecessary sets of polygons, and an efficinet algorithm to compute a minimum distance between two polygons in order to compensate the inherent disadvantage of the algorithm. It takes only a few times iteration to find minimum distance for msot polygons. The correctness of the algortihm are visually tested with a line which connects two points making a global minimum distance of simple convex object(box) and concave object(pipe). The algorithm can find minimum distance between two convex objects made of about 200 polygons respectively less than a second computing time.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.629-632
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• 1997

This paper presents the design method of controller which is combined Genetic Algorithms with the Generalized minimum variance self tuning controller. It is shown that the controllers adapts to changes in the system parameters with time delays and noises. The self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a polynomial parameters. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.124-126
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• 1989

Inverse kinematic problem is a crucial point for robot manipulator control. In this paper, to implement the Jacobian control technique we used the Hopfield(Tank)'s neural network. The states of neurons represent joint veocities, and the connection weights are determined from the current value of the Jacobian matrix. The network energy function is constructed so that its minimum corresponds to the minimum least square error. At each sampling time, connection weights and neuron states are updated according to current joint position. Inverse kinematic solution to the planar redundant manipulator is solved by computer simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.10a
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• pp.301-305
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• 2001

Conventionally, robot control algorithms are divided into two stages, namely, path or trajectory planning and path tracking(or path control). This division has been adopted mainly as a means of alleviating difficulties in dealing with complex, complex, coupled manipulator dynamics. The minimum-time manipulator control problem is solved for the case when the path is specified and the actuator torque limitations are known. In path planning, DP is applied to applied to find the shortest path form initial position to final position with the assumptions that there is no obstacle and that each path is straight line. In path control, the phase plane technique is applied to the minimum-time control with the assumptions that the bound on each actuator torque is a function of joint position and velocity or constant. This algorithm can be used for any manipulator that has rigid link, known dynamics equations of motion, and joint angles that can be determined at a given position on the path.

• Journal of the Korean Society of Safety
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• v.22 no.1 s.79
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• pp.36-39
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• 2007

It is important to know Minimum Ignition Energy(MIE) of flammable materials for ignition hazard of chemical processes etc.. Currently a capacitor discharge is used mainly to measure the MIE. Then, it is impossible to control actively discharge energies and discharge time because the MIE measurement uses a high voltage capacitor and fixed capacitor. However, the control of discharge energy and discharge time will be convenient if self-sustain discharge is used. In this paper, we measured the MIE by self-sustain discharge of a pulse shape to propose the new measuring method of the MIE. AS a result, ignition energies are increased gradually as discharge duration time gets longer, and discharge current grows larger. Also, an arc discharge and a glow discharge occurred during the experimental period, and the ignition by glow discharges happened when discharge duration time was $90{\mu}s$, discharge current was 8A and 1A Especially, the MIE occurred the 0.05mm and 0.08mm of the gap distance between discharge electrode in the same discharge duration time.