• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.127-130
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• 1995

Fuzzy controllers have proven to be powerful in controlling dynamic processes where mathematical models are unknown or intractable and ill-defined. The way of improving the performance of a fuzzy controller is based on making up rules, constructing membership functions, selecting a defuzzification method and adjusting input-output scaling factors. But there are many difficulties in tuning those to optimize a fuzzy controller. So, in this paper, we propose the look-up table based self-orgenizing fuzzy controller (LSOFC) which optimizes look-up values resulting from the above fuzzy processes. We use the plus-minus tuning method(PMTM), scanning the value through the processes of addition and subtraction. Simulation results demonstrate that the performance of LSOFC is far better than that of a non-tuning fuzzy controller.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1173-1177
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• 1990

Cerebellar Model Linear Associator Net(CMLAN), a kind of neuro-net based adaptive control function generator, was applied to the problem of direct inverse calibration of three and six d.o.f. POMA 560 robot. Since CMLAN autonomously maps and generalizes a desired system function via learning on the sampled input/output pair nodes, CMLAN allows no knowledge in system modeling and other error sources. The CMLAN based direct inverse calibration avoids the complex procedure of identifying various system parameters such as geometric(kinematic) or nongeometric(dynamic) ones and generates the corresponding desired compensated joint commands directly to each joint for given target commands in the world coordinate. The generated net outputs automatically handles the effect of unknown system parameters and dynamic error sources. On-line sequential learning on the prespecified sampled nodes requires only the measurement of the corresponding tool tip locations for three d.o.f. manipulator but location and orientation for six d.o.f. manipulator. The proposed calibration procedure can be applied to any robot.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.6
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• pp.930-935
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• 1987

This paper presents a decentralized model reference adaptive control scheme for an interconnected continuous linear system composed of a number of single input single output subsystems. The scheme can treat the unknown strengh of interconnections as well as the uncertainty of subsystems. The scheme automatically adjusts the local feedback gains so that the output of each subsystem exponetially tracks that of the reference model.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.2
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• pp.110-115
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• 2000

A receding horizon FIR filter is suggested for discrete time-varying systems, combining the Kalman filter with the receding horizon strategy. The suggested filter is shown to be an FIR structure that has many good ingerent properties. The suggested filter is represented in an iterative form and also in a standard FIR form. The suggested filter turns out to be a remarkable deadbeat observer that is often robust against system and measurement noises. It is also shown that the suggested filter is an unbiased estimator irrespective of any horizon initial condition. For the amenability to parallel and systolic implementation as well as the numerical stability, a square-root algorithm for the suggested filter is presented. To evaluate performance, the suggested filter is applied to a problem of unknown input estimation and compared with the existing Kalman filter based approach.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.113-115
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• 1997

This paper presents an efficient method which can estimate the system with unmodeled dynamics using D-L networks. The proposed method is to estimate system with unmodeled dynamics recursively from only input-output information, which can exclude additional procedure for system description and thus reduce the required computational burden for real-time estimation. Higher convergence speed is achieved with our manner when compared with widely-used conventional methods.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.573-575
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• 1997

In this paper, the electronic differential system for electric vehicle using neural network is proposed and its performance is evaluated. The input features of NN are obtained by processing the encoder and potentiometer during driving. The 3 layered NN with back propagation algorithm has been used. Evaluation experiments show that the proposed controller is effective in controlling of unknown nonlinear plants.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.12
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• pp.2233-2239
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• 2007

The pantograph-catenary system is one of important components for high-speed rail system that are powered electrically. Electrical power is delivered from a catenary structure to the train via a pantograph and thus it is very important to regulate the contact force between catenary and pantograph. Although a lot of research results for active pantograph have been reported, most of them have made an unrealistic assumption that the catenary displacement is constant with respect to the time. In this paper, we present a new pantograph model that regards the catenary displacement as an unknown disturbance input. Moreover, a disturbance observer based controller is proposed to remove the effect of disturbance, i.e., the catenary displacement variation. The computer simulation result shows that the substantial improvement in regulating the contact force can be achieved by the proposed controller.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1957-1958
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• 2008

The Logic Built In Self Test (LBIST) technique is substantially applied in chip design in most many semiconductor company in despite of unavoidable overhead like an increase in dimension and time delay occurred as it used. Currently common LBIST software uses the MISR (Multiple Input Shift Register) However, it has many considerations like defining the X-value (Unknown Value), length and number of Scan Chain, Scan Chain and so on for analysis of result occurred in the process. So, to solve these problems, common LBIST software provides the solution method automated. Nevertheless, these problems haven't been solved automatically by Tri-state Bus in logic circuit yet. This paper studies the simulator and algorithm that judges whether Tri-state Bus lines is the circuit which have X-value or One-hot Value after presuming the control signal of the lines which output X-value in the logic circuit to solve the most serious problems.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1775-1776
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• 2008

This paper presents a adaptive fuzzy control suitable for motion control of multi-link robot manipulators with uncertainties. When joint velocities are available, full state adaptive fuzzy feedback control is designed to ensure the stability of the closed loop dynamic. If the joint velocities are not measurable, an observer is introduced and an adaptive output feedback control is designed based on the estimated velocities. To reduce the number of fuzzy rules of the fuzzy controller, we consider the properties of robot dynamics and the decomposition of the unknown input gain matrix. The proposed controller is robust against uncertainties and external disturbances. The validity of the control scheme is demonstrated by computer simulations on a two-link robot manipulator.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.4
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• pp.96-103
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• 2007

In this paper, we present a novel and numerically efficient algorithm for high resolution TOA(Time Of Arrival) estimation under indoor radio propagation channels. The proposed algorithm is not dependent on the structure of receivers, i.e, it can be used with either coherent or non-coherent receivers. The TOA estimation algorithm is based on a high resolution frequency estimation algorithm of Minimum-norm. The efficiency of the proposed algorithm relies on numerical analysis techniques in computing signal or noise subspaces. The algorithm is based on the two step procedures, one for transforming input data to frequency domain data and the other for estimating the unknown TOA using the proposed efficient algorithm. The efficiency in number of operations over other algorithms is presented. The performance of the proposed algorithm is investigated by means of computer simulations.. Throughout the analytic and computer simulation results, we show that the proposed algorithm exhibits superior performance in estimating TOA estimation with limited computational cost.