• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.101-108
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• 2001

In this study, the static and dynamic characteristics of endmilling process were modelled and the analytic realization of chatter mechanism was discussed. In this reward, We have discussed on the comparative assessment of recursive time series modeling algorithms that cal represent time machining process and detect the abnormal machining behaviors in precision endmilling operation. In this study, simulation and experimental works were performed to show the malfunctional behaviors. For this purpose, new recursive algorithm(RLSM) was adopted for the oil-line system identification and monitoring of a machining process, we can apply these new algorithms in real process for detection of abnormal chatter. Also, The stability lobe of chatter was analysed by varying parameter of cutting dynamics in regenerative chatter mechanics.

• The Journal of the Acoustical Society of Korea
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• v.19 no.5
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• pp.84-90
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• 2000

The bearing detection of radiated target noise is very important at underwater acoustic measurement and passive detection. It differs the arrival tines of received signal at each sensor. Therefore, the bearing can be obtained from the time delay. This paper proposes a new algorithm using the RLSL adaptive filter for TDE. The proposed method is particularly attractive when there is a limitation of priori information about the received signal spectra and when the delay is subject to variation. As the simulation results, it is shown that the proposed algorithm has better convergence characteristics and TDE speed, and so that the usefulness of proposed algorithm is confirmed.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.129-143
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• 2021

This paper proposes actuator fault detection and adaptive fault-tolerant control algorithms using performance index and human-like learning for longitudinal autonomous vehicles. Conventional longitudinal controller for autonomous driving consists of supervisory, upper level and lower level controllers. In this paper, feedback control law and PID control algorithm have been used for upper level and lower level controllers, respectively. For actuator fault-tolerant control, adaptive rule has been designed using the gradient descent method with estimated coefficients. In order to adjust the control parameter used for determination of adaptation gain, human-like learning algorithm has been designed based on perceptron learning method using control errors and control parameter. It is designed that the learning algorithm determines current control parameter by saving it in memory and updating based on the cost function-based gradient descent method. Based on the updated control parameter, the longitudinal acceleration has been computed adaptively using feedback law for actuator fault-tolerant control. The finite window-based performance index has been designed for detection and evaluation of actuator performance degradation using control error.

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.13-22
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• 2020

This paper presents an adaptive feedback based actuator fault detection and tolerant control algorithms for longitudinal functional safety of autonomous driving. In order to ensure the functional safety of autonomous vehicles, fault detection and tolerant control algorithms are needed for sensors and actuators used for autonomous driving. In this study, adaptive feedback control algorithm to compute the longitudinal acceleration for autonomous driving has been developed based on relationship function using states. The relationship function has been designed using feedback gains and error states for adaptation rule design. The coefficients in the relationship function have been estimated using recursive least square with multiple forgetting factors. The MIT rule has been adopted to design the adaptation rule for feedback gains online. The stability analysis has been conducted based on Lyapunov direct method. The longitudinal acceleration computed by adaptive control algorithm has been compared to the actual acceleration for fault detection of actuators used for longitudinal autonomous driving.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.89-102
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• 2001

Using a multiproduct translog cost function model, this paper examines the existence or absence of scale and scope economies in Seoul's urban bus industry. The Paper then conceptualizes that the bus firm produces three outputs (city, seat and local bus-kilometers) using low input factors(labor, capital, fuel and maintenance). Using 1996 annual observations for 81 Seoul's bus firms, the equation system consisting of a cost function and three input share equations is estimated with the nonlinear iterative Zellner method. The findings show that the cost function corresponding to a non-homothetic production technology with separability between local bus outputs and inputs adequately represents the structure of cost for Seoul's bus firms, and that the demand lot all input factors is quite inelastic with respect to their own price. On the other hand, nearly all firms experience mild overall economies or scale, but rather marked product-specific economies of scale with respect to all the three outputs. In addition, there appear to be substantial economies or scope associated with the joint production of city and seat bus services, while considerable diseconomies of scope associated with that of city and local bus services. These results indicate that the merger of smaller firms into larger firms with a fleet of approximately 200 buses would result in more cost-efficient bus services.

• Journal of Advanced Navigation Technology
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• v.3 no.2
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• pp.156-166
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• 1999

In multi-vehicle tracking systems Kalman filter is generally used for tracking vehicles. Despite well known advantages of Kalman filter that presents optimality with constraints, it is difficult to track several vehicles in real time simultaneously due to a large number of computations. In this paper, we propose a multi-vehicle tracking system with an adaptive predictor that employs recursive least square algorithm which can be easily implemented for real time application on a transversal filter. The performance of the proposed tracking system is compared to one with Kalman filter using a synthetic sequential image generated by computer graphics and real sequential image taken at intersections. Simulation results show that the proposed tracking system can be applied to track vehicles in real sequential image at the rate of 30 frame/sec on a PC environments without any special hardwares.

• International Area Studies Review
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• v.15 no.3
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• pp.239-261
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• 2011

The cyclicality of productivity has been one of the essential issues in macroeconomics. Since Solow(1957) developed the dominant approach to the measurement of productivity growth, Solow's approach, which assumes the perfect competition, the constant returns to scale, and the full use of input factor has been modified particularly in Hall's(1990) and Basu's(1996) works. Their researches take account of market power, returns to scale, and variable factor utilization. This paper establishes the empirical model based on Hall's(1990) and Basu's(1996) models, estimates 4 types of Solow's reidual in manufacturing and 2 service industries over the period 1975:1-2010:4, and analyzes the cyclicality of measured productivity. The result proved the measured productivity to be procyclical in manufacturing industries and electricity and water industry, and in contrast to the Basu's, the variable factor utilization transformed the countercyclicality of measured productivity into its procyclicality in the Korean economy.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.6
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• pp.1-10
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• 2007

This paper presents a direct nonlinear multivariable self-tuning PID controller using neural network which adapts to the changing parameters of the nonlinear multivariable system with noises and time delays. The nonlinear multivariable system is divided linear part and nonlinear part. The linear controller are used the self-tuning PID controller that can combine the simple structure of a PID controllers with the characteristics of a self-tuning controller, which can adapt to changes in the environment. The linear controller parameters are obtained by the recursive least square. And the nonlinear controller parameters are achieved the through the Back-propagation neural network. In order to demonstrate the effectiveness of the proposed algorithm, the computer simulation results are presented to adapt the nonlinear multivariable system with noises and time delays and with changed system parameter after a constant time. The proposed PID type nonlinear multivariable self-tuning method using neural network is effective compared with the conventional direct multivariable adaptive controller using neural network.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.10
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• pp.64-74
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• 2007

Because of the size and environment in the shipbuilding process, the portable type robot is required for the automatic seam tracking. For this reason, the structure of laser sensor should be considered in the initial design step and the coordinate transformation between welding robot and laser sensor, which is joint finder, must be identified exactly and the real time tracking algorithm based on these consideration could be developed. In this research, laser displacement sensor in which its structure is laser beam's vertical projection, is developed to recognize the location of weld joint. In practical applications, however, images of weld joints are often degraded because of the surface specularity or spatter. To overcome the problem, the constrained joint finding algorithm is proposed. In the approach of coordinate conversion rule for the visual feedback control among welding torch, robot body and laser sensor is applied by the same reference point method. In the real time seam tracking algorithms we propose constrained sampling method which uses look ahead distance. The RLS(Recursive Least Square) filter is applied to obtain the smooth tracking path from the sensitive edge data. From the experimental results, we could see the possibility that the developed laser sensor with proposed processing algorithm and real time seam tracking method can be used as a welding under the shipbuilding condition.

• Nuclear Engineering and Technology
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• v.27 no.3
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• pp.336-343
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• 1995

The Self Tuning Regulator(STR) method which is an approach of adaptive control theory, is ap-plied to design the fully automatic power controller of the nonlinear reactor model. The adaptive control represent a proper approach to design the suboptimal controller for nonlinear, time-varying stochastic systems. The control system is based on a third­order linear model with unknown, time-varying parameters. The updating of the parameter estimates is achieved by the recursive extended least square method with a variable forgetting factor. Based on the estimated parameters, the output (average coolant temperature) is predicted one-step ahead. And then, a weighted one-step ahead controller is designed so that the difference between the output and the desired output is minimized and the variation of the control rod position is small. Also, an integral action is added in order to remove the steady­state error. A nonlinear M plant model was used to simulate the proposed controller of reactor power which covers a wide operating range. From the simulation result, the performances of this controller for ramp input (increase or decrease) are proved to be successful. However, for step input this controller leaves something to be desired.