• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.3
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• pp.10-21
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• 1993

Bilinear models are attractive for adaptive filtering applications because they can approximate a large class of nonlinear systems adequately, and usually with considerable parsimony in the number of coefficients compared with Volterra models. But bilinear filters have stability problem because they involve nonlinear feedback. Adaptive algorithms for bilinear filters may be diverge and have poor convergence characteristics when input signal is large In this paper, necessary and sufficient condition for mean square stability of bilinear filters for given input signal statistics is briefly described, and the method obtaining the input bound to guarantee the stability of bilinear filters is presented. New RPEM algorithm, which does not diverge and has the superior convergence characteristics compared with the conventional RPEM algorithm when input signal is large, is derived by applying the time-varying Kalman filtering concept to the conventional RPEM algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.185-188
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• 1999

An estimation algorithm for vehicle driving load has been proposed in this paper. Driving load is an important factor in a vehicle's longitudinal motion control. An approach using an observer is introduced to estimate driving load based on inexpensive RPM sensors currently being used in production vehicles. Also, a torque estimation technique using nonlinear characteristic functions has been incorporated in this estimation algorithm. Using a nonlinear full vehicle simulation model, we study the effect of the driving load on longitudinal vehicle motion, and the performance of the estimation algorithm has been evaluated. The proposed estimation algorithm has good performance and robustness over uncertainties in the system parameters. An accurate estimate of the driving load can be very helpful in the development of advance vehicle control systems such as intelligent cruise control systems, CW/CA systems and smooth shift control systems.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.2
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• pp.56-68
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• 1994

The objective of camera calibration is to determine the internal optical characteristics of camera and the three-dimensional position and orientation of camera with respect to the real world. Calibration procedure for computer vision should be automatical, accurate and applicable to general purpose cameras and lenses. In this paper, we present camera calibration method which meets the above requirements. The algorithm is based on the two-stage method which takes into account lens distortion in the second stage. In this paper, the overdetermined nonlinear system is established in terms of the constraints to all directions and our calibration algorithm is proposed which is constructed by using Marquardt iterations and our calibration algorithm is proposed which is constructed by using Marquardt iteration method in solving nonlinear equations. Experimental results indicate that lens distortion should be taken into consideration for the calibration of the general-purpose lens. With 24 calibration points acquired out of 512$\times$512 image, the proposed algorithm came up with average error of less than 1 pixel and showed a higher accuracy over the conventional two-stage method.

• Journal of applied mathematics & informatics
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• v.29 no.1_2
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• pp.173-190
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• 2011

In this paper, we construct a new approach of affine scaling interior algorithm using the affine scaling conjugate gradient and Lanczos methods for bound constrained nonlinear optimization. We get the iterative direction by solving quadratic model via affine scaling conjugate gradient and Lanczos methods. By using the line search backtracking technique, we will find an acceptable trial step length along this direction which makes the iterate point strictly feasible and the objective function nonmonotonically decreasing. Global convergence and local superlinear convergence rate of the proposed algorithm are established under some reasonable conditions. Finally, we present some numerical results to illustrate the effectiveness of the proposed algorithm.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.4
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• pp.51-56
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• 2006

This paper proposes a control algorithm, which is verified experimentally, for aspherical surface grinding and polishing. The algorithm provides simultaneous control of the position and interpolation of an aspheric curve. The nonlinear formula for the tool position was derived from the aspheric equation and the shape of the tool. The function was partitioned at specific intervals and the control parameters were calculated at each control section. The position, acceleration, and velocity at each interval were updated during the process. A position error feedback was introduced using a rotary encoder. The feedback algorithm corrected the position error by increasing or decreasing the feed speed. In the experimental verification, a two-axis machine was controlled to track an aspherical surface using the proposed algorithm. The effects of the control and process parameters were monitored. The results demonstrated that the maximum tracking error with tuned parameters was at the submicron level for concave and convex surfaces.

• Journal of Korean Society for Quality Management
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• v.28 no.2
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• pp.135-146
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• 2000

This study has adapted a genetic algorithm for an optimal design for the first time. The models using a simulation are the nonlinear models. Using an genetic algorithm in D-optimal, it is more efficient than previous algorithms to get an object function. Not like other algorithms, without any troublesome restrictions about the initial solution, not falling into a local optimal solution, it's the most suitable algorithm. Also if we use it without any adding experiments, we can use it to find optimal design of experimental condition efficiently.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.52-57
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• 2006

In this paper, we have proposed a new adaptive fuzzy control algorithm based on Takagi-Sugeno fuzzy model. The regulation problem for the uncertain SISO nonlinear system is solved by the proposed algorithm. Using the advanced stability theory, the stability of the state, the control gain and the parameter approximation error is proved. Unlike the existing feedback linearization based methods, the proposed algorithm can guarantee the global stability in the presence of the singularity in the inverse dynamics of the plant. The performance of the proposed algorithm is demonstrated through the problem of balancing and swing-up of an inverted pendulum on a cart.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.320-322
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• 2003

This paper describes a current differential relaying algorithm for a three-phase transformer considering the nonlinear magnetization characteristics of the core. The iron-loss current is obtained from the calculated induced voltage and the core-loss resistance. The magnetizing current is calculated from the estimated core flux and the magnetization curve. The proposed algorithm uses the modified differential current, which is obtained by subtracting the iron-loss current and the magnetizing current from the conventional differential current. The various test results show that the algorithm can discriminate internal fault from magnetic inrush, overexcitation and an external fault.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3060-3062
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• 2000

A fast optimal path planning algorithm using the analog Cellular Nonlinear Circuits (CNC) is proposed. The proposed algorithm compute the optimal path using subgoal-based dynamic programming algorithm. In the algorithm, the optimal paths are computed regardless of the distance between the initial and the goal position. It begins to find subgoals starting from the initial position when the output of the initial cell becomes nonzero value. The suboal is set as the initial position to find the next subgoal until the final goal is reached. Simulations have been done considering the imprecise hardware fabrication and the limitation of the magnitude of input value.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.359-362
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• 1996

This paper describes a development of traction control algorithm to investigate dynamic behavior of 2-motor driven electric vehicle. A electric vehicle is represented by a nonlinear seven degree of freedom including accelerations of wheels, longitudinal, lateral, and yaw motions. A nonlinear control algorithm is proposed in order to enhance the driveability of the electric vehicle with torque split control system. With the proposed control algorithm, numerical simulations are performed to analyze the dynamic behavior of the electric vehicle.