• Journal of Power Electronics
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• v.18 no.2
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• pp.558-572
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• 2018

In addition to its modular nature, a Hybrid Modular Multilevel Converter (HMMC) assembled from half-bridge and full-bridge sub-modules, is able to block DC faults with a minimum number of switching devices, which makes it attractive for high power applications. This paper introduces a control strategy based on the Root-Least Square (RLS) algorithm to estimate the capacitor voltages instead of using direct measurements. This action eliminates the need for voltage transducers in the HMMC sub-modules and the associated communication link with the central controller. In addition to capacitor voltage balancing and suppression of circulating currents, a fault tolerant control unit (FTCU) is integrated into the proposed strategy to modify the parameters of the HMMC controller. On advantage of the proposed FTCU is that it does not need extra components. Furthermore, a fault detection unit is adapted by utilizing a hybrid estimation scheme to detect sub-module faults. The behavior of the suggested technique is assessed using PSCAD offline simulations. In addition, it is validated using a real-time digital simulator connected to a real time controller under various normal and fault conditions. The proposed strategy shows robust performance in terms of accuracy and time response since it succeeds in stabilizing the HMMC under faults.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.802-803
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• 2011

매입형 영구자석 동기전동기는 강건한 회전자 구조와 릴럭턴스 토크를 사용할 수 있다는 점, 악계자 제어를 하기 쉽다는 점에서 넓은 속도와 토크를 필요로하는 하이브리드 차량이나 전기 차량에 적합한 전동기이다. 영구자석의 감자곡선은 온도에도 의존하기 때문에 온도에 따라 전동기의 자속과 토크가 변하게 된다. 이 논문은 전기 스쿠터에 사용되는 매입형 영구자석 동기전동기의 온도에 따른 지령 전류 보정에 의한 제어법에 대해 연구하였다. 토크 리플을 줄이기 위해서 속도-토크 곡선과 감자곡선을 이용하여 구하였으며, 보정된 지령 전류를 구하기 위해 Lagrange 보간법과 재귀 최소자승(Recursive Least Square : RLS) 법을사용하여 전류맵을 만들었다.이 지령 전류는 토크와 인버터 출력 전류값을 계산하는데 사용된다. 전류맵을 만들기 위해서 측정한 온도는 20, 80, 100도이다. 본 논문에서 제안한 제어법을 이용하여 토크 리플이 줄어듬을 시뮬레이션과 실험을 통해서 확인할 수 있었다.

• The Journal of the Acoustical Society of Korea
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• v.18 no.5
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• pp.3-11
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• 1999

The conventional stereophonic acoustic echo cancellers need two adaptive filters to estimate one channel echo signal. Since the two channel signals are strongly correlated, the ESR of the input signals is considerably increased whatever the input signals may be. This causes the slow convergence of the adaptive filter for echo cancellation. To speed up the convergence, the AP algorithm is frequently used for the stereophonic acoustic echo canceller although there isn't a fast version for 2-channel case. The AP algorithm can be approximated with the Gram-Schmidt orthogonalization and a TDL structure. We propose a two channel algorithm for stereophonic acoustic echo canceller with the approximated AP algorithm.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2949-2952
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• 2000

A new neural networks and learning algorithm are proposed in order to measure nonlinear heights of complexed road environments in realtime without pre-information. This new neural networks is Error Self Recurrent Neural Networks(ESRN), The structure of it is similar to recurrent neural networks: a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by back-propagation and each weights are updated by RLS(Recursive Least Square). Consequently. this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. We can estimate nonlinear models in realtime by ESRN and learning algorithm and control nonlinear models. To show the performance of this one. we control 7 degree of freedom full car model with several control method. From this simulation. this estimation and controller were proved to be effective to the measurements of nonlinear road environment systems.

• Journal of Satellite, Information and Communications
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• v.6 no.2
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• pp.117-124
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• 2011

In this paper, we present more effective throughput enhancement technique to improve the data rate and reliability by using the multiple antenna technique. The conventional spatial diversity scheme is limited in according with the interference from each antenna channel status, and the orthogonality of spreading codes and subcarriers are destroyed due to the frequency selectivity. Proposed system is considered MC-CDMA system with 4 transmit antennas and 1 receive antenna. Proposed system based on SVD with the MS-RLS MMSE subcarrier combining method in order to achieve better performance with low computational complexity. Via computer simulation, we confirm that the proposed system is able to improve the BER performance by suppressing the interference of other antenna signals.

• The Transactions of the Korean Institute of Power Electronics
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• v.8 no.1
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• pp.80-88
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• 2003

In this paper, the new robust torsional vibration suppression control scheme is proposed for the two mass system. A reduced order state feedback controller where the motor speed and the observed torsional torque are fed back and the PI controller are proposed as the torsional vibration suppression controller. Using the estimated mechanical parameters by off-line RLS(Recursive Least Square) algorithms, the speed controller for torsional vibration suppression is designed and its gains are determined using the Kharitonov robust control theory. The Kharitonov robust control theory can obtain the robust stability with a specified stability margin and a damping limit and the good performance of vibration suppression although if the parameters are varied within some specified limit. The effectiveness and usefulness of the proposed schemes are verified with the simulation and the experimental results on the fully-digitalized 5.5kW two mass system.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11A
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• pp.1244-1252
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• 2004

In this paper, we derive some properties of linear detectors (zero forcing or minimum mean square error) at spatial multiplexing systems with alamouti's space-time block code. Based on the derived properies, this paper proposes low-complexity receivers. Implementing MMSE detector adaptively, the number of weight vectors to be calculated and updated is greatly reduced with the derived properties compared to the conventional methods. In the case of recursive least square algorithm, with the proposed approach computational complexity is reduced to less than the half. We also identify that sorted QR decomposition detector, which reduces the complexity of V-Blast detector, has the same properties for unitary matrix Q and upper triangular matrix R. A complexity reduction of about 50%, for sorted QR decomposition detector, can be achieved by using those properties without the loss of performance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.6
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• pp.673-679
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• 2012

Vehicle rollover is a serious kind of accident, particularly for sport utility vehicles, and its occurrence can be minimized by utilizing active rollover prevention systems. The performance of these protection systems is very sensitive to vehicle inertial parameters such as the vehicle's mass and center of mass. These parameters vary with the number of passengers and in different load situations. In this paper, a unified method for vehicle mass estimation is proposed that takes into account the available driving conditions. Three estimation algorithms are developed based on longitudinal, lateral, and vertical vehicle motion, respectively. Then, the three algorithms are combined to extract information on the vehicle's mass during arbitrary vehicle maneuvering. The performance of the proposed vehicle mass estimation method is demonstrated through real-time experiments.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.4
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• pp.264-274
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• 2003

This paper presents a direct generalized minimum-variance self tuning controller with a PID structure using neural network which adapts to the changing parameters of the nonlinear system with nonminimum phase behavior, noises and time delays. The self-tuning controller with a PID structure is a combination of the simple structure of a PID controller and the characteristics of a self-tuning controller that can adapt to changes in the environment. The self-tuning control effect is achieved through the RLS (recursive least square) algorithm at the parameter estimation stage as well as through the Robbins-Monro algorithm at the stage of optimizing the design parameter of the controller. The neural network control effect which compensates for nonlinear factor is obtained from the learning algorithm which the learning error between the filtered reference and the auxiliary output of plant becomes zero. Computer simulation has shown that the proposed method works effectively on the nonlinear nonminimum phase system with time delays and changed system parameter.