• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.50-55
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• 2013

When it comes to commercial vehicles, their unique characteristics - center of gravity, size, weight distribution - make them particularly vulnerable to rollover. On top of that, conventional heavy vehicle brake exhibits longer actuation delays caused in part by long air lines from brake pedal to tires. This paper describes rollover prevention algorithm that copes with the characteristics of commercial vehicles. In regard of compensating for high actuating delay, predicted rollover index with short preview time has been designed. Moreover, predicted rollover index with longer preview time has been calculated by using road curvature information based on environment information. When rollover index becomes larger than specific threshold value, desired braking force is calculated in order to decrease the index. At the same time, braking force is distributed to each tire to make yaw rate track desired value.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.3
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• pp.209-219
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• 1997

A fuzzy driver model based on a preview-predictor and yaw rate is developed. The model is used to investigate the handling performance of two wheel steering system(2WS) and four wheel steering system(4WS) vehicles. The two degree-of- freedom model which has yaw and lateral motion predicts the path of the vehicles. Based upon the yaw rate and lateral deviations, the fuzzy engine describes the human driver's complicated control behavior which is adjusted for the driving environment. Both typical single lane change maneuver and double lane change maneuver are adopted to demonstrate the feasibility of fuzzy driver model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.160-166
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• 2018

This paper proposes an advanced suspension system and reports its performance in the framework of the preview control algorithm based on the RPS (road profile sensing) system and MSD system with the multi-stage damping characteristics. Typical disturbance inputs that cause excessive vibration and steering instability of an automobile are irregular obstacles that protrude or sink into the road surface to be driven. The control performance can be improved if information on the existence and shape function of its obstacle is known. Based on the results of the previous study, advanced research that uses the actuating system has been processed to be commercialized practically. For this purpose, a switching algorithm between the control logic and the multi-stage damping system was developed and its connectivity is presented. To verify the applicability of an actual vehicle, the proposed control system was implemented in full vehicle models and simulations were performed. The proposed system using the 3-DS actuator system, which is applied for structural simplicity, can improve the ride comfort and steering stability. In addition, the results indicate the feasibility of the intelligently controlled suspension system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.431-437
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• 2017

In this study, based on the RPS algorithm, the application results to an electrically controlled suspension system using previewed road information are presented. Reducing the excessive vibration induced by a disturbance transmitted to the system and secure its stability is a major issue. In particular, in the automotive industry, the demand is constantly being raised. A typical external disturbance causing vibration and instability of a vehicle is an irregular roadway surface that contacts a running vehicle tire. Therefore, obtaining such profile information is an important process. The RPS algorithm using a multi sensor system was constructed and implemented in a real car. Through experimental work using the RPS system included non-contact type optical sensors, it could robustly reconstruct the road input profiles from the intermixed data onto the vehicle's dynamic motion while traveling at an uneven roadway surface. A controller with a preview control was designed in the framework of a semi-active suspension system based on the 7 degrees of freedom full vehicle model. The control performance of the system was evaluated through simulations and the results were compared with the passive vehicle condition. These results highlight the feasibility of the presented control frame.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.430-432
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• 1990

This paper concerns a method for high precision torque control of induction motor supplied with power via a Transister inverter. The control system is totaly digitized using DSP - TMS32010.Since operation time leads to control delay in such a system, torque ripples are more significient than relieved considerably by using current preview control and vector pulse width control. The usefulness of these techniques will be demonstrated by showing the results of a simulation,and results of measurement on a 2.2Kw induction motor.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.240-248
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• 1999

This paper presents a lane-change collision avoidance control algorithm for autonomous vehicles that will be used in AHS(Automated Highway System). In the proposed control algorithm, nominal control inputs are generated by solving the inverse vehicle dynamic equations of motion for a lane-change maneuver. In addition, a corrective steering input from preview as well as DYC (Direct Yaw Moment Control) may be included to reduce unpredictable errors and to insure yaw directional stability, respectively. The performance of the algorithm is evaluated with an ABS HILS system which consist of 17 DOF vehicle model and real ABS hardware parts. The HILS simulation results show that the proposed algorithm may be used for emergency lane-change maneuvers for autonomous vehicles.

• International Journal of Control, Automation, and Systems
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• v.5 no.4
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• pp.355-363
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• 2007

The paper deals with the Kalman stochastic filtering problem for linear continuous-time systems with both instantaneous and time-delayed measurements. Different from the standard linear system, the system state is corrupted by multiplicative white noise, and the instantaneous measurement and the delayed measurement are also corrupted by multiplicative white noise. A new approach to the problem is presented by using projection formulation and reorganized innovation analysis. More importantly, the proposed approach in the paper can be applied to solve many complicated problems such as stochastic $H_{\infty}$ estimation, $H_{\infty}$ control stochastic system with preview and so on.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.775-778
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• 1996

In this research, the robustness of a seam tracking for the automatic welding system is studied. The laser displacement sensor is used as a seam finder. X-Y moving table drived by ac servo motor controls the position and velocity of the torch-and-sensor part. However, dc servo motor is used to control the position and velocity of the torch. The sensor locates ahead of torch to preview the weld line, and brings about the inaccuracy on the torch tracking. To enhance the robustness on this system against the influence of disturbances and model uncertainty, H$\_$.inf./ control is applied to the angular motion of torch. The simulation shows that the tracking accuracy improved significantly. Also, experimental results give a good performance of H$\_$.inf./ control strategy to the automatic seam tracking system for the welding.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.4
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• pp.15-26
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• 1998

Full car model is needed for investigating as a entire dynamics of vehicle. In this study, 7DOF of full car model's dynamics is selected. This paper proposes the output feedback controller based on optimal control theory. Input data and output data from the optimal controller are used for neural network system identification of the suspension system. To do system identification, neural network which has robustness against nonlinearities and disturbances is adapted. This study uses back-propagation algorithm to train a multil-layer neural network. After obtaining a neural network model of a suspension system, a neuro-controller is designed. Neuro-controller controls suspension system with off-line learning method and multistep ahead prediction model based on the neural network model and a neuro-controller. The optimal controller and the neuro-controller are designed and then, both performances are compared through. For simulation, sinusoidal and rectangular virtual bumps are selected.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.485-485
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• 2000

A design method of model following control system using neural networks is proposed. An unknown nonlinear single-input single-output plant is identified using a multilayer neural networks. A linear controller is designed fer the linear approximation model obtained by linearinzing the identification model. The identification model is also used as a plant emulator to obtain the prediction error. Deficient servo performance due to controlling nonlinear plant with only linear controller is mended by adjusting the linear controller output using the prediction output and the parameters of the identification model. An optimal preview controller is adopted as the linear controller by reason of having good servo performance lowering the peak of control input. Validity of proposed method is illustrated through a numerical simulation.