• 자동차안전학회지
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• 제11권2호
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• pp.11-16
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• 2019

This paper suggests an algorithm for detecting fault of longitudinal controller in autonomous vehicles. Guaranteeing safety in fault situation is essential because electronic devices in vehicle are dependent each other. Several methods like alarm to driver, ceding control to driver, and emergency stop are considered to cope with fault. This research investigates the fault monitoring process in fail-safe system, for controller which is responsible for accelerating and decelerating control in vehicle. Residual is computed using desired acceleration control command and actual acceleration, and detection of its abnormal increase leads to the decision that system has fault. Before computing residual for controller, health monitoring process of acceleration signal is performed using hardware and analytic redundancy. In fault monitoring process for controller, a process model which is fitted using driving data is considered to improve the performance. This algorithm is simulated via MATLAB tool to verify performance.

• 자동차안전학회지
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• 제13권4호
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• pp.39-52
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• 2021

This paper presents a longitudinal acceleration controller that can be applied to real vehicles (nonlinear and time-varing systems) with only a simple experiment regardless of the type of vehicle and the control interface structure. The controller consists of a feedforward term for fast response, a zero-throttle acceleration compensation term, and a feedback term (P gain) to compensate for errors in the feedforward term, and another feedback term (I gain) to respond to disturbances such as slope. In order to easily apply it to real vehicles, there are only two tuning parameters, feedforward terms of throttle and brake control. And the remaining parameters can be calculated immediately when the two parameters are decided. The tuning procedure is also unified so that it can be quickly and easily applied to various vehicles. The performance of the controller was evaluated using MATLAB/Simulink and Truksim's European Ben model. In addition, the controller was successfully implemented to 3 medium-sized vehicle (HMC Solati), which is composed of different control interface characteristic. Vehicle driving performance was evaluated on the test track and on the urban roads in Siheung and Seoul.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.389-389
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• 2000

The number of automobiles is rapidly increasing , as are the importance of the car as a way of transportation, and the variety of its uses. In these surroundings, a safety, one of the primary factors which must be considered in automotive engineering, demands a system that aids the driver's vision and perception. In this point of view, development of the more promoted system that complement the existing passive method which relies on just man's ability is the important issue of the advanced traffic system including ITS. In this paper, we provide an algorithm and implementation of a control system that warns the collisions ahead and avoids this situation, using informations about the host-car, target-car and surroundings. The warning is made by an algorithm that decides the degree of safely. With this degree of safely, the controller automatically controls a vehicle's speed to a proper level.

• 자동차안전학회지
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• 제12권2호
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• pp.14-20
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• 2020

This paper presents a vehicle mass and road grade estimator for developing an automated bus. To consider the dynamic characteristics of a bus varying with the number of passengers, the longitudinal controller needs the estimation of the vehicle's mass and road grade in real-time and utilizes the information to adjust the control gains. Discrete Kalman filter is applied to estimate the time-varying road grade, and the recursive least squares algorithm is adopted to account for the constant mass estimation. After being implemented in MATLAB/Simulink, the estimators are evaluated with the dynamic model and experimental data of the target bus. The proposed estimators will be applied to complement the algorithm of the longitudinal controller and proceed with algorithm verification.

• 한국자동차공학회논문집
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• 제12권1호
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• pp.216-221
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• 2004

This paper describes a fault detection and fault handling algorithm to be used in a longitudinal vehicle cruise control systems. The fault diagnosis system consists of two structures to generate proper residuals and to find that which component has a fault. A systematic design of the fault diagnosis system using model-based techniques is presented. A linear observer is used to create a set of signals sensitive to faults in a radar sensor. The fault handling system consists of two structures to compensate for faults and degraded system performance. Simulation results show that the algorithm is effective for a fault diagnosis and handling in a longitudinal vehicle cruise control system.

• 한국자동차공학회논문집
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• 제12권1호
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• pp.215-215
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• 2004

This paper describes a fault detection and fault handling algorithm to be used in a longitudinal vehicle cruise control systems. The fault diagnosis system consists of two structures to generate proper residuals and to find that which component has a fault. A systematic design of the fault diagnosis system using model-based techniques is presented. A linear observer is used to create a set of signals sensitive to faults in a radar sensor. The fault handling system consists of two structures to compensate for faults and degraded system performance. Simulation results show that the algorithm is effective for a fault diagnosis and handling in a longitudinal vehicle cruise control system.

• 한국항공우주학회지
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• 제38권2호
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• pp.150-159
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• 2010

재진입 비행체의 Approach & Landing단계는 Steep Glideslope 단계, Circular Flare 단계, Flare Maneuver 단계로 이루어지며, 본 논문에서는 실시간 경로 생성을 위하여 기하학적 조건을 이용한 기준궤적 생성 알고리즘을 사용하였다. 이를 통하여 재진입비행체의 착륙 안정성을 고려한 기준궤적을 빠른 시간 안에 생성할 수 있다. 그리고 본 논문에서는 비선형 시스템에 대하여 강건성을 가지는 Mamdani Fuzzy PD Controller를 통한 종방향 및 횡방향 제어기를 설계하였다. 또한 Downrange 와 Crossrange의 초기 오차를 포함하는 시뮬레이션을 수행하여, 제안된 Fuzzy 제어기의 우수한 성능을 확인하였다.

• 제어로봇시스템학회논문지
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• 제7권6호
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• pp.477-486
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• 2001

Many physical systems can be modeled by incorporating continuous and discrete event nature together. Such hybrid systems contain both continuous and discrete states that influence the dynamic be-havior of the systems. There has been an increasing interest in thers types of systems during the last dec-ade, mostly due to the growing usage of computers in the control of physical plants but also as a result of the hybrid nature of physical processes. The stability theory for hybrid systems is considered as extension of Lyapunov theory where the existence of an abstract energy function satisfying certain properties verifies stability, called multiple Lyapunov theory. In this paper, a hybrid stabilizing controller is proposed using the control Lyapunov function method and multiple Lyapunov theory, and the proposed method is applied to lon-gitudinal spacing control in a vehicle platoon for intelligent transportation systems(ITS).

• 제어로봇시스템학회논문지
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• 제18권5호
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• pp.453-464
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• 2012

This is a research of an adaptive longitudinal control system for situated cognition in wide range, traffic accidents reduction and safety driving environment by integrated system which graft a road infrastructure's information based on IT onto the intelligent vehicle combined automobile and IT technology. The road infrastructure installed by laser scanner in intersection, speed limited area and sharp curve area where is many risk of traffic accident. The road infra conducts objects recognition, segmentation, and tracking for determining dangerous situation and communicates real-time information by Ethernet with vehicle. Also, the data which transmitted from infrastructure supports safety driving by integrated with laser scanner's data on vehicle bumper.

• 자동차안전학회지
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• 제13권4호
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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.