• 제목/요약/키워드: Vehicle velocity

검색결과 1,006건 처리시간 0.024초

속도구속조건을 이용한 수중 이동체의 접안제어 (A berthing control for underwater vehicle with velocity constraints)

  • 남택근;김철승;노영오;박영산
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2004년도 추계학술대회
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    • pp.41-46
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    • 2004
  • 본 논문에서는 속도 구속조건을 갖는 수중이동체를 초기위치로부터 목적위치에 접안하는 제어기법에 대해서 논의한다. 단, 수중이동 체는 일정방향으로 속도성분을 갖지 않는 즉, 속도구속조건을 가지는 것으로 가정한다. 본 논문에서는 이러한 시스템에 대하여 비 홀로노믹적인 관점에서 시스템을 해석하고 수중이동체를 체인드폼으로 변환한 후 Multi-rate 디지털 제어기법을 적용하여 자세제어를 행하고 수치시뮬레이션을 통하여 제어기법의 유용성을 평가하였다.

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융합된 다중 센서와 EKF 기반의 무인잠수정의 항법시스템 설계 (Navigation System of UUV Using Multi-Sensor Fusion-Based EKF)

  • 박영식;최원석;한성익;이장명
    • 제어로봇시스템학회논문지
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    • 제22권7호
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    • pp.562-569
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    • 2016
  • This paper proposes a navigation system with a robust localization method for an underwater unmanned vehicle. For robust localization with IMU (Inertial Measurement Unit), a DVL (Doppler Velocity Log), and depth sensors, the EKF (Extended Kalman Filter) has been utilized to fuse multiple nonlinear data. Note that the GPS (Global Positioning System), which can obtain the absolute coordinates of the vehicle, cannot be used in the water. Additionally, the DVL has been used for measuring the relative velocity of the underwater vehicle. The DVL sensor measures the velocity of an object by using Doppler effects, which cause sound frequency changes from the relative velocity between a sound source and an observer. When the vehicle is moving, the motion trajectory to a target position can be recorded by the sensors attached to the vehicle. The performance of the proposed navigation system has been verified through real experiments in which an underwater unmanned vehicle reached a target position by using an IMU as a primary sensor and a DVL as the secondary sensor.

자율주행을 위한 레이더 기반 인지 알고리즘의 정량적 분석 (Quantitative Analysis of Automotive Radar-based Perception Algorithm for Autonomous Driving)

  • 이호준;채흥석;서호태;이경수
    • 자동차안전학회지
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    • 제10권2호
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    • pp.29-35
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    • 2018
  • This paper presents a quantitative evaluation method and result of moving vehicle perception using automotive radar. It is also important to analyze the accuracy of the perception algorithm quantitatively as well as to accurately percept nearby moving vehicles for safe and efficient autonomous driving. In this study, accuracy of the automotive radar-based perception algorithm which is developed based on interacting multiple model (IMM) has been verified via vehicle tests on real roads. In order to obtain experimental data for quantitative evaluation, Long Range Radar (LRR) has been mounted on the front of the ego vehicle and Short Range Radar (SRR) has been mounted on the rear side of both sides. RT-range has been installed on the ego vehicle and the target vehicle to simultaneously collect reference data on the states of the two vehicles. The experimental data is acquired in various relative positions and velocity, and the accuracy of the algorithm has been analyzed according to relative position and velocity. Quantitative analysis is conducted on relative position, relative heading angle, absolute velocity, and yaw rate of each vehicle.

인휠모터 차량의 주행 안정화 제어 알고리즘 연구 (A control algorithm for driving stability improvement of in-wheel motors vehicle)

  • 최승회;김진성;허훈
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2011년도 춘계학술대회 논문집
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    • pp.206-211
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    • 2011
  • In this paper, a control algorithm for the improvement of yaw and velocity stability of electrical vehicle with two or four in-wheel motors is proposed. The vehicle is modeled with independently operative in-wheel motor wheels. Different frictions on the wheels are regarded as disturbances, which causes driving instability. In this situation the proposed algorithm enables stabilizing the yaw motion and velocity of vehicle simultaneously. The proposed PID controller is composed with two techniques, which enhance the disturbance reject and point tracking performances. One is nonlinear gain function and the other one is improved integral controller operating as time based weight function. Simulation is conducted to reveal its efficient performance.

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Extended Kalman Filter Based GF-INS Angular Velocity Estimation Algorithm

  • Kim, Heyone;Lee, Junhak;Oh, Sang Heon;Hwang, Dong-Hwan;Lee, Sang Jeong
    • Journal of Positioning, Navigation, and Timing
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    • 제8권3호
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    • pp.107-117
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    • 2019
  • When a vehicle moves with a high rotation rate, it is not easy to measure the angular velocity using an off-the-shelf gyroscope. If the angular velocity is estimated using the extended Kalman filter in the gyro-free inertial navigation system, the effect of the accelerometer error and initial angular velocity error can be reduced. In this paper, in order to improve the navigation performance of the gyro-free inertial navigation system, an angular velocity estimation method is proposed based on an extended Kalman filter with an accelerometer random bias error model. In order to show the validity of the proposed estimation method, angular velocities and navigation outputs of a vehicle with 3 rev/s rotation rate are estimated. The results are compared with estimates by other methods such as the integration and an extended Kalman filter without an accelerometer random bias error model. The proposed method gives better estimation results than other methods.

Wave propagation of graphene platelets reinforced metal foams circular plates

  • Lei-Lei Gan;Jia-Qin Xu;Gui-Lin She
    • Structural Engineering and Mechanics
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    • 제85권5호
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    • pp.645-654
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    • 2023
  • Based on first-order shear deformation theory, a wave propagation model of graphene platelets reinforced metal foams (GPLRMFs) circular plates is built in this paper. The expressions of phase-/group- velocities and wave number are obtained by using Laplace integral transformation and Hankel integral transformation. The effects of GPLs pattern, foams distribution, GPLs weight fraction and foam coefficient on the phase and group velocity of GPLRMFs circular plates are discussed in detail. It can be inferred that GPLs distribution have great impacts on the wave propagation problems, and Porosity-I type distribution has the largest phase velocity and group velocity, followed by Porosity-III, and finally Porosity-II; With the increase of the GPLs weight fraction, the phase- and group- velocities for the GPLRMFs circular plate will be increased; With the increase of the foam coefficient, the phase- and group- velocities for the GPLRMFs circular plate will be decreased.

요각속도 추정을 위한 새로운 차량 모델의 개발 (A Development of New Vehicle Model for Yaw Rate Estimation)

  • 배상우;신무현;김대균;이장무;이재형;탁태오
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2001년도 춘계학술대회논문집B
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    • pp.565-570
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    • 2001
  • Vehicle dynamics control (VDC) system requires more information on driving conditions compared with ABS and/or TCS. In order to develop the VDC system, tire slip angles, vehicle side-slip angle, and vehicle lateral velocity as well as road friction coefficient are needed. Since there are not any cheap and reliable sensors, recent researches on parameter estimation have given rise to a number of parameter estimation techniques. This paper presents new vehicle model to estimate vehicle's yaw rate. This model is improved from the conventional 2 degrees of freedom vehicle model, so-called bicycle model, taking nonlinear effects into account. These nonlinear effects are: (i) tyre nonlinearity; (ii) lateral load transfer during cornering; (iii) variable gear ratio with respect to vehicle velocity. Estimation results are validated with the experimental results.

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대기 속도 센서가 없는 무추력 항공기의 강인 필터 기반의 바람 속도 추정 기법 (Robust Filter Based Wind Velocity Estimation Method for Unpowered Air Vehicle Without Air Speed Sensor)

  • 박용곤종;박찬국
    • 한국항공우주학회지
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    • 제47권2호
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    • pp.107-113
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    • 2019
  • 본 논문에서는 대기 속도 센서가 없는 항공기에서의 강인 필터 기반의 바람 추정 기법을 제안한다. 바람 속도(wind velocity)는 항공기의 유도 및 제어를 더욱 정밀하게 수행하기 위해 사용되는 정보이다. 일반적으로 바람 속도는, 대기 속도와 지면 속도의 차이를 계산하여 얻을 수 있다. 이때 대기 속도는 피토 튜브와 같은 항공기와 대기의 상대 속도를 측정하는 대기 속도 측정 센서에서 얻을 수 있고, 지면 속도는 항법 시스템으로부터 얻을 수 있다. 그러나 항공기의 구성을 간단하게하기 위하여 대기 속도 측정 센서를 장착하지 않는 경우, 바람 속도를 직접적으로 얻을 수 없기 때문에 필터를 이용한 바람 추정 기법이 필수이다. 이때 난류에 의해 항공기의 공력 계수가 변하게 되는데, 이는 바람 추정 필터의 시스템 모델의 불확실성을 유발하게 되고, 결국 바람 추정 성능이 저하된다. 따라서 본 연구에서는 공력계수 불확실성에 강인함을 확보하기 위해 $H{\infty}$ 필터를 적용한 바람 추정 기법을 제안하였다. 시뮬레이션을 통해 제안하는 기법이 공력계수의 불확실성이 있는 상황에서 성능을 개선하는 것을 확인하였다.

경사진 노면에서의 차량의 종 속도 추정 (Vehicle Longitudinal Velocity Estimation on Inclined Road)

  • 이상엽;김인근;이동훈;허건수
    • 한국자동차공학회논문집
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    • 제20권1호
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    • pp.14-19
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    • 2012
  • On-line and real-time information of the longitudinal velocity is the essential factor for the Advanced Vehicle Control Systems such as ABS(Anti-lock Brake System), TCS(Traction Control System), ESC (Electronic Stability Control) etc. However, the longitudinal velocity cannot be easily measured or calculated during braking maneuvering. A new algorithm is presented for the estimation of the longitudinal velocity with the measurements of the vehicle longitudinal/lateral acceleration, steering angle and yaw rate. The algorithm is designed utilizing the Extended Kalman Filter based on the 3 degree of freedom vehicle model. In order to compensate for the biased sensor signal on the inclined road, the inclined angle is also estimated. The performance of the proposed estimation algorithm is evaluated in field tests.

Backstepping 방법을 이용한 IVHS에서의 차량군 리드 차량의 종렬제어기 설계 (Longitudinal Control of the Lead Vehicle of a Platoon in IVHS using Backstepping Method)

  • 박종호;정길도
    • 한국정밀공학회지
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    • 제17권5호
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    • pp.137-144
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    • 2000
  • In this paper, a longitudinal control of the lead vehicle for a platoon in IVHS Regulation Layer is proposed. The backstepping method has been used for the controller design. This method has an advantage in that its stability need not be proven since the controller is designed based on the Lyapunov Function. The control object is that the lead vehicle tracks a reference velocity and maintains a safe distance between the inter-platoons while the followers are keeping the speed of the lead vehicle of a platoon. The coordinate of system is transformed to a new coordinate system for its convenience to design controller. The new coordinate system is composed of error and new error variable. The error is the difference between the safe distance and the actual distance of inter-platoons. A new error variable is the difference between the velocity of vehicle and the estimated state of a system operated by the virtual input. The Lyapunov function is obtained based on the variables of new coordinate system. In the computer simulation, several cases have been studied such as when the lead vehicle is tracking the optimal speed. or a lead vehicle of the following platoon tracks the velocity of the previous platoon while maintaining a safe distance. Also a nonlinear engine time constant case has been investigated. All the simulation results show that the designed controller satisfies the control object sufficiently.

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