The Experts below are selected from a list of 1221 Experts worldwide ranked by ideXlab platform

Yoichi Hori - One of the best experts on this subject based on the ideXlab platform.

  • 2009 “Direct yaw moment control of an in-wheel-motored electric vehicle based on Body Slip Angle fuzzy observer
    2014
    Co-Authors: Cong Geng, Lotfi Mostefai, Mouloud Denai, Yoichi Hori
    Abstract:

    Abstract—A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based Body Slip Angle (β) ob-server. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi–Sugeno-like fuzzy models. Initially, local equivalent vehicle models are built using the lin-ear approximations of vehicle dynamics for low and high lateral acceleration operating regimes, respectively. The optimal β ob-server is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall control system by using fuzzy rules. These fuzzy rules represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism for the fuzzy membership functions has been incorporated to improve the accuracy and performance of the system. The effectiveness of this design approach has been demonstrated in simulations and in a real-time experimental setting. Index Terms—Fuzzy observer, local modeling, state feedback, vehicle lateral dynamics. I

  • multirate estimation and control of Body Slip Angle for electric vehicles based on onboard vision system
    IEEE Transactions on Industrial Electronics, 2014
    Co-Authors: Yafei Wang, Binh Minh Nguyen, Hiroshi Fujimoto, Yoichi Hori
    Abstract:

    A new method for vehicle Body-Slip-Angle estimation using nontraditional sensor configuration and system model is proposed, which enables robust estimation against vehicle parameter uncertainties. In this approach, a linear vehicle bicycle model is augmented with a simple visual model. As the visual model contains few uncertain parameters and increases the observer's design freedom, the combined model-based estimator provides more accurate estimation result compared with the traditional bicycle-model-based one. However, two issues are raised by the combined vehicle and vision models: 1) image processing introduces delay in the visual measurements, and 2) the sampling time of a normal camera is much longer than that of other onboard sensors. For electric vehicles, the control period of motors is much shorter than the sampling time of a normal camera. Considering the aforementioned delay and multirate problems, a multirate Kalman filter with intersample compensation is designed, and the estimation performance can be improved during the sampling intervals of the vision system. Then, a two-degree-of-freedom controller is designed using the estimated Body Slip Angle as feedback for reference tracking. With the proposed multirate estimator, the controller achieves better tracking performance than the singlerate method. The effectiveness of the proposed estimator and controller is demonstrated by both simulations and experiments.

  • vision based multi rate estimation and control of Body Slip Angle for electric vehicles
    Conference of the Industrial Electronics Society, 2012
    Co-Authors: Yafei Wang, Binh Minh Nguyen, Hiroshi Fujimoto, Yoichi Hori
    Abstract:

    Among many vehicle states, Body Slip Angle is one of the most important information for vehicle motion control. Due to the high costs to measure Body Slip Angle with specific devices, it is necessary to investigate estimation methods using existing cheap sensors. From the viewpoint of sensor configuration, gyroscope, steering Angle sensor, etc. are often employed for Body Slip Angle estimation; in this research, two pieces of information provided by vision system are also utilized as additional measurements. Nevertheless, the sampling rate of normal camera is much slower compared to the other kinds of onboard sensors; for electric vehicles (EVs), motors' control period is shorter than the sampling time of cameras, which also brings multi-rate issue. Moreover, the time delay caused by image processing is usually too long to be neglected. In this paper, single-rate and multi-rate Kalman filters considering measurement delay are designed for Body Slip Angle estimation, and a Body Slip Angle controller is designed with the estimated result as feedback. First of all, vehicle model and visual model as well as the multi-rate and delay issues are explained; then, single-rate and multi-rate Kalman filters are designed for Body Slip Angle estimation; and then, Body Slip Angle controllers with single-rate and multi-rate estimators are compared followed with simulations and experimental results; finally, conclusion and future works are presented.

  • vision based vehicle Body Slip Angle estimation with multi rate kalman filter considering time delay
    International Symposium on Industrial Electronics, 2012
    Co-Authors: Yafei Wang, Binh Minh Nguyen, Hiroshi Fujimoto, Yoichi Hori
    Abstract:

    Body Slip Angle is one of the most important information for vehicle motion control; as specific sensors for Body Slip Angle measurement are expensive, it is necessary to investigate estimation methods using existing popular sensors such as gyro sensor, encoder, camera, etc. For EV (electric vehicle), in particular, the motor response is several milliseconds which enables high performance control with short control period; fast signal feedback is consequently desired. Nevertheless, the sampling rate of a normal camera is much slower compared with other kinds of onboard sensors and the time delay caused by image processing cannot be neglected. In this paper, the two problems are solved using a multi-rate Kalman filter with measurement delay included; the estimated Body Slip Angle can be updated every 1 ms. First of all, vehicle model and visual model are explained followed with experimental setup introduction; then, real-time image processing techniques are briefly introduced; and then, single-rate and multi-rate Kalman filters considering time delay are designed to estimate Body Slip Angle; finally, conclusion and further works are presented.

  • Nonlinear Body Slip Angle Observer for Electric Vehicle Stability Control
    World Electric Vehicle Journal, 2008
    Co-Authors: Cong Geng, Yoichi Hori
    Abstract:

    This paper proposes a nonlinear observer for Body Slip Angle (β) estimation, in which a nonlinear tire model is adopted for the observer design. A newly developed method to identify parameters of road surface friction coefficient (μ) is introduced into this observer, which makes the observer adaptive to road condition changing. Simulations and field tests are conducted, where the feasibility of μ identification and effectiveness of the observer are checked, especially for nonlinear cornering situations.

Cong Geng - One of the best experts on this subject based on the ideXlab platform.

  • 2009 “Direct yaw moment control of an in-wheel-motored electric vehicle based on Body Slip Angle fuzzy observer
    2014
    Co-Authors: Cong Geng, Lotfi Mostefai, Mouloud Denai, Yoichi Hori
    Abstract:

    Abstract—A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based Body Slip Angle (β) ob-server. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi–Sugeno-like fuzzy models. Initially, local equivalent vehicle models are built using the lin-ear approximations of vehicle dynamics for low and high lateral acceleration operating regimes, respectively. The optimal β ob-server is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall control system by using fuzzy rules. These fuzzy rules represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism for the fuzzy membership functions has been incorporated to improve the accuracy and performance of the system. The effectiveness of this design approach has been demonstrated in simulations and in a real-time experimental setting. Index Terms—Fuzzy observer, local modeling, state feedback, vehicle lateral dynamics. I

  • direct yaw moment control of an in wheel motored electric vehicle based on Body Slip Angle fuzzy observer
    IEEE Transactions on Industrial Electronics, 2009
    Co-Authors: Cong Geng, Lotfi Mostefai, Mouloud Denai, Yutaka Hori
    Abstract:

    A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based Body Slip Angle (beta) observer. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi-Sugeno-like fuzzy models. Initially, local equivalent vehicle models are built using the linear approximations of vehicle dynamics for low and high lateral acceleration operating regimes, respectively. The optimal beta observer is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall control system by using fuzzy rules. These fuzzy rules represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism for the fuzzy membership functions has been incorporated to improve the accuracy and performance of the system. The effectiveness of this design approach has been demonstrated in simulations and in a real-time experimental setting.

  • Nonlinear Body Slip Angle Observer for Electric Vehicle Stability Control
    World Electric Vehicle Journal, 2008
    Co-Authors: Cong Geng, Yoichi Hori
    Abstract:

    This paper proposes a nonlinear observer for Body Slip Angle (β) estimation, in which a nonlinear tire model is adopted for the observer design. A newly developed method to identify parameters of road surface friction coefficient (μ) is introduced into this observer, which makes the observer adaptive to road condition changing. Simulations and field tests are conducted, where the feasibility of μ identification and effectiveness of the observer are checked, especially for nonlinear cornering situations.

  • a hybrid like observer of Body Slip Angle for electric vehicle stability control fuzzy logic and kalman filter approach
    Vehicle Power and Propulsion Conference, 2008
    Co-Authors: Cong Geng, Lotfi Mostefai, Yoichi Hori
    Abstract:

    A hybrid-like observer for vehicle Body Slip Angle (beta) is proposed, in which a local approximation of the nonlinear tire model is adopted. Local equivalent vehicle models for observer design are built by linear approximation of vehicle dynamics respectively for low and high lateral acceleration operating regimes. Fuzzy logic approach is adopted to combine the local observer models so as to deal with the nonlinear nature of vehicle dynamics. The local observers are designed as linear observers with Kalman filter theory to overcome the influence of system noise. The derivation of this hybrid-like observerpsilas state equations and the estimation mechanism is developed. The fuzzy rules can establish the qualitative relationships among the variables concerning the nonlinear and uncertain nature of vehicle dynamics, such as the saturation of tire force and the influence of road adherence. By adaptation mechanism designing of membership functions in the fuzzy rules, the quantitative accuracy and adaptive performance of the system can be satisfied, which is verified by simulations and experiments.

  • Body Slip Angle observer for electric vehicle stability control based on empirical tire model with fuzzy logic approach
    2008 34th Annual Conference of IEEE Industrial Electronics, 2008
    Co-Authors: Cong Geng, Lotfi Mostefai, Yoichi Hori
    Abstract:

    For effective implementation of observer for vehicle Body Slip Angle (beta) estimation in electric vehicle stability control, an empirical tire model with fuzzy logic approach is proposed, in which a local linearization approximation of the nonlinear tire model is adopted. Tire model parameters of front and rear tires cornering stiffness are identified based on the real vehicle experiments. Based on such modeling method, a hybrid-like observer is developed, in which the local observers are designed as linear observers with Kalman filter theory to overcome the influence of system noise for on-board application. Fuzzy logic approach is adopted to combine the local observer models so as to deal with the nonlinear nature of vehicle dynamics. By choosing the membership functions of weighting factors to be dependent on lateral acceleration and road friction coefficient, the proposed observer is adaptive to different running conditions. The effectiveness is verified by simulation and experimental studies.

Mouloud Denai - One of the best experts on this subject based on the ideXlab platform.

  • 2009 “Direct yaw moment control of an in-wheel-motored electric vehicle based on Body Slip Angle fuzzy observer
    2014
    Co-Authors: Cong Geng, Lotfi Mostefai, Mouloud Denai, Yoichi Hori
    Abstract:

    Abstract—A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based Body Slip Angle (β) ob-server. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi–Sugeno-like fuzzy models. Initially, local equivalent vehicle models are built using the lin-ear approximations of vehicle dynamics for low and high lateral acceleration operating regimes, respectively. The optimal β ob-server is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall control system by using fuzzy rules. These fuzzy rules represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism for the fuzzy membership functions has been incorporated to improve the accuracy and performance of the system. The effectiveness of this design approach has been demonstrated in simulations and in a real-time experimental setting. Index Terms—Fuzzy observer, local modeling, state feedback, vehicle lateral dynamics. I

  • lmi design of a direct yaw moment robust controller based on adaptive Body Slip Angle observer for electric vehicles
    International review of automatic control, 2013
    Co-Authors: L Mostefai, Mouloud Denai, Khatir Tabti, Zemalache K Meguenni, M Tahar
    Abstract:

    A stabilizing observer based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based Body Slip Angle (β) observer. In the design strategy of the fuzzy observer, the vehicle dynamics are represented by local models. Initially, local equivalent vehicle models have been built using linear approximations of vehicle dynamics respectively for low and high lateral acceleration operating regimes. The optimal β observer is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall controlled system by using fuzzy rules. These fuzzy rules consequently represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism has been introduced within the fuzzy design and incorporated to improve the accuracy and performance of the controlled system. The controller can then be robustly synthesized based on Linear Matrix Inequalities and using the deviation states model. The controller-observer pair gives good performances in term of stability and presents convincing advantages regarding the real-time implementation issues. The effectiveness of this design approach has been demonstrated in simulations and using real-time experimental data.

  • direct yaw moment control of an in wheel motored electric vehicle based on Body Slip Angle fuzzy observer
    IEEE Transactions on Industrial Electronics, 2009
    Co-Authors: Cong Geng, Lotfi Mostefai, Mouloud Denai, Yutaka Hori
    Abstract:

    A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based Body Slip Angle (beta) observer. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi-Sugeno-like fuzzy models. Initially, local equivalent vehicle models are built using the linear approximations of vehicle dynamics for low and high lateral acceleration operating regimes, respectively. The optimal beta observer is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall control system by using fuzzy rules. These fuzzy rules represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism for the fuzzy membership functions has been incorporated to improve the accuracy and performance of the system. The effectiveness of this design approach has been demonstrated in simulations and in a real-time experimental setting.

Yutaka Hori - One of the best experts on this subject based on the ideXlab platform.

  • direct yaw moment control of an in wheel motored electric vehicle based on Body Slip Angle fuzzy observer
    IEEE Transactions on Industrial Electronics, 2009
    Co-Authors: Cong Geng, Lotfi Mostefai, Mouloud Denai, Yutaka Hori
    Abstract:

    A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based Body Slip Angle (beta) observer. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi-Sugeno-like fuzzy models. Initially, local equivalent vehicle models are built using the linear approximations of vehicle dynamics for low and high lateral acceleration operating regimes, respectively. The optimal beta observer is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall control system by using fuzzy rules. These fuzzy rules represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism for the fuzzy membership functions has been incorporated to improve the accuracy and performance of the system. The effectiveness of this design approach has been demonstrated in simulations and in a real-time experimental setting.

  • Experimental demonstration of Body Slip Angle control based on a novel linear observer for electric vehicle
    31st Annual Conference of IEEE Industrial Electronics Society 2005. IECON 2005., 2005
    Co-Authors: Y. Aoki, Toshiyuki Uchida, Yutaka Hori
    Abstract:

    In this paper, a Body Slip Angle observer based on yaw rate /spl gamma/ and side acceleration a/sub y/, and a novel control method of Body Slip Angle /spl beta/ are proposed. Body Slip Angle observer is robust against parameter variation and change of road. Some experimental results by UOT MarchII (Fig.1) are shown to verify the effectiveness of the proposed observer. Next, we proposed new control methods for 2-dimension control. We control beta by yaw moment with PID controller. This method is known as DYC (direct yaw moment control) in internal combustion engine vehicles (ICVs). However, the torque difference can be generated directly with in-wheel motors. We performed experiments by UOT MarchII. The experimental results proved that our proposed method was good.

M Tahar - One of the best experts on this subject based on the ideXlab platform.

  • lmi design of a direct yaw moment robust controller based on adaptive Body Slip Angle observer for electric vehicles
    International review of automatic control, 2013
    Co-Authors: L Mostefai, Mouloud Denai, Khatir Tabti, Zemalache K Meguenni, M Tahar
    Abstract:

    A stabilizing observer based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based Body Slip Angle (β) observer. In the design strategy of the fuzzy observer, the vehicle dynamics are represented by local models. Initially, local equivalent vehicle models have been built using linear approximations of vehicle dynamics respectively for low and high lateral acceleration operating regimes. The optimal β observer is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall controlled system by using fuzzy rules. These fuzzy rules consequently represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism has been introduced within the fuzzy design and incorporated to improve the accuracy and performance of the controlled system. The controller can then be robustly synthesized based on Linear Matrix Inequalities and using the deviation states model. The controller-observer pair gives good performances in term of stability and presents convincing advantages regarding the real-time implementation issues. The effectiveness of this design approach has been demonstrated in simulations and using real-time experimental data.