The Experts below are selected from a list of 108 Experts worldwide ranked by ideXlab platform
Kazuhiro Kosuge - One of the best experts on this subject based on the ideXlab platform.
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control of a four wheel independently driven electric vehicle with a large sideslip Angle
Robotics and Biomimetics, 2014Co-Authors: Hiroshi Nakano, Jun Kinugawa, Kazuhiro KosugeAbstract:Herein, we propose a motion-control algorithm for a vehicle with a large sideslip Angle. The proposed algorithm is designed on the basis of the planar motion of the vehicle using a four-wheel vehicle model. The proposed algorithm controls the vehicle velocity, sideslip Angle of the vehicle, and yaw rate of the vehicle using the driving forces of the four-wheels and Steer Angle of the front wheels as control inputs. The proposed method is implemented in a simulation and in an experimental system, and the results show the effectiveness of the proposed method.
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Control of an electric vehicle with a large sideslip Angle using driving forces of four independently-driven wheels and Steer Angle of front wheels
2014 IEEE ASME International Conference on Advanced Intelligent Mechatronics, 2014Co-Authors: Hiroshi Nakano, Jun Kinugawa, Ken Okayama, Kazuhiro KosugeAbstract:This paper proposes a motion control scheme for an electric vehicle with a large sideslip Angle. The scheme employs the driving forces of the four independently driven wheels and the Steer Angle of the front wheels. The proposed control algorithm is derived in two steps based on a planar vehicle dynamics with four wheels. First, a control algorithm is derived for the control of forward velocity and yaw rate based on vehicle dynamics. This algorithm describes forward translational motion and yaw rotational motion using redundant driving forces generated by the four wheels as control inputs. Second, a control algorithm for the sideslip Angle of the vehicle is derived based on lateral translational motion dynamics of the vehicle using the Steer Angle of the front wheels as an input. The proposed control algorithm is implemented in a small experimental vehicle, and experimental results illustrate the effectiveness of the proposed motion control scheme.
M. Depoorter - One of the best experts on this subject based on the ideXlab platform.
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Lateral displacement sensor placement and forward velocity effects on stability of lateral control of vehicles
Proceedings of the 1997 American Control Conference (Cat. No.97CH36041), 1997Co-Authors: A. Alleyne, M. DepoorterAbstract:This paper presents both a simulation and experimental look at lateral vehicle dynamics for automatic Steering control. Simulation work shown is based upon the well known "bicycle model". Experimental work is completed on a small-scale vehicle run on the Illinois Roadway Simulator (IRS). Frequency and time domain methods are used to model the vehicle for various sensor locations and forward speeds. The resulting model is a polynomial transfer function from front Steer Angle input to lateral displacement output. The trends of the bicycle model appear in the experimental vehicle both in pole and zero mapping. In addition, the Steering actuator of the vehicle is shown to be a significant factor for model reference and PI based control design.
Jeffrey V Caulk - One of the best experts on this subject based on the ideXlab platform.
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experimental and theoretical performance of a particle velocity vector sensor in a hybrid acoustic beamformer
2009Co-Authors: Jeffrey V CaulkAbstract:Abstract : Acoustic measurements have traditionally relied exclusively on sound pressure sensors. This research investigated the performance of Microflown 3D hybrid pressure and acoustic particle velocity sensors in a linear array. Each Microflown sensor has three output channels proportional to the acoustic particle velocity in the three, nominally orthogonal, directions in addition to an output from an omnidirectional pressure microphone. The linear array was formed with a conventional omnidirectional microphone as the center element and two Microflown sensors located 17.2cm away on either side. The Microflown acoustic particle velocity channels were characterized first by the amplitude and phase relationship of their transfer functions relative to their co-located pressure microphone. The transfer function between the Microflown pressure hydrophones and the conventional center microphone was also measured. This enabled the amplitude and phase of all channels to be expressed relative to the center microphone signal. Beamforming was carried out in the frequency domain by applying the appropriate weight and phase delay for the desired Steer Angle. The bandwidth of the beamformer was limited from about 300Hz to 1.5kHz. At lower frequencies, insufficient signal to noise limited the coherence required to establish the transfer functions while at higher frequencies the phase of the particle velocity transfer functions grew increasingly sensitive to orientation Angle. Experiments carried out in the Naval Postgraduate School Anechoic Chamber using single and multiple acoustic sources compared extremely well to the theoretical performance. The addition of hybrid pressure and particle velocity sensors proved successful in eliminating the bearing ambiguity inherent in a linear array of omnidirectional sensors with no change in orientation, no complicated post-processing and no additional time expended.
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experimental and theoretical performance of a particle velocity vector sensor in a hybrid acoustic beamformer
2009Co-Authors: Jeffrey V CaulkAbstract:Abstract : Acoustic measurements have traditionally relied exclusively on sound pressure sensors. This research investigated the performance of Microflown 3D hybrid pressure and acoustic particle velocity sensors in a linear array. Each Microflown sensor has three output channels proportional to the acoustic particle velocity in the three, nominally orthogonal, directions in addition to an output from an omnidirectional pressure microphone. The linear array was formed with a conventional omnidirectional microphone as the center element and two Microflown sensors located 17.2cm away on either side. The Microflown acoustic particle velocity channels were characterized first by the amplitude and phase relationship of their transfer functions relative to their co-located pressure microphone. The transfer function between the Microflown pressure hydrophones and the conventional center microphone was also measured. This enabled the amplitude and phase of all channels to be expressed relative to the center microphone signal. Beamforming was carried out in the frequency domain by applying the appropriate weight and phase delay for the desired Steer Angle. The bandwidth of the beamformer was limited from about 300Hz to 1.5kHz. At lower frequencies, insufficient signal to noise limited the coherence required to establish the transfer functions while at higher frequencies the phase of the particle velocity transfer functions grew increasingly sensitive to orientation Angle. Experiments carried out in the Naval Postgraduate School Anechoic Chamber using single and multiple acoustic sources compared extremely well to the theoretical performance. The addition of hybrid pressure and particle velocity sensors proved successful in eliminating the bearing ambiguity inherent in a linear array of omnidirectional sensors with no change in orientation, no complicated post-processing and no additional time expended.
Hiroshi Nakano - One of the best experts on this subject based on the ideXlab platform.
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control of a four wheel independently driven electric vehicle with a large sideslip Angle
Robotics and Biomimetics, 2014Co-Authors: Hiroshi Nakano, Jun Kinugawa, Kazuhiro KosugeAbstract:Herein, we propose a motion-control algorithm for a vehicle with a large sideslip Angle. The proposed algorithm is designed on the basis of the planar motion of the vehicle using a four-wheel vehicle model. The proposed algorithm controls the vehicle velocity, sideslip Angle of the vehicle, and yaw rate of the vehicle using the driving forces of the four-wheels and Steer Angle of the front wheels as control inputs. The proposed method is implemented in a simulation and in an experimental system, and the results show the effectiveness of the proposed method.
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Control of an electric vehicle with a large sideslip Angle using driving forces of four independently-driven wheels and Steer Angle of front wheels
2014 IEEE ASME International Conference on Advanced Intelligent Mechatronics, 2014Co-Authors: Hiroshi Nakano, Jun Kinugawa, Ken Okayama, Kazuhiro KosugeAbstract:This paper proposes a motion control scheme for an electric vehicle with a large sideslip Angle. The scheme employs the driving forces of the four independently driven wheels and the Steer Angle of the front wheels. The proposed control algorithm is derived in two steps based on a planar vehicle dynamics with four wheels. First, a control algorithm is derived for the control of forward velocity and yaw rate based on vehicle dynamics. This algorithm describes forward translational motion and yaw rotational motion using redundant driving forces generated by the four wheels as control inputs. Second, a control algorithm for the sideslip Angle of the vehicle is derived based on lateral translational motion dynamics of the vehicle using the Steer Angle of the front wheels as an input. The proposed control algorithm is implemented in a small experimental vehicle, and experimental results illustrate the effectiveness of the proposed motion control scheme.
Stefano Melzi - One of the best experts on this subject based on the ideXlab platform.
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On the vehicle sideslip Angle estimation through neural networks: Numerical and experimental results
Mechanical Systems and Signal Processing, 2011Co-Authors: Stefano Melzi, Edoardo SabbioniAbstract:Abstract Stability control systems applying differential braking to inner/outer tires are nowadays a standard for passenger car vehicles (ESP, DYC). These systems assume as controlled variables both the yaw rate (usually measured on board) and the sideslip Angle. Unfortunately this latter quantity can directly be measured only through very expensive devices however unsuitable for ordinary vehicle implementation and thus it must be estimated. Several state observers eventually adapting the parameters of their reference vehicle models have been developed at the purpose. However sideslip Angle estimation is still an open issue. In order to avoid problems concerned with reference model parameters identification/adaptation, a layered neural network approach is proposed in this paper to estimate the sideslip Angle. Lateral acceleration, yaw rate, speed and Steer Angle which can be acquired by ordinary sensors are used as inputs. The design of the neural network and the definition of the manoeuvres constituting the training set have been gained by means of numerical simulations with a 7 d.o.f.s vehicle model. Performance and robustness of the implemented neural network have subsequently been verified by post-processing the experimental data acquired with an instrumented vehicle and referred to several handling manoeuvres (step-Steer, power on, double lane change, etc.) performed on various road surfaces. Results generally show a good agreement between the estimated and the measured sideslip Angle.
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A methodology for vehicle sideslip Angle identification: comparison with experimental data
Vehicle System Dynamics, 2007Co-Authors: Federico Cheli, Edoardo Sabbioni, M. Pesce, Stefano MelziAbstract:Sideslip Angle could provide important information concerning vehicle's stability. Unfortunately direct measurement of sideslip Angle requires a complex and expensive experimental set-up, which is not suitable for implementation on ordinary passenger cars; thus, this quantity has to be estimated starting from the measurements of vehicle lateral/longitudinal acceleration, speed, yaw rate and Steer Angle. According to the proposed methodology, sideslip Angle is estimated as a weighted mean of the results provided by a kinematic formulation and those obtained through a state observer based on vehicle single-track model. Kinematical formula is considered reliable for a transient manoeuvre, while the state observer is used in nearly quasi-state condition. The basic idea of the work is to make use of the information provided by the kinematic formulation during a transient manoeuvre to update the single-track model parameters (tires cornering stiffnesses). A fuzzy-logic procedure was implemented to identify stea...
