Jerk Information Research Articles

Hysteresis Modeling and Compensation of Piezoelectric Actuators Using Gaussian Process with High-Dimensional Input

Rate-dependent hysteresis seriously deteriorates the positioning accuracy of the piezoelectric actuators, especially when tracking high-frequency signals. As a widely-used nonparametric Bayesian method, the Gaussian process (GP) has proven its effectiveness in nonlinear hysteresis modeling. In this paper, the dimension of the input to the GP model is extended to consider more dynamic features of the tracking signal so as to improve the rate-dependent hysteresis modeling accuracy. In contrast with the traditional training set containing only the position and speed information, the acceleration and jerk information, as well as their temporal distribution information, is also included in the input of the model. An inverse hysteresis compensator (IHC) is established in the same way, and open-loop and closed-loop controllers are developed by using the IHC. Experimental results on a PEA stage show that with the increase in the input dimension, the hysteresis modeling accuracy improves greatly and, thus, the controllers based on IHC can achieve a better tracking performance.

車両横加加速度に基づくヨーモーメント制御手法の検討(第4報)実車試験によるダブルレーンチェンジ操作に対する効果検証

車両横加加速度に基づくヨーモーメント制御手法の検討(第4報)実車試験によるダブルレーンチェンジ操作に対する効果検証

車両横加加速度に基づくヨーモーメント制御手法の検討（第3 報）

車両横加加速度に基づくヨーモーメント制御手法の検討（第3 報）

A yaw-moment control method based on a vehicle's lateral jerk information

Previously, a new control concept called ‘G-vectoring control (GVC)’ to improve vehicle agility and stability was developed. GVC is an automatic longitudinal acceleration control method that responds to vehicle lateral jerk caused by the driver's steering manoeuvres. In this paper, a new yaw-moment control method, which generates a stabilising moment during the GVC command and has positive acceleration value and the driver's accelerator pedal input is zero, was proposed. A new hybrid control, which comprises GVC, electric stability control and this new control, was constructed, and it was installed in a test vehicle and tested on a snowy surface. The very high potential for improvement in both agility and stability was confirmed.

Study on Yaw-moment Control Method Based on Vehicle Lateral Jerk Information (Second Report)

Study on Yaw-moment Control Method Based on Vehicle Lateral Jerk Information (Second Report)

Improvement in vehicle agility and stability by G-Vectoring control

We extracted a trade-off strategy between longitudinal traction/braking force and cornering force by using jerk information through observing an expert driver's voluntary braking and turning action. Using the expert driver's strategy, we developed a new control concept, called ‘G-Vectoring control’, which is an automatic longitudinal acceleration control (No DYC) in accordance with the vehicle's lateral jerk caused by the driver's steering manoeuvres. With the control, the direction of synthetic acceleration (G) changes seamlessly (i.e. vectoring). The improvements in vehicle agility and stability were evaluated by theoretical analysis and through computer simulation. We then introduced a ‘G-Vectoring’ equipped test vehicle realised by brake-by-wire technology and executed a detailed examination on a test track. We have confirmed that the vehicle motion in view of both handling and ride quality has improved dramatically.

A Contribution to Jerk Detection

AbstractIn technical applications the jerk information will be used for i.a. motion control, comfort evaluation or prediction of acceleration. In the majority of cases the jerk will be determined indirectly by differentiation of measured acceleration signals and depends consequently on the acceleration signals' quality and the differentiation's algorithms. An accurate jerk determination can only be realized by using an appropriate filter with respect to the relevant frequency range. In order to avoid such limitation a method of direct jerk detection will be required. Based on a 2 DOF mass system with viscous coupling a possible method was presented in [1] to detect directly the jerk. Thereby, in certain conditions the jerk is proportional to the displacement of one mass. Another method of direct jerk detection is given implicitly in [2]. With this method the jerk information will be generated by an additional inner variable of a damped single mass system based on the fundamental idea of the Mesoscopic Particle Method [3]. Both presented methods will be investigated and evaluated regarding its limits of applicability as a result of arbitrary periodical and impact‐like excitations. (© 2009 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Proposal of the longitudinal driver model in coordination with vehicle lateral motion based upon jerk information : A driver model derived from voluntary driving that has vehicle dynamic rationality

Proposal of the longitudinal driver model in coordination with vehicle lateral motion based upon jerk information : A driver model derived from voluntary driving that has vehicle dynamic rationality

An experimentally confirmed driver longitudinal acceleration control model combined with vehicle lateral motion

Some approaches to emulating an expert driver's longitudinal and lateral integrated control using jerk information are studied in this paper. A trade-off strategy between longitudinal traction versus cornering traction was extracted experimentally by using jerk information to observe voluntary braking and turning during driving. The strategy is realised by determining the longitudinal acceleration command during combination motion by vehicle lateral jerk. The vehicle dynamical rationality of the method is also evaluated by computer simulation in view of instantaneous handling characteristics. Applying the strategy, we made a longitudinal driver model that works in coordination with any steering input. Adopting a programmed handling model and a preview-follower model for the steering input, we carried out computer simulation. We also carried out cornering and braking lane-change experiments with an expert driver. The simulation results and experimental results agree well and we confirm that the model can emulate a certain part of the expert driver's control strategy for trading off longitudinal and lateral accelerations.

Understanding and Evaluation of Driver and Vehicle Dynamic Characteristics based upon Jerk Information

Understanding and Evaluation of Driver and Vehicle Dynamic Characteristics based upon Jerk Information

Proposal of the Longitudinal Driver Model in Coordination with Vehicle Lateral Motion based upon Jerk Information

Proposal of the Longitudinal Driver Model in Coordination with Vehicle Lateral Motion based upon Jerk Information

A Study of Motion Evaluation and Control Systems using Jerk Information. 1st Report, A Jerk Sensor and its application to Vehicle Motion Control Systems.

The jerk (the time rate of change of acceleration) is one of the most important kinds of bodily sensitive information. In driving situation, when a vehicle accelerates or decelerates rapidly, skilled drivers can adaptively control the vehicle by perceiving wheel spin or wheel lock from subtle vehicle jerk information, rather than from wheel-speed information. This suggests that the performance of vehicle motion control systems, including the extent of "natural" feeling for drivers, can be improved by enabling the systems to detect jerk and/or acceleration information, and emulate responses of a skilled driver. We have developed a sensor for deriving the values of both acceleration and jerk by using the law of electromagnetic induction. This sensor performs well and has several potential applications. This paper introduces the principle and performance of jerk sensor, and also proposes other possibility of motion control systems using jerk information.