Modelling and model predictive control for a bicycle-rider system

This study proposes a bicycle-rider control model based on model predictive control (MPC). First, a bicycle-rider model with leaning motion of the rider’s upper body is developed. The initial simulation data of the bicycle rider are then used to identify the linear model of the system in state-space form for MPC design. Control characteristics of the proposed controller are assessed by simulating the roll-angle tracking control. In this riding task, the MPC uses steering and leaning torques as the control inputs to control the bicycle along a reference roll angle. The simulation results in different cases have demonstrated the applicability and performance of the MPC for bicycle-rider modelling.     

Handling Capabilities of Vehicles in Emergencies Using Coordinated AFS and ARMC Systems

In this paper, an advanced control technique that can be implemented in hard emergency situations of vehicles is introduced. This technique suggests integration between Active Front Steering (AFS) and Active Roll Moment Control (ARMC) systems in order to enhance the vehicle controllability. For this purpose, the AFS system applies a robust sliding mode controller (SMC) that is designed to influence the steering input of the driver by adding a correction steering angle for maintaining the vehicle yaw rate under control all the time. The AFS system is then called active-correction steering control. The ARMC system is designed to differentiate the front and rear axles' vertical suspension forces in order to alter the vehicle yaw rate and to eliminate the vehicle roll motion as well. Moreover, the operation of the SMC is based on tracking the behavior of a nonlinear 2-wheel model of 2-DOF used as a reference model. The 2-wheel model incorporates real tire characteristics, which can be inferred by the use of trained neural networks. The results clearly demonstrate the enhanced characteristics of the proposed control technique. The SMC with the assistance of the ARMC provides less correction of the steering angle and accordingly reduces the possibility of occurrence of the saturation phenomenon that is likely to take place in the operation of the SMC systems.     

Handling Capabilities of Vehicles in Emergencies Using Coordinated AFS and ARMC Systems

In this paper, an advanced control technique that can be implemented in hard emergency situations of vehicles is introduced. This technique suggests integration between Active Front Steering (AFS) and Active Roll Moment Control (ARMC) systems in order to enhance the vehicle controllability. For this purpose, the AFS system applies a robust sliding mode controller (SMC) that is designed to influence the steering input of the driver by adding a correction steering angle for maintaining the vehicle yaw rate under control all the time. The AFS system is then called active-correction steering control. The ARMC system is designed to differentiate the front and rear axles' vertical suspension forces in order to alter the vehicle yaw rate and to eliminate the vehicle roll motion as well. Moreover, the operation of the SMC is based on tracking the behavior of a nonlinear 2-wheel model of 2-DOF used as a reference model. The 2-wheel model incorporates real tire characteristics, which can be inferred by the use of trained neural networks. The results clearly demonstrate the enhanced characteristics of the proposed control technique. The SMC with the assistance of the ARMC provides less correction of the steering angle and accordingly reduces the possibility of occurrence of the saturation phenomenon that is likely to take place in the operation of the SMC systems.     

High-speed optimal steering of a tractor–semitrailer

A high-speed optimal trailer steering controller for a tractor–semitrailer is discussed. A linear model of a tractor–semitrailer with steered trailer axles is described, and an optimal trailer steering controller is introduced. A path-following controller is derived to minimise the path-tracking error in steady-state manoeuvres using active trailer steering. A roll stability controller is introduced by adding the lateral acceleration of trailer centre of gravity as another objective in the steering controller, so as to improve roll stability in transient manoeuvres. A strategy to switch between these two control modes is demonstrated. Simulation results show that the steering controller can ensure good path tracking of articulated vehicles in steady-state manoeuvres and improve roll stability significantly in transient manoeuvres, while maintaining the path-tracking deviation within an acceptable range. Tests with an experimental tractor–semitrailer equipped with a high-bandwidth active steering system validate the controller design and simulation results. The roll stability controller reduces the measured rearward amplification by 27%.     

A nonlinear model of bicycle shimmy

This paper presents a nonlinear model accurately describing, both qualitatively and quantitatively, the onset and dynamics of bicycle shimmy. Methods of nonlinear dynamics, such as numerical continuation and bifurcation analysis, show that the model exhibits two stable periodic motions found experimentally in on-road tests: the weave and wobble (or shimmy) mode. The modelling results are compared with experimental data collected by riding a racing bicycle downhill at high speeds with hands on the handlebar. The model predicts with surprising accuracy the amplitudes and frequencies of the oscillations, the longitudinal velocity at which they occur, as well as the substantial independence of wobble frequency and amplitude from the forward speed. The lateral acceleration of the upper tube of the frame near the steering axis reaches 5–10?g, both in the model and in the data. The analysis shows that wobble onset and amplitude is particularly sensitive to changes in the torsional stiffness of the frame and strongly depends on tyre lateral force and aligning torque at the wheel–road contact point. It also allows to quantify the additional viscous rotary damping that should be added to the steering assembly to prevent wobble.     

An optimal model-based trajectory following architecture synthesising the lateral adaptive preview strategy and longitudinal velocity planning for highly automated vehicle

Automated driving has received a broad of attentions from the academia and industry, since it is effective to greatly reduce the severity of potential traffic accidents and achieve the ultimate automobile safety and comfort. This paper presents an optimal model-based trajectory following architecture for highly automated vehicle in its driving tasks such as automated guidance or lane keeping, which includes a velocity-planning module, a steering controller and a velocity-tracking controller. The velocity-planning module considering the optimal time-consuming and passenger comforts simultaneously could generate a smooth velocity profile. The robust sliding mode control (SMC) steering controller with adaptive preview time strategy could not only track the target path well, but also avoid a big lateral acceleration occurred in its path-tracking progress due to a fuzzy-adaptive preview time mechanism introduced. In addition, an SMC controller with input–output linearisation method for velocity tracking is built and validated. Simulation results show this trajectory following architecture are effective and feasible for high automated driving vehicle, comparing with the Driver-in-the-Loop simulations performed by an experienced driver and novice driver, respectively. The simulation results demonstrate that the present trajectory following architecture could plan a satisfying longitudinal speed profile, track the target path well and safely when dealing with different road geometry structure, it ensures a good time efficiency and driving comfort simultaneously.     

Path-following in model predictive rollover prevention using front steering and braking

In this paper vehicle path-following in the presence of rollover risk is investigated. Vehicles with high centre of mass are prone to roll instability. Untripped rollover risk is increased in high centre of gravity vehicles and high-friction road condition. Researches introduce strategies to handle the short-duration rollover condition. In these researches, however, trajectory tracking is affected and not thoroughly investigated. This paper puts stress on tracking error from rollover prevention. A lower level model predictive front steering controller is adopted to deal with rollover and tracking error as a priority sequence. A brake control is included in lower level controller which directly obeys an upper level controller (ULC) command. The ULC manages vehicle speed regarding primarily tracking error. Simulation results show that the proposed control framework maintains roll stability while tracking error is confined to predefined error limit.     

Roll stabilisation of road vehicles using a variable stiffness suspension system

A variable stiffness architecture is used in the suspension system to counteract the body roll moment, thereby enhancing the roll stability of the vehicle. The variation of stiffness concept uses the ‘reciprocal actuation’ to effectively transfer energy between a vertical traditional strut and a horizontal oscillating control mass, thereby improving the energy dissipation of the overall suspension. The lateral dynamics of the system is developed using a bicycle model. The accompanying roll dynamics are also developed and validated using experimental data. The positions of the left and right control masses are sequentially allocated to reduce the effective body roll and roll rate. Simulation results show that the resulting variable stiffness suspension system has more than 50% improvement in roll response over the traditional constant stiffness counterparts. The simulation scenarios examined is the fishhook manoeuvre.     

基于全桥半桥切换的EPS系统滑模控制的分析与设计

基于建立的电动助力转向系统(EPS)动态模型,以电动助力转向系统为研究对象,首先分析EPS系统的功率驱动电路的两种驱动方式,分析了全桥、半桥功率驱动原理,推导出平均电流表达式,并依此设计了全桥、半桥切换器。根据滑模控制的基本原理,利用EPS系统中助力电机的模型,设计出一种简单实用的滑模控制器。仿真和试验结果表明,该控制器有很好的控制效果,克服了传统控制器不能很好解决系统中的非线性的问题,使得EPS系统具有很好的动态性能。     

Gaussian Process Regression Feedforward Controller for Diesel Engine Airpath

Gaussian Process Regression (GPR) provides emerging modeling opportunities for diesel engine control. Recent serial production hardwares increase online calculation capabilities of the engine control units. This paper presents a GPR modeling for feedforward part of the diesel engine airpath controller. A variable geotmetry turbine (VGT) and an exhaust gas recirculation (EGR) valve outer loop controllers are developed. The GPR feedforward models are trained with a series of mapping data with physically related inputs instead of speed and torque utilized in conventional control schemes. A physical model-free and calibratable controller structure is proposed for hardware flexibility. Furthermore, a discrete time sliding mode controller (SMC) is utilized as a feedback controller. Feedforward modeling and the subsequent airpath controller (SMC+GPR) are implemented on the physical diesel engine model and the performance of the proposed controller is compared with a conventional PID controller with table based feedforward.     

System identification and attitude control of motorcycle by computer-aided dynamics analysis

System identification of the motorcycle model constructed by computer-aided dynamics analysis is introduced to design a control system for attitude stabilization of the motorcycle. The identified model can be reduced to the coupled mode system between the roll and the front steering. The front-steering control system using the roll angle is designed by H_∞ control theory, based on the reduced-order model and the full-order model, respectively. It is verified from simulation results that the motorcycle attitude against disturbance is stabilized by the H_∞ controller, and that the reduced-order controller exhibits efficient stabilization performance in comparison with the full-order controller.     

On the wobble mode of a bicycle

Wheel shimmy and wobble are well-known dynamic phenomena at automobiles, aeroplanes and motorcycles. In particular, wobble at the motorcycle is an (unstable) eigenmode with oscillations of the wheel about the steering axis, and it is no surprise that unstable bicycle wobble is perceived unpleasant or may be dangerous, if not controlled by the rider in time. Basic research on wobble at motorcycles within the last decades has revealed a better understanding of the sudden onset of wobble, and the complex relations between parameters affecting wobble have been identified. These fundamental findings have been transferred to bicycles. As mass distribution and inertial properties, rider influence and lateral compliances of tyre and frame differ at bicycle and motorcycle, models to represent wobble at motorcycles have to prove themselves, when applied to bicycles. For that purpose numerical results are compared with measurements from test runs, and parametric influences on the stability of the wobble mode at bicycles have been evolved. All numerical analysis and measurements are based on a specific test bicycle equipped with steering angle sensor, wheel-speed sensor, global positioning system (GPS) 3-axis accelerometer, and 3-axis angular velocity gyroscopic sensor.     

Development of control logic for hydraulic active roll control system

Developed in this research is a control logic for the ARC (Active Roll Control) system that uses rotary-type hydraulic stabilizer actuators at the front and rear axles. The hydraulic components of the system were modeled in detail using AMESim, and a driving logic for the hydraulic circuit was constructed based upon the model. The performance of the driving logic was evaluated on a test bench, and it demonstrated good pressure tracking capability. The control logic was then designed with the target of reducing the roll motion of the vehicle during cornering. The control logic consists of two parts: a feedforward controller that generates anti-roll moments in response to the centrifugal force, and a feedback controller that generates anti-roll moments in order to make the roll angle to follow its target value. The developed ARC logic was evaluated on a test vehicle under various driving conditions including a slowly accelerated circular motion and a sinusoidal steering. Through the test, the ARC system demonstrated successful reduction of the roll motion under all conditions, and any discomfort due to the control delay was not observed even at a fast steering maneuver.     

Identification of linear handling models for road vehicles

This study reports the identification of linear handling models for road vehicles starting from structural identifiability analysis, continuing with the experiments to acquire data on a vehicle equipped with a sensor set and data acquisition system, and ending with the estimation of parameters using the collected data. The model structure originates from the well-known linear bicycle model that is frequently used in handling analysis of road vehicles. Physical parameters of the bicycle model structure are selected as the unknown parameter set that is to be identified. Global identifiability of the model structure is analysed, in detail, and concluded according to various available sensor sets. Physical parameters of the bicycle model structure are estimated using prediction error estimation method. Genetic algorithms are used in the optimisation phase of the identification algorithm to overcome the difficulty in the selection of initial values for parameter estimates. Validation analysis of the identified model is also presented. The identified model is shown to track the system response successfully.     

Roll angle estimator based on angular rate measurements for bicycles

ABSTRACT

Measuring the roll angle of single-track vehicles has always been a challenging task; however, accurate and reliable measurements of this magnitude are paramount for controlling the stability of these vehicles, both for autonomous riding and for safety reasons. A roll angle estimation is also useful in other situations, such as tests to perform the identification of the parameters of the rider control. In this work, a new algorithm is presented for estimating the roll angle of bicycles. This estimator, based on the well-known Kalman filter, employs a wheel speed sensor to approximate the speed of the vehicle, and three angular rate sensors, which are currently small and affordable sensors. The proposed method was implemented in a microcontroller and tested in a bicycle and the results were compared with measurements obtained with optical sensors, showing a good correlation. Although it has not been tested in motorcycles, comparable results are expected.     

非拥挤路段自行车交通流特性研究

自行车是城市居民出行的主要方式之一，研究自行车交通流的特性对于合理规划道路交通资源，提高白行车交通服务水平具有重要意义。针对白行车交通流与机动车交通流的不同特征，提出了以单位面积车道上车辆集散程度定义白行车交通流密度的新方法，并基于调查数据，研究了非拥挤状态下自行车交通流密度、车速和流率3个参数的相关性，发现非拥挤自行车流的速度总是分布在接近期望车速的范围内，且与流率、密度无关，而速度的离散程度随着密度的增大而减小。最后，分析了车道、宽度与交通流3个参数的相关性，并建立了相应的回归模型，模型可用于在给定自行车交通需求以及服务水平条件下自行车道的设计宽度。     

一种汽车ESP仿真模型的研究

基于Pacejka的"魔术公式"轮胎模型,建立了包括汽车纵向与横向移动、横摆、侧倾和4个车轮的转动的8自由度动力学模型.设计了由汽车仿真模型和驱动系统、四通道制动系统、制动踏板、转向盘与油门踏板等实物以及控制器(ESP)等部分组成的半实物仿真平台.以侧向加速度与横摆角速度为仿真控制变量对模型进行仿真测试.仿真与实车测试数据相当接近,为ESP的研究提供了有效的模型.     

Study on the performance of active front steering system

The performance of a steering system equipped with active front steering (AFS) device is investigated with the consideration of AFS intervention and a proposed dynamic model. Firstly, the kinematics and dynamics of AFS are illustrated based on the mechanism of AFS with planetary gear set and a detailed dynamic model. Furthermore, a basic control on the voltage of DC motor at AFS actuator is proposed. It is realized by a proportional controller that the input is the difference of desired steering ratio and a conventional gear ratio. Finally, two numerical simulations are carried out. One is on-center handling test to demonstrate the basic characteristics of AFS. The other simulation is to demonstrate the effects of vehicle speed, frequency of steering input and AFS intervention on steering system performance. It is shown that the proposed AFS dynamic model is capable to simulate dynamic performance of AFS. The effect of AFS intervention on turning efforts at hand steering wheel is inevitable and the turning comfort is deteriorated to some extent.     

无人驾驶机器人车辆非线性模糊滑模车速控制

为了实现不同行驶工况下车速的精确、稳定控制,提出一种基于非线性干扰观测器的无人驾驶机器人车辆模糊滑模车速控制方法。考虑模型不确定性和外部干扰对车速控制的影响,建立车辆纵向动力学模型。通过分析无人驾驶机器人油门机械腿、制动机械腿的结构、机械腿操纵自动挡车辆踏板的运动,建立油门机械腿和制动机械腿的运动学模型。在此基础上,分别设计油门/制动切换控制器、油门模糊滑模控制器以及制动模糊滑模控制器,并进行控制系统的稳定性分析。油门/制动切换控制器以目标车速的导数为输入来进行油门与制动之间的切换控制。油门模糊滑模控制器和制动模糊滑模控制器以当前车速以及车速误差为输入,分别以油门机械腿直线电机位移和制动机械腿直线电机位移为输出来实现对油门与制动的控制。模糊滑模控制器中,为了减少控制抖振,滑模控制的反馈增益系数由模糊逻辑进行在线调节。模糊滑模控制器中的非线性干扰观测器用于估计和补偿无人驾驶机器人车辆的模型不确定性与外部干扰。仿真及试验结果对比分析表明：本文方法能够精确地估计和补偿无人驾驶机器人车辆的模型不确定性和外部干扰,避免了油门控制与制动控制之间的频繁切换,并实现了精确稳定的车速控制。