Wheel Control Research Articles

Continuous Identification of Driver Model Parameters via the Unscented Kalman Filter

Advanced Driver-Assistance Systems (ADAS) have become an essential part of modern cars. Among the solutions proposed, haptic shared control of the steering wheel is increasingly being studied. A fundamental question is how drivers adapt their behavior to these systems. This article proposes to use the Unscented Kalman Filter (UKF) to identify the variation over time in the psychological and neuromuscular parameters of a driver structured model. The goal here is to understand how the driver adapts to changes, whether regarding the behavior of the steering system, the visibility or the road conditions. The LPV system considered for identification is known as the cybernetic driver model. Two experiments carried out respectively with Simulink© and on a driving simulator provide the data. The methodology proposed for tuning the UKF is studied from the results obtained with those data. A multi-UKF strategy is also considered. The methodology reveals useful when a compromise between rapidity and precision has to be achieved for parameters estimation. It opens the way to a detailed analysis of the driver’s parameter variations within the multi-UKF framework.

Исследование быстродействия алгоритма управления малогабаритным космическим аппаратом с использованием двигателей-маховиков

The paper considers a mathematical model of spacecraft motion in quaternions, taking into account the control constraints on the kinetic and control torque of the reaction wheel. We analyzed current approaches to the search for reaction wheel control factors providing quasi-optimal performance. Boundary conditions for different types of reaction wheel control have been obtained analytically. Furthermore, we introduced our own approach to the study of the effective control coefficients of the two term controller of the reaction wheel. By means of the new approach, the maneuver was successfully analyzed without any control constraints on the kinetic and control torque of the reaction wheel, and the dependences of the control coefficients were obtained providing the required speed for the considered case. Findings of research show that the dependences of the control coefficients obtained provide the highest performance for any initial angles of rotation in comparison with the previously obtained theoretical dependences of the coefficients

Nonlinear Steering Wheel Angle Control Using Self-Aligning Torque with Torque and Angle Sensors for Electrical Power Steering of Lateral Control System in Autonomous Vehicles.

The development of sensor technology enabled the use of composite sensors to measure the torque and angle of steering wheels at gradually decreasing costs while maintaining the required safety. The electric power steering (EPS) is vital to the safety of the car, therefore it is not worth sacrificing safety to save cost and the SWA control with angle sensor gradually becomes the mainstream. Existing methods to control steering wheel angle (SWA) for EPS consider the self-aligning torque as a disturbance that should be rejected. However, this torque is useful to return the SWA from an outward to the center position. Hence, we propose a nonlinear control of SWA using the self-aligning torque for EPS in the lateral control system of autonomous vehicles. The proposed method consists of a high-gain disturbance observer and a backstepping controller, where the former aims to estimate the self-aligning torque, and an auxiliary state variable prevents using the derivative of the measured signal. The nonlinear controller is designed via backstepping to bound the SWA tracking error. The self-aligning torque provides damping that can improve the controller tracking when following the same direction of the input torque on the steering wheel control. In this case, the control input can be reduced by the damping effect of the self-aligning torque. The performance of the proposed method is validated through EPS hardware-in-the-loop simulation.

How Much Smart Is Too Much?: Exploring the Slow Adoption of New Consumer Technology

Today's proliferation of systems, devices, and things causes some severe side effects. The use cases of smart anything, although numerous, are often made very complex due to the abundance of devices required to enable those use cases. This causes a variety of human-machine interfaces (HMIs), which are by no means standardized, making the public adoption of consumer technology much harder than we might anticipate. Smart phones, tablets, and TVs introduce little commonality in user interfaces (UIs) regarding their openness and the variety of applications available. Our vehicles are offering us disconnected, proprietary infotainment systems and awkward input devices, including numerous buttons and touch, jog shuttle, and steering wheel controls. Smart gadgets and homes are among the most complicated both to install and use, as they still require considerable do-it-yourself (DIY) skills or the help of a trained professional. Furthermore, various new wearables now require users to attach electronics to their person-as if the stress of locating the smartphone before leaving the house is not enough on its own. Learning how to use all of these devices, making use of them, and weaving them into everyday life can be so cumbersome that we may stop adopting new solutions altogether. This has already started to happen. Let me attempt to qualify some reasons for the caveat. These come from two trouble-causing dilemmas. The first is integration versus differentiation (Figure 1).

Occupational fatal injuries associated with mobile hand-fed wood chippers.

Workers are killed every year in wood chipper-related incidents despite the repeated hazard warnings. In-depth, comprehensive, and up-to-date studies are needed to identify causal, risk, and contributing factors and assess the current control measures so that an effective and proactive prevention approach can be developed. Cases were identified from four online databases and manually reviewed to characterize and categorize the fatal events. The study identified 113 wood chipper-related worker deaths (1982-2016). The victims were killed in struck-by (57), caught-in (41), motor vehicle (7), electrical (4), fall (2), and heat stroke (2) incidents while performing chipper-related tasks. Chipper-related worker deaths are preventable. Young and inexperienced workers may be at higher risk for caught-in deaths. The current feed wheel control devices are not effective for workers to self-rescue. Fully automatic feed wheel stop devices are needed to prevent caught-in incidents.

On the Experimental Analysis of Integral Sliding Modes for Yaw Rate and Sideslip Control of an Electric Vehicle with Multiple Motors

With the advent of electric vehicles with multiple motors, the steady-state and transient cornering responses can be designed based on high-level reference targets, and implemented through the continuous torque control of the individual wheels, i.e., torque-vectoring or direct yaw moment control. The literature includes several papers describing the application of the sliding mode control theory to torque-vectoring. However, the experimental implementations of sliding mode controllers on real vehicle prototypes are very limited at the moment. More importantly, to the knowledge of the authors, there is lack of experimental assessments of the performance benefits of direct yaw moment control based on sliding modes, with respect to other controllers, such as the proportional integral derivative controllers or linear quadratic regulators currently used for stability control in production vehicles. This paper aims to reduce this gap by presenting an integral sliding mode controller for concurrent yaw rate and sideslip control. A new driving mode, the Enhanced Sport mode, is proposed, inducing sustained high values of sideslip angle, which can be safely limited to a specified threshold. The system is experimentally assessed on a four-wheel-drive electric vehicle along a wide range of maneuvers. The performance of the integral sliding mode controller is compared with that of a linear quadratic regulator during step steer tests. The results show that the integral sliding mode controller brings a significant enhancement of the tracking performance and yaw damping with respect to the more conventional linear quadratic regulator based on an augmented single-track vehicle model formulation.

Development of Handrim-Activated Power-Assist Wheelchair for Seniors and the Disabled

This paper presents a new handrim-activated power-assist wheelchair (HAPAW) for seniors and the disabled. The HAPAW has all the benefits of manual and electric wheelchairs and is being actively developed for use by the disabled and seniors, because of the global aging trend. The key technological components of a HAPAW are a sensor-embedded driving wheel mechanism for detecting user intention and a balancing algorithm for improved driving performance. In this work, a driving wheel mechanism with a simple non-contact user-intention-detection sensor composed of a magnet and Hall sensor was designed. In addition, a balancing algorithm that uses the measured torque and time difference for driving wheel control was applied. An HAPAW prototype incorporating the designed driving wheel and control algorithm was fabricated, and its performance was tested according to the electric wheelchair standards. In addition, to confirm the power-assist effect, the power-assist wheelchair energy consumption was measured separately for senior and disabled participants and compared with that for a manual wheelchair. Through performance testing and clinical testing, it was confirmed that the developed HAPAW can be successfully employed as an electric wheelchair, with improved driving performance and energy efficiency over those of a manual wheelchair.

LQR optimal control research for four-wheel steering forklift based-on state feedback

Taking the steering performance of four-wheel steering (4WS) forklift as the research object, based on two degrees of freedom (2DOF) model and three degree of freedom (3DOF) model of 4WS system, combined with the characteristics and steering requirements of forklift, the Linear Quadratic Regulator (LQR) optimization control algorithm based on state feedback is proposed, and the solution of LQR control algorithm for the 4WS forklift is presented. The simulation analyses of the steering performance of proportional control 4WS, LQR control 4WS and rear wheel steering (RWS) control are given. The simulation results show that the comprehensive effect of LQR optimal control is better, and it effectively improves the flexibility and the handling stability of 4WS forklift.

A Study on the Individual Control Method Comparing the Lateral Displacement Control of Front Wheel and Rear Wheel of IRWs System

This paper proposes an algorithm to obtain better results in the integrated control by reflecting the characteristics of the individual control of the front wheel and the rear wheel of tram systems. In the case of the surface transportation, which has recently been introduced, severely curved driving performance is required for the downtown. It is possible to decrease the curve radius and to improve the performance of the straight driving with the individual torque control. Therefore, the individual torque control performance of the motor is the most important point of the surface transportation. The front and rear wheels have different torque characteristics, and the length of the bogie during curve travel also affects these results. This system is more controllable than the system with 1Controller 4Motor (1C4M) in the form of 2C4M with the front and rear wheels being individually controlled, allowing more precise control because of its higher degree of freedom. Because of this individually controlled characteristic, it is possible to control more precisely in the integrated control considering the characteristics of the front wheel and the characteristics of the rear wheel. The validity of the proposed control algorithm is verified by experimental results using a small-scale bogie system.

Space Propulsion Technology for Small Spacecraft

As small satellites become more popular and capable, strategies to provide in-space propulsion increase in importance. Applications range from orbital changes and maintenance, attitude control and desaturation of reaction wheels to drag compensation and de-orbit at spacecraft end-of-life. Space propulsion can be enabled by chemical or electric means, each having different performance and scalability properties. The purpose of this review is to describe the working principles of space propulsion technologies proposed so far for small spacecraft. Given the size, mass, power, and operational constraints of small satellites, not all types of propulsion can be used and very few have seen actual implementation in space. Emphasis is given in those strategies that have the potential of miniaturization to be used in all classes of vehicles, down to the popular 1-L, 1-kg CubeSats and smaller.

Validation of a Mechanical Drive with Individual Wheel Control

Mobile-machine drivetrains are subject to high demands. In order to realize these requirements in the best possible way, KIT ’s Institute of Mobile Machines and its corporate partners has investigated a torque splitter drive for mobile machines. The successful validation of the component is followed by a validation in context of possible machine types by means of MOBiL, which is an XiL method adapted to mobile machines.

Model predictive control–based approach for assist wheel control of a multi-axle crane to improve steering efficiency and dynamic stability

This research deals with assist wheel control to improve the steering efficiency and dynamic stability of the multi-axle crane based on model predictive control. Since multi-axle crane has relatively high inertia and long distance between the axles, it has slow dynamic response, and thus, different steering strategies according to driving speed intervals are required. Specifically, the steering strategy is that the number of wheels fixed mechanically increases to secure dynamic stability as the driving speed increases. However, although this strategy enables to secure stability by slowing down the dynamic response, it also has a weakness to decrease the steering efficiency. If the steering efficiency is decreased, it may result in augmenting an accident rate due to an increase in driver’s fatigue. Therefore, this study suggests a new steering strategy to improve the steering efficiency by simultaneously guaranteeing dynamic stability. The suggested steering control algorithm can enhance both steering efficiency and stability by deriving an assist wheel control input based on model predictive control using a variable weighting factor derived from the driver’s steering input (steering angle on the first axle). Development and performance evaluation of the suggested algorithm were conducted in the MATLAB/Simulink environment, and evaluation results confirmed that the developed algorithm could both enhance the driver’s steering efficiency and secure dynamic stability.

Control Allocation Based on All Wheel Control in the Dynamic Control of Eight In-wheel Motor Drive Vehicle

Control Allocation based on all wheel control in the Dynamic Control of an eight in-wheel motor drive vehicle is studied in this paper which adopts the hierarchical control strategy and all the wheels are controllable(AWC), including the upper level controller and the lower level controller. The upper level controller calculates the target force (yaw moment) according to the vehicle motion states. And the lower level controller undertakes the distribution of the target force to each tire accordingly. Furthermore, the control system proposed in this paper integrates active steering with direct yaw moment control strategy. Through driver-in-loop simulation under certain conditions, the proposed control allocation is contrasted with the direct yaw moment control(DYC) which only take the longitudinal force into account when distribute the tire force. And the results show that the control allocation based on all wheel control(AWC) is better than traditional direct yaw moment control(DYC), especially in the field of trajectory following as well as in-wheel motor torque distribution.

Traction-energy balancing adaptive control with slip optimization for wheeled robots on rough terrain

On rough terrain, excessive wheel slippage is easily generated by changes of surface conditions such as soil types and geometries. It induces considerable loss of wheel traction and battery energy. To prevent this, wheeled robots should consistently recognize the current situation generated between wheel and surface. And also wheeled robots are required to optimally control wheel motion in limited wheel traction and battery capacity. Therefore, this paper proposes a novel wheel control algorithm based on slip optimization of traction and energy, which is adaptive to change of surface condition. Proposed wheel control algorithm is called Traction-Energy Balancing Adaptive Control (TEB) in this paper and TEB assigns optimized rotation speed to each wheel by observing wheel slip ratio which is a key parameter of TEB. As functions of TEB, TEB is largely divided into three main parts; (1) slip optimizer (2) slip controller (3) SC-compensator. In the slip optimizer, two optimal slip models were derived as a function of slip ratios regarding maximum traction and tractive efficiency using experimental data about wheel-terrain interaction in three types of soil (grass, gravel and sand). And the optimal slip models were employed in order to determine a desired slip value of wheel with observation of a change in actual robot velocity as control input in the slip controller. For optimal slip control, the proposed slip controller is based on conventional PID controller with compensating disturbance in the controller (SC-compensator) which occurs by change of surface shapes. In the SC-compensator, radial function networks (RBFN) was applied in the slip controller and RBFN was of help to readjust previously set PID gains depending on occurred slip error. Finally, TEB was experimentally verified by controlling a real robot having four wheels on various terrain types.

Inverse dynamics particle swarm optimization applied to constrained minimum-time maneuvers using reaction wheels

The paper deals with the problem of time-optimal spacecraft reorientation maneuvers by means of reaction wheels, with boundary and path constraints. When searching for solutions to optimal attitude-control problems, spacecraft can be easily modeled as controlled by external torques. However, when using actuators such as reaction wheels, conservation of the total angular momentum must be taken into account and the wheel dynamics must be included. A rest-to-rest slew maneuver is considered where an optical sensor cannot be exposed to sources of bright light such as the Earth, the Sun and the Moon. The motion must be constrained to prevent the sensor axis from entering into established keep-out cones. The minimum-time solution is proposed using the Inverse Dynamics Particle Swarm Optimization technique. The attitude and the kinematics of the satellite evolve, leading to the successive attainment of the wheel control input via fixed-step numerical integration. Numerical results are evaluated over different scenarios. It is established that the computation of minimum time maneuvers with the proposed technique leads to near optimal solutions, which fully satisfy all the boundary and path constraints. The ability to converge in a variety of different scenarios always requiring the same computational effort characterizes the proposed technique as a feasible future on-board path-planner.

Improving The Manoeuvrability of Electric Vehicle with Four-Wheel Drive and Four-Wheel Steering – A Nonlinear Model Vehicle Dynamics Approach

The dynamics motion of a vehicle is inherently a nonlinear dynamics system especially at high speed. Majority of past researches on four-wheel steering (4WS) vehicle adopt easier way of modelling a control system based on vehicle with linear dynamic equation of motion. This paper study on the vehicle dynamics of an electric vehicle with 4WD and 4WS based on nonlinear vehicle dynamic approach. A numerical simulation was performed to analyse the variance of a linear model and nonlinear model during cornering at various constant speed. The results show that during low speed cornering at 10 km/h, the linear and nonlinear model produced similar steady state cornering based on the trajectory and yaw rotational speed. However, the variants of linear and nonlinear started to appear as the vehicle speed increase. By obtaining the steady state cornering speed, another numerical simulation was performed to analyse the characteristics of the 4WD and 4WS electric vehicle. A passive control of the rear wheels’ steer angle was implement in the simulation. The results show that the parallel steering mode decreased the yaw rotational speed which broaden the trajectory of the cornering, while the opposite steering mode increased the yaw rotational speed that led to a tighter trajectory during cornering.

Driver Workload and Secondary Task Modality while Driving on Horizontal Curves

High driver workload has been considered as a risk factor in motor vehicle crashes. To minimize the number of crashes and improve driving safety, it is necessary to investigate driver workload and the most influential factor that affects driver workload. In this study, we examined the effects of road geometry, driving performance (by both steering wheel and pedal controls), and secondary task modality type on driver workload. A hierarchical ordinary least squares multiple regression analysis revealed that visually demanding secondary task predicted higher driver workload. This finding could help in-vehicle interface designs to minimize driver workload and improve driving safety.

Stability assist wheel control of multi-axle all-terrain crane using RLS algorithms with forgetting

This paper describes stability assist wheel control based on RLS estimation with forgetting in order to improve the dynamic stability of a multi-axle all-terrain crane. Existing multi-axle all-terrain cranes have greater mass and a longer distance between axles than ordinary vehicles, so their rotational inertia is very large. Large rotational inertia implies a slower dynamic response for yaw motion, and it is difficult to achieve the desired yaw motion within an expected amount of time. Therefore, ensuring yaw and lateral dynamic stability is an important theme in research regarding multi-axle all-terrain cranes. In this study, to ensure the crane’s dynamic stability, a simplified linear crane model of a multi-axle all-terrain crane was developed, in which an assist wheel was chosen according to speed, for control. To improve the driving stability, the chosen assistant wheel’s optimal steering angle was calculated through LQR, and to calculate the optimal feedback gain and steering angle, the rotational inertia and lateral velocity were estimated using recursive least square algorithms with forgetting. MATLAB/Simulink based simulations were used to evaluate the performance of the assist wheel controller for improving the crane’s dynamic stability, and the simulation results showed that the proposed stability assist wheel control method improved yaw and lateral dynamic stability over existing steering systems.

Path Tracking for a Skid-steer Vehicle using Model Predictive Control with On-line Sparse Gaussian Process

Skid-steer vehicle can generate a large traction force, which is especially good for navigation on a rough terrain. However, the turning motion is so sensitive to slippage effect that designing a controller is still challenging problem. Also, the motion of the vehicle is affected not only by wheel motion, but also by the road properties and the characteristics of wheel control. With this in mind, we employ a model predictive control (MPC) with an on-line model learning. The velocity model, which represents the relationship between true vehicle velocity and input command, is learned with an on-line sparse Gaussian process (GP). The on-line sparse GP can reduce the computational complexity of GP and also consistently update the model from the driving data. Finally, combining with MPC makes it possible to generate an optimal policy based on the learned model. Experiments are conducted to test the tracking performance of skid-steer robot. The results show the more reliable performance than the method based on a conventional model with parameter adaptation.

The ITASAT CubeSat Development and Design

Because they are inexpensive platforms for satellites, CubeSats have become a low-cost way for universities and even developing countries to have access to space technology. This paper presents the ITASAT design, particularly the Attitude Determination and Control Subsystem, the Onboard Software, and the Assembly,Integration and Testing program. The ITASAT is a 6U CubeSat nano-satellite in development at the Instituto Tecnologico de Aeronautica, in Sao Jose dos Campos, Brazil. The platform and its subsystems will be provided by industry while the payloads are being designed and developed by the principal investigators. The ITASAT Attitude Determination and Control Subsystem will rely on a 3-axis magnetometer, 6 analog cosine sun sensors, 3-axis MEMS gyroscopes, 3 magnetic torque coils, and 3 reaction wheels. The Attitude Determination and Control Subsystem operating modes, control laws, and embedded software are under the responsibility of the Instituto Tecnologico de Aeronautica. A Kalman filter shall be employed to estimate the quaternion attitude and gyroscope biases from sensor measurements. The Attitude Determination and Control Subsystem operating modes are the nominal mode, with geocentric pointing attitude control and the stabilization mode, in which only the satellite angular velocity is controlled. The nominal mode will be split into 2 sub-modes: reaction wheel control plus magnetic wheel desaturation and 3-axis magnetic attitude control. Simulation results have shown that the attitude can be controlled with 1-degree accuracy in nominal mode with the reaction wheels, but these errors grow as much as 20 degrees or higher with the 3-axis magnetic control.