POSITION TRACKING CONTROL OF DC MOTOR FOR FRONT WHEEL SYSTEMS VIA HILS SIMULATION METHOD

This paper present about position tracking control of DC motor to be used as the actuator controller for the front wheel test rig system. The controller strategy that was developed is based on Proportional-Integral-Derivative (PID) controller. It consists of one single closed control loops namely position tracking control loop.  To evaluate the effectiveness of the proposed controller, simulation and experimental studies were performed by using various input demand such as saw tooth, sine and step functions in 5°, 10°, 15° and 20° with the present of steering ratio at 360:20. The results, it is found that the trend between simulation and experimental data are similar with the command position with acceptable level of error which less than 10% for application at hand

Proportional-integral-derivative control algorithm with delay compensation for steer-by-wire under network controlled system

Controller Area Network (CAN) is a popular network commonly used in the automotive industry which is an advanced serial bus system designed for real-time control system. This thesis addresses the modelling and controller design for Steer-by-Wire (SbW) system under the influence of a network controlled system. The analysis of the control performance of the SbW system under several CAN configuration setting is discussed in detail. The mathematical model of the SbW system is adopted from previous research works using both steering rack dynamic and the vehicle system dynamic. Proportional-Integral-Derivative (PID) controller that can compensate delay is designed to achieve the desired control performance of the SbW system. The analysis of the control performance is solely based on the simulation conducted in the Matlab/Simulink software environment with Truetime toolbox to simulate the real time performance of the SbW system. The simulation is performed based on nine different cases in the event of several difference in the CAN network properties such as the network speed, sampling periods, scheduling techniques, rate of data losses, interruption by higher priority data and clock drift to evaluate the control performance of the SbW system. The result is found that the SbW system control performance deteriorates by the selection of low network speed, sensor’s sampling periods and the rate of data losses

Side Wind Compensation using Active Suspension

This thesis investigates what mechanisms that contribute to the interaction between lateral and vertical dynamics in a fourwheeled vehicle. For this a vehicle model was derived. To capture all the essential dynamics of the vehicle, both a horizontal model and a vertical model was used. The interaction between the models turned out to be quite evident, making it possible to use the active suspension system to influence the yaw dynamics of the vehicle. Further, it was investigated how this effect could be used for attenuating the effects of wind gusts. Since steer by wire is still a topic of active research and it's integration into vehicles lies in the future, this cannot presently be used for side wind rejection. With the vehicle model, it was possible to design a feedback controller that uses the active suspension system for side wind rejection. Key word

Steering control for haptic feedback and active safety functions

Steering feedback is an important element that defines driver–vehicle interaction. It strongly affects driving performance and is primarily dependent on the steering actuator\u27s control strategy. Typically, the control method is open loop, that is without any reference tracking; and its drawbacks are hardware dependent steering feedback response and attenuated driver–environment transparency. This thesis investigates a closed-loop control method for electric power assisted steering and steer-by-wire systems. The advantages of this method, compared to open loop, are better hardware impedance compensation, system independent response, explicit transparency control and direct interface to active safety functions.The closed-loop architecture, outlined in this thesis, includes a reference model, a feedback controller and a disturbance observer. The feedback controller forms the inner loop and it ensures: reference tracking, hardware impedance compensation and robustness against the coupling uncertainties. Two different causalities are studied: torque and position control. The two are objectively compared from the perspective of (uncoupled and coupled) stability, tracking performance, robustness, and transparency.The reference model forms the outer loop and defines a torque or position reference variable, depending on the causality. Different haptic feedback functions are implemented to control the following parameters: inertia, damping, Coulomb friction and transparency. Transparency control in this application is particularly novel, which is sequentially achieved. For non-transparent steering feedback, an environment model is developed such that the reference variable is a function of virtual dynamics. Consequently, the driver–steering interaction is independent from the actual environment. Whereas, for the driver–environment transparency, the environment interaction is estimated using an observer; and then the estimated signal is fed back to the reference model. Furthermore, an optimization-based transparency algorithm is proposed. This renders the closed-loop system transparent in case of environmental uncertainty, even if the initial condition is non-transparent.The steering related active safety functions can be directly realized using the closed-loop steering feedback controller. This implies, but is not limited to, an angle overlay from the vehicle motion control functions and a torque overlay from the haptic support functions.Throughout the thesis, both experimental and the theoretical findings are corroborated. This includes a real-time implementation of the torque and position control strategies. In general, it can be concluded that position control lacks performance and robustness due to high and/or varying system inertia. Though the problem is somewhat mitigated by a robust H-infinity controller, the high frequency haptic performance remains compromised. Whereas, the required objectives are simultaneously achieved using a torque controller

DESIGN OF A SEMI-ACTIVE STEERING SYSTEM FOR A PASSENGER CAR

This thesis presents research into an improved active steering system technology for a passenger car road vehicle, based on the concept of steer-by-wire (SBW) but possessing additional safety features and advanced control algorithms to enable active steering intervention. An innovative active steering system has been developed as 'Semi-Active Steering' (SAS) in which the rigid steering shaft is replaced with a low stiffness resilient shaft (LSRS). This allows active steer to be performed by producing more or less steer angle to the front steered road wheels relative to the steering wheel input angle. The system could switch to either being 'active' or 'conventional' depending on the running conditions of the vehicle; e.g. during normal driving conditions, the steering system behaves similarly to a power-assisted steering system, but under extreme conditions the control system may intervene in the vehicle driving control. The driver control input at the steering wheel is transmitted to the steered wheels via a controlled steering motor and in the event of motor failure, the LSRS provides a basic steering function. During operation of the SAS, a reaction motor applies counter torque to the steering wheel which simulates the steering 'feel' experienced in a conventional steering system and also applies equal and opposite counter torque to eliminate disturbance force from being felt at the steering wheel during active control operation. The thesis starts with the development of a mathematical model for a cornering road vehicle fitted with hydraulic power-assisted steering, in order to understand the relationships between steering characteristics such as steering feel, steering wheel torque and power boost characteristic. The mathematical model is then used to predict the behaviour of a vehicle fitted with the LSRS to represent the SAS system in the event of system failure. The theoretical minimum range of stiffness values of the flexible shaft to maintain safe driving was predicted. Experiments on a real vehicle fitted with an LSRS steering shaft simulator have been conducted in order to validate the mathematical model. It was found that a vehicle fitted with a suitable range of steering shaft stiffness was stable and safe to be driven. The mathematical model was also used to predict vehicle characteristics under different driving conditions which were impossible to conduct safely as experiments. Novel control algorithms for the SAS system were developed to include two main criteria, viz. power-assistance and active steer. An ideal power boost characteristic curve for a hydraulic power-assisted steering was selected and modified and a control strategy similar to Steer-by-Wire (SBW) was implemented on the SAS system. A full-vehicle computer model of a selected passenger car was generated using ADAMS/car software in order to demonstrate the implementation of the proposed SAS system. The power-assistance characteristics were optimized and parameters were determined by using an iteration technique inside the ADAMS/car software. An example of an open-loop control system was selected to demonstrate how the vehicle could display either under-steer or over-steer depending on the vehicle motion. The simulation results showed that a vehicle fitted with the SAS system could have a much better performance in terms of safety and vehicle control as compared to a conventional vehicle. The characteristics of the SAS system met all the requirements of a robust steering system. It is concluded that the SAS has advantages which could lead to its being safely fitted to passenger cars in the future. Keywords: steer-by-wire, active steering, innovative, power-assisted steering, steering control, flexible shaft, steering intervention, system failure, safety features

Experimental validation of a multibody model for a vehicle prototype and its application to automotive state observers

[Abstract] The simulation of multibody system dynamics is a key element of Computer-Aided Design and also a well-established tool in the development of new vehicles. A vehicle model is a typical multibody system made of rigid and/or flexible bodies that are interconnected by joints and usually undergo large translational and rotational displacements. In the last decade, real-time simulations of vehicle multibody models have gained interest thanks to the development hardware- or human-in-the-loop applications. Efficient multibody formulations must be employed to simulate complex systems in real-time and reliability of the models and validity are of the highest importance. This thesis focuses first on the study of the validity of real¿time vehicle multibody models developed at the Laboratorio de Ingeniería Mecánica of the University of La Coruña. For this purpose, a vehicle prototype has been built and automated in order to repeat reference maneuvers. The numerous sensors on the prototype gather the most relevant magnitudes of the vehicle motion (roll-pitch-yaw rates, wheel speeds, etc). Two low speed maneuvers involving the longitudinal and lateral vehicle dynamics have been repeated several times in a test area at the campus of the engineering school. A real-time multibody model of the vehicle prototype has been prepared as well as a simulation environment that includes a close graphical environment, a true road profile and collision detection. Subsystems like brakes or tires have also been modeled. Both test maneuvers have been repeated with the developed multibody model in the simulation environment using inputs that have been measured experimentally. Selected simulation variables have then been compared to their experimental counterparts provided with a confidence interval that characterizes the field testing process errors. The results of the comparisons have then been interpreted to extract useful guidelines to build real-time vehicle multibody models. Once a real-time vehicle model is validated, it not only raises the possibility to be used in hardware- or human-in-the-loop applications but also in on-board stability controllers. Nowadays simplified vehicle models coming from the classical vehicle dynamics theory are commonly employed in on-board stability controllers. The use of real-time vehicle multibody models in state observers (a widely-used control technique in stability controllers) is a research subject initiated a few years before the beginning of this thesis at the Laboratorio de Ingeniería Mecánica. The last part of this thesis goes first over the developed implementation of the Extended Kalman filter, a common state observer for nonlinear systems, with multibody models and, after that presents several new implementations using this filter and other filters coming from the family of the sigma-point Kalman filters

Design of a digital ride quality augmentation system for commuter aircraft

Commuter aircraft typically have low wing loadings, and fly at low altitudes, and so they are susceptible to undesirable accelerations caused by random atmospheric turbulence. Larger commercial aircraft typically have higher wing loadings and fly at altitudes where the turbulence level is lower, and so they provide smoother rides. This project was initiated based on the goal of making the ride of the commuter aircraft as smooth as the ride experienced on the major commercial airliners. The objectives of this project were to design a digital, longitudinal mode ride quality augmentation system (RQAS) for a commuter aircraft, and to investigate the effect of selected parameters on those designs

REAL-TIME ERROR DETECTION AND CORRECTION FOR ROBUST OPERATION OF AUTONOMOUS SYSTEMS USING ENCODED STATE CHECKS

The objective of the proposed research is to develop methodologies, support algorithms and software-hardware infrastructure for detection, diagnosis, and correction of failures for actuators, sensors and control software in linear and nonlinear state variable systems with the help of multiple checks employed in the system. This objective is motivated by the proliferation of autonomous sense-and-control real-time systems, such as intelligent robots and self-driven cars which must maintain a minimum level of performance in the presence of electro-mechanical degradation of system-level components in the field as well as external attacks in the form of transient errors. A key focus is on rapid recovery from the effects of such anomalies and impairments with minimal impact on system performance while maintaining low implementation overhead as opposed to traditional schemes for recovery that rely on duplication or triplication. On-line detection, diagnosis and correction techniques are investigated and rely on analysis of system under test response signatures to real-time stimulus. For on-line error detection and diagnosis, linear and nonlinear state space encodings of the system under test are used and specific properties of the codes, as well as machine learning model based approaches were used are analyzed in real-time. Recovery is initiated by copying check model values to correct error for sensor and control software malfunction, and by redesigning the controller parameter on-the-fly for actuators to restore system performance. Future challenges that need to be addressed include viability studies of the proposed techniques on mobile autonomous system in distributed setting as well as application to systems with soft as well as hard real-time performance constraints.Ph.D

Nonlinear Modeling and Control of Driving Interfaces and Continuum Robots for System Performance Gains

With the rise of (semi)autonomous vehicles and continuum robotics technology and applications, there has been an increasing interest in controller and haptic interface designs. The presence of nonlinearities in the vehicle dynamics is the main challenge in the selection of control algorithms for real-time regulation and tracking of (semi)autonomous vehicles. Moreover, control of continuum structures with infinite dimensions proves to be difficult due to their complex dynamics plus the soft and flexible nature of the manipulator body. The trajectory tracking and control of automobile and robotic systems requires control algorithms that can effectively deal with the nonlinearities of the system without the need for approximation, modeling uncertainties, and input disturbances. Control strategies based on a linearized model are often inadequate in meeting precise performance requirements. To cope with these challenges, one must consider nonlinear techniques. Nonlinear control systems provide tools and methodologies for enabling the design and realization of (semi)autonomous vehicle and continuum robots with extended specifications based on the operational mission profiles. This dissertation provides an insight into various nonlinear controllers developed for (semi)autonomous vehicles and continuum robots as a guideline for future applications in the automobile and soft robotics field. A comprehensive assessment of the approaches and control strategies, as well as insight into the future areas of research in this field, are presented.First, two vehicle haptic interfaces, including a robotic grip and a joystick, both of which are accompanied by nonlinear sliding mode control, have been developed and studied on a steer-by-wire platform integrated with a virtual reality driving environment. An operator-in-the-loop evaluation that included 30 human test subjects was used to investigate these haptic steering interfaces over a prescribed series of driving maneuvers through real time data logging and post-test questionnaires. A conventional steering wheel with a robust sliding mode controller was used for all the driving events for comparison. Test subjects operated these interfaces for a given track comprised of a double lane-change maneuver and a country road driving event. Subjective and objective results demonstrate that the driver’s experience can be enhanced up to 75.3% with a robotic steering input when compared to the traditional steering wheel during extreme maneuvers such as high-speed driving and sharp turn (e.g., hairpin turn) passing. Second, a cellphone-inspired portable human-machine-interface (HMI) that incorporated the directional control of the vehicle as well as the brake and throttle functionality into a single holistic device will be presented. A nonlinear adaptive control technique and an optimal control approach based on driver intent were also proposed to accompany the mechatronic system for combined longitudinal and lateral vehicle guidance. Assisting the disabled drivers by excluding extensive arm and leg movements ergonomically, the device has been tested in a driving simulator platform. Human test subjects evaluated the mechatronic system with various control configurations through obstacle avoidance and city road driving test, and a conventional set of steering wheel and pedals were also utilized for comparison. Subjective and objective results from the tests demonstrate that the mobile driving interface with the proposed control scheme can enhance the driver’s performance by up to 55.8% when compared to the traditional driving system during aggressive maneuvers. The system’s superior performance during certain vehicle maneuvers and approval received from the participants demonstrated its potential as an alternative driving adaptation for disabled drivers. Third, a novel strategy is designed for trajectory control of a multi-section continuum robot in three-dimensional space to achieve accurate orientation, curvature, and section length tracking. The formulation connects the continuum manipulator dynamic behavior to a virtual discrete-jointed robot whose degrees of freedom are directly mapped to those of a continuum robot section under the hypothesis of constant curvature. Based on this connection, a computed torque control architecture is developed for the virtual robot, for which inverse kinematics and dynamic equations are constructed and exploited, with appropriate transformations developed for implementation on the continuum robot. The control algorithm is validated in a realistic simulation and implemented on a six degree-of-freedom two-section OctArm continuum manipulator. Both simulation and experimental results show that the proposed method could manage simultaneous extension/contraction, bending, and torsion actions on multi-section continuum robots with decent tracking performance (e.g. steady state arc length and curvature tracking error of 3.3mm and 130mm-1, respectively). Last, semi-autonomous vehicles equipped with assistive control systems may experience degraded lateral behaviors when aggressive driver steering commands compete with high levels of autonomy. This challenge can be mitigated with effective operator intent recognition, which can configure automated systems in context-specific situations where the driver intends to perform a steering maneuver. In this article, an ensemble learning-based driver intent recognition strategy has been developed. A nonlinear model predictive control algorithm has been designed and implemented to generate haptic feedback for lateral vehicle guidance, assisting the drivers in accomplishing their intended action. To validate the framework, operator-in-the-loop testing with 30 human subjects was conducted on a steer-by-wire platform with a virtual reality driving environment. The roadway scenarios included lane change, obstacle avoidance, intersection turns, and highway exit. The automated system with learning-based driver intent recognition was compared to both the automated system with a finite state machine-based driver intent estimator and the automated system without any driver intent prediction for all driving events. Test results demonstrate that semi-autonomous vehicle performance can be enhanced by up to 74.1% with a learning-based intent predictor. The proposed holistic framework that integrates human intelligence, machine learning algorithms, and vehicle control can help solve the driver-system conflict problem leading to safer vehicle operations

Synthesis and Analysis of an Active Independent Front Steering (AIFS) System

Technological developments in road vehicles over the last two decades have received considerable attention towards pushing the safe performance limits to their ultimate levels. Towards this goal, Active Front Steering (AFS) and Direct Yaw-moment Control (DYC) systems have been widely investigated. AFS systems introduce corrective steering angles to the conventional system in order to realize a target handling response for a given speed and steering input. An AFS system, however, may yield limited performance under severe steering maneuvers involving substantial lateral load shift and saturation of the inside tire-road adhesion. The adhesion available at the outer tire, on the other hand, would remain under-utilized. This dissertation explores effectiveness of an Active Independent Front Steering (AIFS) system that could introduce a corrective measure at each wheel in an independent manner. The effectiveness of the AIFS system was investigated firstly through simulation of a yaw-plane model of a passenger car. The preliminary simulation results with AIFS system revealed superior potential compared to the AFS particularly in the presence of greater lateral load shift during a high-g maneuver. The proposed concept was thus expected to be far more beneficial for enhancement of handling properties of heavy vehicles, which invariably undergo large lateral load shift due to their high center of mass and roll motion. A nonlinear yaw-plane model of a two-axle single-unit truck, fully and partially loaded with solid and liquid cargo, with limited roll degree-of-freedom (DOF) was thus developed to study the performance potentials of AIFS under a range of steering maneuvers. A simple PI controller was synthesized to track the reference yaw rate response of a neutral steer vehicle. The steering corrections, however, were limited such that none of the tires approach saturation. For this purpose, a tire saturation zone was identified considering the normalized cornering stiffness property of the tire. The controller strategy was formulated so as to limit the work-load magnitude at a pre-determined level to ensure sufficient tire-road adhesion reserve to meet the braking demand, when exists. Simulation results were obtained for a truck model integrating AFS and AIFS systems subjected to a range of steering maneuvers, namely: a J-turn maneuver on uniform as well as split-μ road conditions, and path change and obstacle avoidance maneuvers. The simulation results showed that both AFS and AIFS can effectively track the target yaw rate of the vehicle, while the AIFS helped limit saturation of the inside tire and permitted maximum utilization of the available tire-road adhesion of the outside tire. The results thus suggested that the performance of an AIFS system would be promising under severe maneuvers involving simultaneous braking and steering, since it permitted a desired adhesion reserve at each wheel to meet a braking demand during the steering maneuver. Accordingly, the vehicle model was extended to study the dynamic braking characteristics under braking-in-turn maneuvers. The simulation results revealed the most meritorious feature of the AIFS in enhancing the braking characteristics of the vehicle and reducing the stopping time during such maneuvers. The robustness of the proposed control synthesis was subsequently studied with respect to parameter variations and external disturbance. This investigation also explores designs of fail-safe independently controllable front wheels steering system for implementation of the AIFS concept