3,103 research outputs found

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

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    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

    Trajectory generation for road vehicle obstacle avoidance using convex optimization

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    This paper presents a method for trajectory generation using convex optimization to find a feasible, obstacle-free path for a road vehicle. Consideration of vehicle rotation is shown to be necessary if the trajectory is to avoid obstacles specified in a fixed Earth axis system. The paper establishes that, despite the presence of significant non-linearities, it is possible to articulate the obstacle avoidance problem in a tractable convex form using multiple optimization passes. Finally, it is shown by simulation that an optimal trajectory that accounts for the vehicle’s changing velocity throughout the manoeuvre is superior to a previous analytical method that assumes constant speed

    Model-based H2/H1 control design of integrated vehicle tracking systems

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    The paper presents the design of an integrated heavy vehicle system which consists of the driveline, the brake, the suspension and the steering components. The purpose of the integration is to create an adaptive cruise control which is able to keep the distance from the preceding vehicle and track the path on roads. The vehicle model consists of the dynamics of the sprung mass and the unsprung masses and handles the effects of road and wind disturbances. The design of the adaptive cruise-control system is based on the H2/H∞ control method. The operation of the controlled system is illustrated through simulation examples

    Steering control for haptic feedback and active safety functions

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    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

    Continuous and discrete time attitude control of a vehicle

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    Kontrola řízení vozidla se stala významným problémem v automatizačních aplikacích v automobilovém průmyslu. Ta se stala reálnou díky zavedení různých "by-wire" subsystémů, jako je např. "steer-by-wire," "break-by-wire," atd. Tyto subsystémy reprezentují elektronické ekvivalenty již existujících mechanických a hydraulických subsystémů. Především pak může být zavedeno číslicové řízení, určené na základě vzorkování dynamiky vozidla. Výhodou periodického snímání vstupních veličin je vyvarování se určitých poruch spojitého řízení.Attitude vehicle control has become an important problem in automotive control applications. Such a control is made possible thanks to the introduction of various "by-wire" subsystems, such as steer-by-wire, break-by-wire, etc. These represent the electronic equivalent of existing mechanical and hydraulic subsystems. In particular, digital controls determined on the basis of the vehicle sampled dynamics can be determined. The advantage of determining a digital control is the avoidance of performance deterioration of the continuous control law when implemented with zero order holders.

    Development Of Steer-By-Wire (SBW) Controller System For Steering Respone

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    This research focuses on the development of Steer-By-Wire (SBW) controller system for steering response. The steering system is an essential part of the interface between the driver and the vehicle that provides the possibility of lateral guidance. SBW system is means as removing the mechanical linkages and hydraulic part with electronic system. The development of vehicle model consists of ride, tire and handling models used in this study. The vehicle model is then validated with CarSimEd. The relation between the rack and pinion is identified for the steering ratio on SBW model. The steering system is modeled combine with actuator model in MATLAB Simulink. There are several types of controller are used on SBW system to find the similar response with the conventional steering. The selected controller will be applied on SBW system to control the actuator in simulation and experimental. The simulation result is validated with Hardware-in-the-Loop Simulation (HiLS) in real time situation using xPC Target application in MATLAB Simulink to control SBW system in experiment. The target outcome of this study for SBW steering system is to get a responsiveness similarity to conventional steering system with selected controller by comparing both steering system. The study shows that such similarity was achieved. The study of SBW system response is beneficial in the SBW system with the proposed controller can be implemented on real vehicles

    Kinisi: A Platform for Autonomizing Off-Road Vehicles

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    This project proposed a modular system that would autonomize off-road vehicles while retaining full manual operability. This MQP team designed and developed a Level 3 autonomous vehicle prototype using an SAE Baja vehicle outfitted with actuators and exteroceptive sensors. At the end of the project, the vehicle had a drive-by-wire system, could localize itself using sensors, generate a map of its surroundings, and plan a path to follow a desired trajectory. Given a map, the vehicle could traverse a series of obstacles in an enclosed environment. The long- term goal is to alter the software system to make it modular and operate in real-time, so the vehicle can autonomously navigate off-road terrain to rescue and aid a distressed individual
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