Fuzzy Logic Approach to Stability Control

Traditional Electronic Stability Control (ESC) for automobiles is usually accomplished through the use of estimated vehicle dynamics from simplified models. Starting with the conventional two degree-of-freedom vehicle model, one can estimate the vehicle states from the driver steering input. From this estimate, vehicle sideslip angle can be found and this is generally used with a threshold value to initiate a control action. The input/output relationship of the model depends heavily on the accuracy of the parameters used and various means to correct model inaccuracies. Specifically, these models depend on the tire cornering stiffness which is prone to change with age and loading of the tires. Moreover, not all consumers will replace the original equipment (OE) tires with the same ones. Vehicle response is also directly related to coefficient of friction between the tire and road which varies with road and tire conditions. These issues may result in the degradation of the effectiveness of the ESC system. At the very least, they may require extensive tuning of the control algorithms. This thesis proposes a different method for estimating the instability of a vehicle. It is solely based on measurable vehicle dynamic response characteristics including lateral acceleration, yaw rate, speed, and driver steering input. These signals are appropriately conditioned and evaluated with fuzzy logic to determine the degree of instability present. When the \u27degree of instability\u27 passes a certain threshold, the appropriate control action is applied to the vehicle in the form of differential yaw braking. Using only the measured response of the vehicle alleviates the problem of degraded performance when vehicle parameters change. Finally, ten case studies of different vehicles, configurations, environments, driver models, and maneuvers are tested with the same ESC strategy to examine the concept of stability control without estimation. Four very different vehicles ranging from a sports car to a sport utility vehicle (SUV) in multiple configurations including degraded rear tires and different loading conditions are used in evaluating the proposed ESC. These vehicles and configurations are subjected to multiple maneuvers including a double lane change and a fishhook maneuver with tire-to-road conditions such as split mu and low mu to simulate slippery road conditions. The main result of this research is the evolution of a new ESC concept where performance is not based on a vehicle model with set parameters that lose effectiveness in estimating the vehicle dynamic states when the vehicle changes. Instead, the algorithm relies only on the current measurable dynamic states of the vehicle to preserve stability

A Controls-Oriented Approach For Modeling Professional Drivers During Ultra-High Performance Maneuvers

In the study of vehicle dynamics and controls, modeling ultra-high performance maneuvers (i.e., minimum-time vehicle maneuvering) is a fascinating problem that explores the boundaries of capabilities for a human controlling a machine. Professional human drivers are still considered the benchmark for controlling a vehicle during these limit handling maneuvers. Different drivers possess unique driving styles, i.e. preferences and tendencies in their local decisions and corresponding inputs to the vehicle. These differences in the driving style among professional drivers or sets of drivers are duly considered in the vehicle development process for component selection and system tuning to push the limits of achievable lap times. This work aims to provide a mathematical framework for modeling driving styles of professional drivers that can then be embedded in the vehicle design and development process. This research is conducted in three separate phases. The first part of this work introduces a cascaded optimization structure that is capable of modeling driving style. Model Predictive Control (MPC) provides a natural framework for modeling the human decision process. In this work, the inner loop of the cascaded structure uses an MPC receding horizon control strategy which is tasked with finding the optimal control inputs (steering, brake, throttle, etc.) over each horizon while minimizing a local cost function. Therein, we extend the typical fixed-cost function to be a blended cost capable of optimizing different objectives. Then, an outer loop finds the objective weights used in each MPC control horizon. It is shown that by varying the driver\u27s objective between key horizons, some of the sub-optimality inherent to the MPC process can be alleviated. In the second phase of this work, we explore existing onboard measurements of professional drivers to compare different driving styles. We outline a novel racing line reconstruction technique rooted in optimal control theory to reconstruct the driving lines for different drivers from a limited set of measurements. It is demonstrated that different drivers can achieve nearly identical lap times while adopting different racing lines. In the final phase of this work, we use our racing line technique and our cascaded optimization framework to fit computable models for different drivers. For this, the outer loop of the cascaded optimization finds the set of objective weights used in each local MPC horizon that best matches simulation to onboard measurements. These driver models will then be used to optimize vehicle design parameters to suit each driving style. It will be shown that different driving styles will yield different parameters that optimize the driver/vehicle system

Scanning Electron Microscopy Studies of Staphylococcal Adherence to Heart Valve Endothelial Cells in Organ Culture: An In Vitro Model of Acute Endocarditis

Organ cultures of human heart valves were used as a model to study the initial pathobiology of acute infective bacterial endocarditis. We used Staphylococcus aureus isolated from a case of infective endocarditis to infect the in vitro culture of the heart valves. Using scanning electron microscopy, we assessed the initial damage, attachment to and invasion of the endothelial cell layer by staphylococci. Our results indicate there is initial damage to the endothelium prior to observation of staphylococci attaching to the endothelial cell. By 12 h post infection, there is significant attachment and damage. At 24 h after infection, destruction of the heart valve endothelium is complete. The attachment and destruction arc progressive events and can be correlated quantitatively with bacterial numbers from the culture medium and those attached to the valves. This is correlated with increasing adherence ratios of the attaching staphylococci

Integrated Administrative Data for Early Childhood Iowa: A Governance Model to inform Policy and Program Collaboration

In response to demands on public systems to do more, do better, and cost less, the value of integrated administrative data systems (IDS) for social policy is increasing (Fantuzzo & Culhane, 2016). This is particularly relevant in programming for young children where services are historically fragmented, disconnected from systems serving school-aged children, and siloed among health, human services, and education agencies. Guided by the vision that Iowa’s early childhood system will be effectively and efficiently coordinated to support healthy families, we are developing an early childhood IDS to address this disconnection and facilitate relevant and actionable social policy research. Iowa’s IDS is a state-university partnership that acknowledges the need for agencies to retain control of their data while enabling it to be integrated across systems for social policy research. The innovative governance model deliberately incorporates procedures for stakeholder engagement at critical tension points between executive leaders, program managers, researchers, and practitioners. Standing committees (Governance Board, Data Stewardship, and Core team) authorize and implement the work of the IDS, while ad-hoc committees are solicited for specific projects to advise and translate research into practice. This paper will articulate the Iowa IDS governance model that was informed by means tested principles articulated by the Actionable Intelligence for Social Policy Network. It will include our collaborative development process; articulated mission and principles that guided discussions about legal authorization, governance, and use cases; and the establishment of governance committees to implement our vision for ethical and efficient use of administrative data for social policy

Ecohydrological separation in wet, low energy northern environments? A preliminary assessment using different soil water extraction techniques

Funded by European Research Council ERC. Grant Number: project GA 335910 VEWA ACKNOWLEDGEMENTS The constructive comments and suggestions from two anonymous reviewers greatly improved an earlier version of this manuscript. Jon Dick, Jason Lesselsand Jane Bang Poulsen are thanked for assistance with data collection; Audrey Innes for sample preparation and assistance with the cryogenic extraction of water samples; Paula Craib for glassware design; Colleagues in Prof. J. Anderson’s lab for day-to-day assistance incryogenic extraction; Todd Dawson and Nathalie Schultz for providing information on extraction techniques and the analysis of vegetation water; Hedda Weitz for help with the centrifugation of soil samples;and Iain Malcolm and colleagues at the Marine Scotland Freshwater Lab for providing meteorological data. We thank Jason Newton and the Scottish Universities Environmental Research Centre (SUERC) Mass Spectrometry Facility Laboratory in East Kilbride for theisotopic analyses of the xylem water samples. The European Research Council ERC (project GA 335910VEWA) is thanked for funding.Peer reviewedPostprin