Evolutionary optimization of a motorcycle traction control system based on fuzzy logic.

Política de acceso abierto tomada de: https://v2.sherpa.ac.uk/id/publication/3451Braking and traction control systems are fundamental vehicle safety equipments. The first ones prevent the wheels from locking, maintaining, when possible, the handling of the vehicle under emergency braking. While the second ones control wheel slip when excessive torque is applied on driving wheels. The aim of this work is to develop and implement a new control model of a traction control system to be installed on a motorcycle, regulating the slip in traction and improving dynamic behavior of two-wheeled vehicles. This paper presents a novel traction control algorithm which makes use of a fuzzy logic control block. Two strategies to create the control block have been carried out. In the first one, the parameters that define the fuzzy logic controller have been tuned according to experience. In the second one, the parameters have been obtained by means of an Evolutionary Algorithm (EA) in order to design an augmented traction controller. It has been proved that the use of EA can improve the fuzzy logic based control algorithm, obtaining better results than those produced with the control tuned only by experience

Controllo di trazione: metodi per lo sviluppo di algoritmi

Lo svolgimento della tesi ha riguardato principalmente lo studio della problematica del controllo di trazione e stabilita' in genere. E' stata quindi approfondita la conoscenza di fisica dei veicoli e delle parti e sottosistemi che compongono auto e moto, oltre alle procedure di acquisizione ed elaborazione delle grandezze necessarie per le analisi. Successivamente sono stati studiati una procedura e una base software per lo studio e la simulazione di nuovi sistemi di controllo, utilizzati per lo sviluppo di un controllo della trazione che è stato realizzato e testato su diversi veicol

Infrastructure-as-a-Service Usage Determinants in Enterprises

The thesis focuses on the research question, what the determinants of Infrastructure-as-a-Service usage of enterprises are. A wide range of IaaS determinants is collected for an IaaS adoption model of enterprises, which is evaluated in a Web survey. As the economical determinants are especially important, they are separately investigated using a cost-optimizing decision support model. This decision support model is then applied to a potential IaaS use case of a large automobile manufacturer