Control theory can be used to make an unstable system stable. This thesis seeks to do this, where the system is a two DOF inverted pendulum with reaction wheels for stabilisation. The thesis also seeks to answer what is most important for making it stabilize for a longer period of time. It was decided that a state space controller was to be used with various sensors measuring the states. To be able to design a functioning demonstrator, a mathematical model of the system dynamics was developed. In the end the demonstrator proved to function as desired, being able to balance indefinitely. It was found that it is absolutely necessary to either give the controller a perfect set point or to implement an automatic set point. / Reglerteknik kan användas för att göra ostabila system stabila. Målet med detta projekt var att göra detta med ett system i form av en inverterad pendel med två frihetsgrader som balanseras med hjälp av två svänghjul. Projektet söker att besvara frågan om vad som är de viktigaste faktorerna för att få systemet att vara stabilt över en längre tid. En tillståndsåterkoppling användes som regulator vilket innebar att flera olika sensorer behövdes för att mäta de olika tillstånden. För att kunna konstruera en fungerande prototyp utvecklades en matematisk modell av systemet vilken användes för simulering av systemet. Till slut konstruerades en fungerade prototyp som till synes kunde balansera över oöverskådlig tid. En av de faktorer som visade sig påverka huruvida systemet uppnår stabilitet över längre tid var hur bra referenspunkt som gavs till regulatorn, det vill säga det tillstånd som regulatorn reglerar systemet mot. Det visade sig vara möjligt att implementera en självjusterande referenspunkt som gjorde systemet stabilt över tid.

Detta arbete undersöker hur undervisningsmodellen flipped classroom påverkar elevers inlärning inom matematik. Intervjuer med fem matematiklärare och fyra elever ligger till grund för att undersöka detta. Vi har antagit en socialkonstruktivistisk syn på inlärning och har därefter tematiskt analyserat empirin som genererades från semistrukturella, kvalitativa intervjuer. Av resultatet framgår att modellen möjliggör varierad undervisning, alltså flera olika inlärningsmoment kan täckas in på lektionstid. Detta kan vara i form av exempelvis grupparbete eller laborativa aktiviteter. Flipped classroom bidrar även med ytterligare repetitionsmaterial som är lättillgängligt. Arbetet kopplas även till tidigare forskning som främst bedrivits i USA. En utav slutsatserna är att undervisningsmodellen kan gynna elever som generellt ligger på en låg kunskapsnivå. En annan slutsats är att de videobaserade genomgångarna som kan infinna sig i undervisningen, kan ha ett mer koncentrerat innehåll och en tydligare struktur än genomgångar i klassrummet, vilket påverkar inlärningen.

How does future shopping look like? At the moment the physical shopping spaces are threatened by the e-commerce – A type of shopping that very often is a cure of boredom. It’s not a memorable experience, no story surrounding the object creating added value neither for the object or to the story connecting it with yourself. This thesis have been an investigation of physical retail architecture followed by a proposal: A 500 meter long railway tunnel, like a very long arcade, turned into a space for textile exhibitions, shopping and performance. Like an inverted Crystal Palace. All interior built up by scaffolding, ready to be torn down for the tunnel to once again serve the military in case of emergency. The walls are not made by glass, but lit up rock, reflecting the artificial light. It’s a linear experience. It goes from light to dark to colour. Dusk to dawn. The hidden becomes reviled, the unfocused becomes clear. It’s a space for your imagination, to experience new things, deepening your knowledge and escapism.

Vision-based object stabilisation is an exciting and challenging area of research, and is one that promises great technical advancements in the field of computer vision. As humans, we are capable of a tremendous array of skilful interactions, particularly when balancing unstable objects that have complex, non-linear dynamics. These complex dynamics impose a difficult control problem, since the object must be stabilised through collaboration between applied forces and vision-based feedback. To coordinate our actions and facilitate delivery of precise amounts of muscle torque, we primarily use our eyes to provide feedback in a closed-loop control scheme. This ability to control an inherently unstable object by vision-only feedback demonstrates an exceptionally high degree of voluntary motor skill. Despite the pervasiveness of vision-based stabilisation in humans and animals, relatively little is known about the neural strategies used to achieve this task. In the last few decades, with advancements in technology, we have tried to impart the skill of vision-based object stabilisation to machines, with varying degrees of success. Within the context of this research, we continue this pursuit by employing the classic Cart Inverted Pendulum; an inherently unstable, non-linear system to investigate dynamic object balancing by vision-only feedback. The Inverted Pendulum is considered to be one of the most fundamental benchmark systems in control theory; as a platform, it provides us with a strong, well established test bed for this research. We seek to discover what strategies are used to stabilise the Cart Inverted Pendulum, and to determine if these strategies can be deployed in Real-Time, using cost-effective solutions. The thesis confronts, and overcomes the problems imposed by low-bandwidth USB cameras; such as poor colour-balance, image noise and low frame rates etc., to successfully achieve vision-based stabilisation. The thesis presents a comprehensive vision-based control system that is capable of balancing an inverted pendulum with a resting oscillation of approximately ±1º. We employ a novel, segment-based location and tracking algorithm, which was found to have excellent noise immunity and enhanced robustness. We successfully demonstrate the resilience of the tracking and pose estimation algorithm against visual disturbances in Real-Time, and with minimal recovery delay. The algorithm was evaluated against peer reviewed research; in terms of processing time, amplitude of oscillation, measurement accuracy and resting oscillation. For each key performance indicator, our system was found to be superior in many cases to that found in the literature. The thesis also delivers a complete test software environment, where vision-based algorithms can be evaluated. This environment includes a flexible tracking model generator to allow customisation of visual markers used by the system. We conclude by successfully performing off-line optimization of our method by means of Artificial Neural Networks, to achieve a significant improvement in angle measurement accuracy. / Goodrich Engine Control Systems and Balfour Beatty Rail Technologies

京都大学 / 新制・課程博士 / 博士(人間健康科学) / 甲第24095号 / 人健博第102号 / 新制||人健||7(附属図書館) / 京都大学大学院医学研究科人間健康科学系専攻 / (主査)教授 市橋 則明, 教授 稲富 宏之, 教授 松田 秀一 / 学位規則第4条第1項該当 / Doctor of Human Health Sciences / Kyoto University / DFAM

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