Resilience-enhanced control reconfiguration for autonomous systems

Unmanned systems keep replacing manned systems as a paradigm shift. According to the Unmanned Autonomous Systems (UAS) market forecast reports, the UAS market value is expected to grow two to three times higher in ten years. Considering the economic impacts of UAS application in job markets and component manufacturing industries, the UAS market value may very well exceed, which is predicted in the reports. However, regulations have limited the effective utilization of UAS due to safety concerns. These restrictive regulations significantly delay the potential usefulness of civilian and commercial UAVs. According to the Unmanned Aerial Vehicle (UAV) incidence reports, mechanical failures come out to be one of the top reasons for the incidents except for human errors. Technically, it is impossible to avoid any fault or failure in any systems. However, it can be possible to save the faulty system if the faults are treated properly. In this regard, this research has reviewed the state-of-the-art techniques regarding system safety improvement in the presence of a critical fault mode. Promising concepts are resilience engineering and Active Fault Tolerant Control (AFTCS) systems. Resilience engineering has been more focus on system design and resilience assessment methods. AFTCS mainly contributes to the fast and stable operating point recovery without the consideration of long-term system performances or mission success. Prognostics-enhanced reconfigurable control frameworks have proposed the online prognosis for a Remaining Useful Life (RUL) prediction within the control scheme but do not address comprehensive mission capability trade-offs. The objective of this study is to design a resilience-enhanced reconfigurable control framework for unmanned autonomous systems in the presence of a critical fault mode during the operation. The proposed resilience-enhanced reconfigurable control framework is composed of three fundamental modules: 1) immediate performance recovery by Model Predictive Control (MPC) and Differential Dynamic Programming (DDP) approaches, 2) long-term mission capability trade-offs by an optimization routine, and 3) situational awareness by a particle filtering-based fault diagnosis and Case-Based Reasoning (CBR). Critical development of this thesis is an introduction of an adaptation parameter in an MPC formulation (Module 1) and optimization process to find an optimal value for the adaptation parameter (Module 2). Module 3 enables long-term mission capability reasoning when a new fault growth pattern is observed. In order to test the efficacy of the proposed framework, under-actuated hovercraft as a testbed and an insulation degradation of an electrical thrust motor as a critical fault mode are introduced. The experiments explore the effect of the adaptation parameter on long-term mission capabilities and identify the necessity of the proper trade-offs. Further experiments investigate the efficacy of each module and the integrated framework. The experiment results show that the adaptation parameter adjusts a control strategy, so that mission capabilities are optimized while vulnerable long-term mission capabilities are recovered. The integrated framework presents the improvement to the probability of mission success in the presence of a critical fault mode. Lastly, as a generalization of the design process for the resilience-enhanced reconfigurable control framework, a design methodology suggests a step-by-step design procedure. Assumptions of the research have guided the required steps and limitations of the proposed framework.Ph.D

Approaches to shipboard power generation systems design and management. Probabilistic approach to load prediction and system optimal design, sizing and management

This doctoral thesis presents new ideas and formulations on shipboard power system sizing and management. The main motivation behind this work is to fill, at least in part, the current technological and mythological gap between land and marine applications, concerning the sizing and management of power systems. This gap is the result of several changes regarding both the electric and marine applications. Two of these are, for example, the recent increase of electric power installed on board modern vessels and recent development of technologies for land microgrids. In this context, it should be noted that, also the modern ships are comparable to land microgrids, where the generation and loads are close in space and the on board power system may work either islanded or connected to the land grid. Nowadays, microgrids are a hot topic in electric engineering, with a constant development of novel approaches for both their sizing and management. On the other hand, considering the increase in the power installed on board ships, the traditional methods developed in the last century to size and manage these systems have shown increasing limitations and inaccuracies. This results in oversized power generation systems, low performances and high level of air and sea pollution due to ships activities. To overcome these problems and criticalities, this work presents a probabilistic approach to load prediction, which may increase the flexibility of the power system design and allow a significant reduction in the total power installed. Moreover, the traditional method to size the diesel generators, based on satisfying the maximum load, it is revised with the formulation of an optimal problem, which can consider as input either the results of the traditional method to load prediction or those obtained applying the probabilistic one. Finally, due to the recent introduction in land microgrids of energy storage system, which may cover the power fluctuations due to renewable resources, allow a better management of energy and increase the quality of service, an optimum method is developed and described in order to select, size and manage these systems on board ships

INTEGRATED MOLECULAR PROFILING FOR ANALYZING AND PREDICTING THERAPEUTIC MECHANISM, RESPONSE, BIOMARKER AND TARGET

Ph.DDOCTOR OF PHILOSOPH

Maps of Lessons Learnt in Requirements Engineering

Both researchers and practitioners have emphasized the importance of learning from past experiences and its consequential impact on project time, cost, and quality. However, from the survey we conducted of requirements engineering (RE) practitioners, over 70\% of the respondents stated that they seldom use RE lessons in the RE process, though 85\% of these would use such lessons if readily available. Our observation, however, is that RE lessons are scattered, mainly implicitly, in the literature and practice, which obviously, does not help the situation. We, therefore, present ``maps” of RE lessons which would highlight weak (dark) and strong (bright) areas of RE (and hence RE theories). Such maps would thus be: (a) a driver for research to ``light up” the darker areas of RE and (b) a guide for practice to benefit from the brighter areas. To achieve this goal, we populated the maps with over 200 RE lessons elicited from literature and practice using a systematic literature review and survey. The results show that approximately 80\% of the elicited lessons are implicit and that approximately 70\% of the lessons deal with the elicitation, analysis, and specification RE phases only. The RE Lesson Maps, elicited lessons, and the results from populating the maps provide novel scientific groundings for lessons learnt in RE as this topic has not yet been systematically studied in the field

A system for the simulation of hardware to software allocation and performance evaluation

Imperial Users onl

Modelling and scheduling of heterogeneous computing systems

Ph.DDOCTOR OF PHILOSOPH

N+3 Aircraft Concept Designs and Trade Studies

Appendices A to F present the theory behind the TASOPT methodology and code. Appendix A describes the bulk of the formulation, while Appendices B to F develop the major sub-models for the engine, fuselage drag, BLI accounting, etc

Building information modeling – A game changer for interoperability and a chance for digital preservation of architectural data?

Digital data associated with the architectural design-andconstruction process is an essential resource alongside -and even past- the lifecycle of the construction object it describes. Despite this, digital architectural data remains to be largely neglected in digital preservation research – and vice versa, digital preservation is so far neglected in the design-and-construction process. In the last 5 years, Building Information Modeling (BIM) has seen a growing adoption in the architecture and construction domains, marking a large step towards much needed interoperability. The open standard IFC (Industry Foundation Classes) is one way in which data is exchanged in BIM processes. This paper presents a first digital preservation based look at BIM processes, highlighting the history and adoption of the methods as well as the open file format standard IFC (Industry Foundation Classes) as one way to store and preserve BIM data