Control integrated finite state machine design for photovoltaic module integrated converter

The operation state of photovoltaic Module Integrated Converter (MIC) is subjected to change due to different source and load conditions, while state-swap is usually implemented with flow chart based sequential controller in the past research. In this paper, the signatures for different operational states are evaluated and investigated, which lead to an effective control integrated finite state machine (CIFSM), providing real-time state-swap as fast as the local control loop. The proposed CIFSM is implemented digitally for a boost type MIC prototype and tested under a variety of load and source conditions. The test results prove the effectiveness of the proposed CIFSM design.

Neural network enhanced self tuning adaptive control application for non-linear control of dynamic systems

The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

State-of-the-art in lean design engineering:a literature review on white collar lean

Lean is usually associated with the ‘operations’ of a manufacturing enterprise; however, there is a growing awareness that these principles may be transferred readily to other functions and sectors. The application to knowledge-based activities such as engineering design is of particular relevance to UK plc. Hence, the purpose of this study has been to establish the state-of-the-art, in terms of the adoption of Lean in new product development, by carrying out a systematic review of the literature. The authors' findings confirm the view that Lean can be applied beneficially away from the factory; that an understanding and definition of value is key to success; that a set-based (or Toyota methodology) approach to design is favoured together with the strong leadership of a chief engineer; and that the successful implementation requires organization-wide changes to systems, practices, and behaviour. On this basis it is felt that this review paper provides a useful platform for further research in this topic.

Design and analysis of distributed utility maximization algorithm for multihop wireless network with inaccurate feedback

Distributed network utility maximization (NUM) is receiving increasing interests for cross-layer optimization problems in multihop wireless networks. Traditional distributed NUM algorithms rely heavily on feedback information between different network elements, such as traffic sources and routers. Because of the distinct features of multihop wireless networks such as time-varying channels and dynamic network topology, the feedback information is usually inaccurate, which represents as a major obstacle for distributed NUM application to wireless networks. The questions to be answered include if distributed NUM algorithm can converge with inaccurate feedback and how to design effective distributed NUM algorithm for wireless networks. In this paper, we first use the infinitesimal perturbation analysis technique to provide an unbiased gradient estimation on the aggregate rate of traffic sources at the routers based on locally available information. On the basis of that, we propose a stochastic approximation algorithm to solve the distributed NUM problem with inaccurate feedback. We then prove that the proposed algorithm can converge to the optimum solution of distributed NUM with perfect feedback under certain conditions. The proposed algorithm is applied to the joint rate and media access control problem for wireless networks. Numerical results demonstrate the convergence of the proposed algorithm. © 2013 John Wiley & Sons, Ltd.

Ontologies for crisis management:a review of state of the art in ontology design and usability

The growing use of a variety of information systems in crisis management both by non-governmental organizations (NGOs) and emergency management agencies makes the challenges of information sharing and interoperability increasingly important. The use of semantic web technologies is a growing area and is a technology stack specifically suited to these challenges. This paper presents a review of ontologies, vocabularies and taxonomies that are useful in crisis management systems. We identify the different subject areas relevant to crisis management based on a review of the literature. The different ontologies and vocabularies available are analysed in terms of their coverage, design and usability. We also consider the use cases for which they were designed and the degree to which they follow a variety of standards. While providing comprehensive ontologies for the crisis domain is not feasible or desirable there is considerable scope to develop ontologies for the subject areas not currently covered and for the purposes of interoperability.

Design and analysis of distributed utility maximization algorithm for multihop wireless network with inaccurate feedback

Distributed network utility maximization (NUM) is receiving increasing interests for cross-layer optimization problems in multihop wireless networks. Traditional distributed NUM algorithms rely heavily on feedback information between different network elements, such as traffic sources and routers. Because of the distinct features of multihop wireless networks such as time-varying channels and dynamic network topology, the feedback information is usually inaccurate, which represents as a major obstacle for distributed NUM application to wireless networks. The questions to be answered include if distributed NUM algorithm can converge with inaccurate feedback and how to design effective distributed NUM algorithm for wireless networks. In this paper, we first use the infinitesimal perturbation analysis technique to provide an unbiased gradient estimation on the aggregate rate of traffic sources at the routers based on locally available information. On the basis of that, we propose a stochastic approximation algorithm to solve the distributed NUM problem with inaccurate feedback. We then prove that the proposed algorithm can converge to the optimum solution of distributed NUM with perfect feedback under certain conditions. The proposed algorithm is applied to the joint rate and media access control problem for wireless networks. Numerical results demonstrate the convergence of the proposed algorithm. © 2013 John Wiley & Sons, Ltd.

Supporting learners’ agentic engagement with feedback:a systematic review and a taxonomy of recipience processes

Much has been written in the educational psychology literature about effective feedback and how to deliver it. However, it is equally important to understand how learners actively receive, engage with, and implement feedback. This article reports a systematic review of the research evidence pertaining to this issue. Through an analysis of 195 outputs published between 1985 and early 2014, we identified various factors that have been proposed to influence the likelihood of feedback being used. Furthermore, we identified diverse interventions with the common aim of supporting and promoting learners' agentic engagement with feedback processes. We outline the various components used in these interventions, and the reports of their successes and limitations. Moreover we propose a novel taxonomy of four recipience processes targeted by these interventions. This review and taxonomy provide a theoretical basis for conceptualizing learners' responsibility within feedback dialogues and for guiding the strategic design and evaluation of interventions. Receiving feedback on one's skills and understanding is an invaluable part of the learning process, benefiting learners far more than does simply receiving praise or punishment (Black & Wiliam, 1998 Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5, 7–74. doi:10.1080/0969595980050102[Taylor & Francis Online]; Hattie & Timperley, 2007 Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77, 81–112. doi:10.3102/003465430298487[CrossRef], [Web of Science ®]). Inevitably, the benefits of receiving feedback are not uniform across all circumstances, and so it is imperative to understand how these gains can be maximized. There is increasing consensus that a critical determinant of feedback effectiveness is the quality of learners' engagement with, and use of, the feedback they receive. However, studies investigating this engagement are underrepresented in academic research (Bounds et al., 2013 Bounds, R., Bush, C., Aghera, A., Rodriguez, N., Stansfield, R. B., & Santeen, S. A. (2013). Emergency medicine residents' self-assessments play a critical role when receiving feedback. Academic Emergency Medicine, 20, 1055–1061. doi:10.1111/acem.12231[CrossRef], [PubMed], [Web of Science ®]), which leaves a “blind spot” in our understanding (Burke, 2009 Burke, D. (2009). Strategies for using feedback students bring to higher education. Assessment & Evaluation in Higher Education, 34, 41–50. doi:10.1080/02602930801895711[Taylor & Francis Online], [Web of Science ®]). With this blind spot in mind, the present work sets out to systematically map the research literature concerning learners' proactive recipience of feedback. We use the term “proactive recipience” here to connote a state or activity of engaging actively with feedback processes, thus emphasizing the fundamental contribution and responsibility of the learner (Winstone, Nash, Rowntree, & Parker, in press Winstone, N. E., Nash, R. A., Rowntree, J., & Parker, M. (in press). ‘It'd be useful, but I wouldn't use it’: Barriers to university students' feedback seeking and recipience. Studies in Higher Education. doi: 10.1080/03075079.2015.1130032[Taylor & Francis Online]). In other words, just as Reeve and Tseng (2011 Reeve, J., & Tseng, M. (2011). Agency as a fourth aspect of student engagement during learning activities. Contemporary Educational Psychology, 36, 257–267. doi:10.1016/j.cedpsych.2011.05.002[CrossRef], [Web of Science ®]) defined “agentic engagement” as a “student's constructive contribution into the flow of the instruction they receive” (p. 258), likewise proactive recipience is a form of agentic engagement that involves the learner sharing responsibility for making feedback processes effective.