A fluid power application of alternative robust control strategies

This thesis presents alternative methods for designing a speed controller for a hydrostatic power transmission system. Recognising that such a system, comprising a valve controlled motor supplied by the laboratory ring main and driving a hydraulic pump as a load, contains significant non-linearities, the thesis shows that robust 'modern control' approaches may be applied to produce viable controllers without recourse to the use of a detailed model of the system. In its introduction, it considers why similar approaches to the design of fluid power systems have not been applied hitherto. It then sets out the design and test, in simulation and on a physical rig, of two alternative linear controllers using H∞ based methods and a 'self organising fuzzy logic' controller (SOFLC). In the linear approaches, differences between the characteristics of the system and the simple models of it are accommodated in the controller design route as 'perturbations' or 'uncertainties'. The H∞ based optimisation methods allow these to be recognised in the design. “Mixed sensitivity” and “Loop shaping” methods are each applied to design controllers which are tested successfully on the laboratory rig. The SOFLC in operation does not rely on a model, but instead allows fuzzy control rules to evolve. In the practical tests, the system is subjected to a range of disturbances in the form of supply pressure fluctuations and load torque changes. Also presented are test results for proportional and proportional plus integral (PI) controllers, to provide a reference. It is demonstrated qualitatively that performance using the linear controllers is superior to that using proportional and PI controllers. An increased range of stable operation is achieved by the controller designed using “loop shaping” – performance is enhanced by the use of two controllers selected automatically according to the operating speed, using a “bumpless” transfer routine. The SOFLC proved difficult to tune. However, stable operation was achieved.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Excavations of a second iron age enclosure on Winnall Down, Winchester, Hampshire, 2006

Aerial survey during the 1970s identified two plough-levelled enclosures, 300m apart, on Winnall Down, Winchester. One of these, Winnall Down I, was excavated by Fasham (1985) in advance of the M3 motorway extension, and revealed evidence for intensive Bronze Age and Iron Age occupation. The adjacent enclosure, Winnall Down II, was not examined by Fasham however, and its date and relationship to Winnall Down I was not known. This paper details the results of a small-scale research excavation on Winnall Down II. It established that some occupation within both enclosures was contemporaneous and this arrangement implies complex agreements over land apportionment and agricultural activities

Frequent Occurrence of an Intron 4 Mutation in Multiple Endocrine Neoplasia Type 1

MEN1 is an autosomal dominant disorder characterized by parathyroid, pituitary, and pancreatic tumors. The MEN1 gene is located on chromosome 11q13 and encodes a 610-amino acid protein. MEN1 mutations are of diverse types and are scattered throughout the coding region, such that almost every MEN1 family will have its individual mutation. To further characterize such mutations we ascertained 34 unrelated MEN1 probands and undertook DNA sequence analysis. This identified 17 different mutations in 24 probands (2 nonsense, 2 missense, 2 in-frame deletions, 5 frameshift deletions, 1 frameshift deletional-insertion, 3 frameshift insertions, 1 donor splice site mutation, and a g-->a transition that resulted in a novel acceptor splice site in intron 4). The intron 4 mutation was found in 7 unrelated families, and the tumors in these families varied considerably, indicating a lack of genotype-phenotype correlation. However, this intron 4 mutation is the most frequently occurring germline MEN1 mutation ( approximately 10% of all mutations), and together with 5 others at codons 83-84, 118-119, 209-211, 418, and 516, accounts for 36.6% of all mutations, a finding that indicates an approach for identifying the widely diverse MEN1 mutations