The application of H controller synthesis to high speed independent drive systems

This thesis describes work completed on the application of H controller synthesis to the design of controllers for single axis high speed independent drive design examples. H controller synthesis was used in a single controller format and in a self-tuning regulator, a type of adaptive controller. Three types of industrial design examples were attempted using H controller synthesis, both in simulation and on a Drives Test Facility at Aston University. The results were benchmarked against a Proportional, Integral and Derivative (PID) with velocity feedforward controller (VFF), the industrial standard for this application. An analysis of the differences between a H and PID with VFF controller was completed. A direct-form H controller was determined for a limited class of weighting function and plants which shows the relationship between the weighting function, nominal plant and the controller parameters. The direct-form controller was utilised in two ways. Firstly it allowed the production of simple guidelines for the industrial design of H controllers. Secondly it was used as the controller modifier in a self-tuning regulator (STR). The STR had a controller modification time (including nominal model parameter estimation) of 8ms. A Set-Point Gain Scheduling (SPGS) controller was developed and applied to an industrial design example. The applicability of each control strategy, PID with VFF, H, SPGS and STR, was investigated and a set of general guidelines for their use was determined. All controllers developed were implemented using standard industrial equipment.

Experimental investigation of the fuel properties of glidfuel, palm oil mill effluent biodiesel and blends

Biofuels derived from industry waste have potential to substitute fossil fuels (Diesel and Gasoline) in internal combustion (IC) engines. Use of waste streams as fuels would help to reduce considerably life-cycle greenhouse gas emissions and minimise waste processing costs. In this study an investigation into the fuel properties of two waste derived biofuels were carried out, they are: (i) Glidfuel (GF) biofuel - a waste stream from paper industry, and (ii) Palm Oil Mill Effluent (POME) biodiesel - biodiesel produced from palm oil industry effluent through various treatment and transesterification process. GF and POME was mixed together at various proportions and separately with fossil diesel (FD) to assess the miscibility and various physical and chemical properties of the blends. Fuel properties such as kinematic viscosity, higher heating value, water content, acid number, density, flash point temperature, CHNO content, sulphur content, ash content, oxidation stability, cetane number and copper corrosion ratings of all the fuels were measured. The properties of GF, POME and various blends were compared with the corresponding properties of the standard FD. Significance of the fuel properties and their expected effects on combustion and exhaust emission characteristics of the IC engine were discussed. Results showed that most properties of both GF and POME biodiesel were comparable to FD. Both GF and POME were miscible with each other, and also separately with the FD. Flash point temperatures of GF and POME biodiesel were 40.7°C and 158.7°C respectively. The flash point temperature of GF was about 36% lower than corresponding FD. The water content in GF and FD were 0.74 (% wt) and 0.01 (% wt) respectively. Acidity values and corrosion ratings of both GF and POME biodiesel were low compared to corresponding value for FD. The study concluded that optimum GF-POME biofuel blends can substitute fossil diesel use in IC engines.

Thermal properties of fibre Bragg gratings inscribed point-by-point by infrared femtosecond laser

Direct, point-by-point inscription of fibre Bragg gratings by an infrared femtosecond laser has been reported recently. Response of these gratings to annealing at temperatures in the range 500 to 1050°C is studied for the first time. Gratings inscribed by infrared femtosecond lasers were thermally stable at temperatures up to 900°C, representing a significant improvement in comparison with the 'common', UV-inscribed, gratings. Annealing at temperatures up to 700°C increased grating reflectivity. © IEE 2005.

Interacting nonequilibrium systems with two temperatures

We investigate a simplified model of two fully connected magnetic systems maintained at different temperatures by virtue of being connected to two independent thermal baths while simultaneously being interconnected with each other. Using generating functional analysis, commonly used in statistical mechanics, we find exactly soluble expressions for their individual magnetization that define a two-dimensional nonlinear map, the equations of which have the same form as those obtained for densely connected equilibrium systems. Steady states correspond to the fixed points of this map, separating the parameter space into a rich set of nonequilibrium phases that we analyze in asymptotically high and low (nonequilibrium) temperature limits. The theoretical formalism is shown to revert to the classical nonequilibrium steady state problem for two interacting systems with a nonzero heat transfer between them that catalyzes a phase transition between ambient nonequilibrium states. © 2013 American Physical Society.

Accurate estimation of isoelectric point of protein and peptide based on amino acid sequences

Motivation: In any macromolecular polyprotic system - for example protein, DNA or RNA - the isoelectric point - commonly referred to as the pI - can be defined as the point of singularity in a titration curve, corresponding to the solution pH value at which the net overall surface charge - and thus the electrophoretic mobility - of the ampholyte sums to zero. Different modern analytical biochemistry and proteomics methods depend on the isoelectric point as a principal feature for protein and peptide characterization. Protein separation by isoelectric point is a critical part of 2-D gel electrophoresis, a key precursor of proteomics, where discrete spots can be digested in-gel, and proteins subsequently identified by analytical mass spectrometry. Peptide fractionation according to their pI is also widely used in current proteomics sample preparation procedures previous to the LC-MS/MS analysis. Therefore accurate theoretical prediction of pI would expedite such analysis. While such pI calculation is widely used, it remains largely untested, motivating our efforts to benchmark pI prediction methods. Results: Using data from the database PIP-DB and one publically available dataset as our reference gold standard, we have undertaken the benchmarking of pI calculation methods. We find that methods vary in their accuracy and are highly sensitive to the choice of basis set. The machine-learning algorithms, especially the SVM-based algorithm, showed a superior performance when studying peptide mixtures. In general, learning-based pI prediction methods (such as Cofactor, SVM and Branca) require a large training dataset and their resulting performance will strongly depend of the quality of that data. In contrast with Iterative methods, machine-learning algorithms have the advantage of being able to add new features to improve the accuracy of prediction. Contact: yperez@ebi.ac.uk Availability and Implementation: The software and data are freely available at https://github.com/ypriverol/pIR. Supplementary information: Supplementary data are available at Bioinformatics online.