Model-based controller design for a plastic film extrusion process

This paper reports the development and implementation of a model-based cross-directional controller for plastic film extrusion and other web-forming processes. The controller design has a similar structure to that of internal model control (IMC) with the addition of an observer whose gain is designed to minimise process and model mis-match. The observer gain is obtained by solving a multi-objective optimisation through the application of a genetic algorithm and simulation results are presented in this paper demonstrating improvements that can be achieved by the proposed controller over two existing CD controllers

Modeling and control of a plastic film manufacturing web process

This paper is concerned with the modelling of aplastic film manufacturing process and the development and implementation of a model-based Cross-Directional (CD) controller. The model is derived from first-principles and some empirical relationships. The final validated nonlinear model could provide a useful off-line platform for developing control and monitoring algorithms.A new controller is designed which has a similar structureto that of Internal Model Control (IMC) with the addition ofan observer whose gain is designed to minimise process andmodel mis-match. The observer gain is obtained by solving amulti-objective optimisation problem through the application of a genetic algorithm. The controller is applied to the nonlinear model and simulation results are presented demonstrating improvements that can be achieved by the proposed controller over two existing CD controllers

A control and monitoring oriented model of a film manufacturing process

This paper describes the development of a control and monitoring oriented model of a plastic film manufacturing process. The model is mainly derived from first-principles and has been implemented in the Matlab/Simulink dynamic simulation environment. The development of the model forms the first phase of a project that aims to develop a nonlinear sub-space based monitoring, fault detection and trouble shooting system for the film manufacturing process

Model predictive control of a variable-speed pitch-regulated wind turbine

The Model Predictive Controller is designed for a 5MW variable-speed pitch-regulated wind turbine for three operating points – below rated wind speed, just above rated wind speed, and above rated wind speed. At each operating point, the controllers are designed based on two different linear models of the same wind turbine to investigate the impact of using different control design models (i.e. the model used for designing a model-based controller) on the control performance

Control oriented modelling of a wind turbine and farm

The Matlab/Simulink model of the Supergen (Sustainable Power Generation and Supply) Wind 5 MW exemplar wind turbine, which has been employed by a number of researchers at various institutions and Universities over the last decade, is improved, especially in speed, to facilitate wind farm modelling. Note that wind farm modelling usually involves duplicating wind turbine models, hence the speed of each turbine model is critical in wind farm modelling. The objective is achieved through various stages, including prewarping, implicit and explicit discretisation, and conversion to C. Simulation results are presented to demonstrate that improvement in speed is significant and that the resulting wind turbine model can be used for wind farm modelling more efficiently. It is important to highlight that improvement in speed is achieved without compromising the complexity of the turbine model; that is, each turbine included in a wind farm is not simplified or compromised

Fault detection and diagnosis of a plastic film extrusion process

This paper presents a new approach to the design of a model-based fault detection and diagnosis system for application to a plastic film extrusion process. The design constructs a residual generator via parity relations. A multi-objective optimisation problem must be solved in order for the residual to be sensitive to faults but insensitive to disturbances and modelling errors. In this paper, we exploit a genetic algorithm for solving this multi-objective optimisation problem and the resulting fault detection and diagnosis system is applied to a first-principles model of a plastic film extrusion process. Simulation results demonstrate that various types of faults can be detected and diagnosed successfully

Using improved power electronics modeling and turbine control to improve wind turbine reliability

Improving offshore wind turbine reliability is a key industry goal to improve the availability of this renewable energy generation source. The semiconductor devices in the wind turbine power converter are traditionally considered as the most sensitive and important components to achieve this and managing their thermomechanical stressing is vital, since this is one of their principal long-term aging mechanisms. Conventional deterministic reliability prediction methods used in industrial applications are not suitable for wind turbine applications, due to the stochastic nature of the wind speed. This paper develops an electrothermal model of the power devices, which is integrated with a wind turbine system model for the investigation of power converter thermal cycling under various operating conditions. The model has been developed to eliminate the problems of pulse width modulation switching, substantially reducing simulation time. The model is used to improve the current controller tuning method to reduce thermal stresses suffered by the converter during a grid fault. The model is finally used to design a control method to alleviate a key problem of the doubly fed induction generator—severe thermal cycling caused during operation near synchronous speed

A computational approach for identifying pathogenicity islands in prokaryotic genomes

BACKGROUND: Pathogenicity islands (PAIs), distinct genomic segments of pathogens encoding virulence factors, represent a subgroup of genomic islands (GIs) that have been acquired by horizontal gene transfer event. Up to now, computational approaches for identifying PAIs have been focused on the detection of genomic regions which only differ from the rest of the genome in their base composition and codon usage. These approaches often lead to the identification of genomic islands, rather than PAIs. RESULTS: We present a computational method for detecting potential PAIs in complete prokaryotic genomes by combining sequence similarities and abnormalities in genomic composition. We first collected 207 GenBank accessions containing either part or all of the reported PAI loci. In sequenced genomes, strips of PAI-homologs were defined based on the proximity of the homologs of genes in the same PAI accession. An algorithm reminiscent of sequence-assembly procedure was then devised to merge overlapping or adjacent genomic strips into a large genomic region. Among the defined genomic regions, PAI-like regions were identified by the presence of homolog(s) of virulence genes. Also, GIs were postulated by calculating G+C content anomalies and codon usage bias. Of 148 prokaryotic genomes examined, 23 pathogenic and 6 non-pathogenic bacteria contained 77 candidate PAIs that partly or entirely overlap GIs. CONCLUSION: Supporting the validity of our method, included in the list of candidate PAIs were thirty four PAIs previously identified from genome sequencing papers. Furthermore, in some instances, our method was able to detect entire PAIs for those only partial sequences are available. Our method was proven to be an efficient method for demarcating the potential PAIs in our study. Also, the function(s) and origin(s) of a candidate PAI can be inferred by investigating the PAI queries comprising it. Identification and analysis of potential PAIs in prokaryotic genomes will broaden our knowledge on the structure and properties of PAIs and the evolution of bacterial pathogenesis