A hierarchical physical model-based approach to predictive control of a thermal power plant for efficient plant-wide disturbance rejection

Extending the work presented in Prasad et al. (IEEE Proceedings on Control Theory and Applications, 147, 523-37, 2000), this paper reports a hierarchical nonlinear physical model-based control strategy to account for the problems arising due to complex dynamics of drum level and governor valve, and demonstrates its effectiveness in plant-wide disturbance handling. The strategy incorporates a two-level control structure consisting of lower-level conventional PI regulators and a higher-level nonlinear physical model predictive controller (NPMPC) for mainly set-point manoeuvring. The lower-level PI loops help stabilise the unstable drum-boiler dynamics and allow faster governor valve action for power and grid-frequency regulation. The higher-level NPMPC provides an optimal load demand (or set-point) transition by effective handling of plant-wide interactions and system disturbances. The strategy has been tested in a simulation of a 200-MW oil-fired power plant at Ballylumford in Northern Ireland. A novel approach is devized to test the disturbance rejection capability in severe operating conditions. Low frequency disturbances were created by making random changes in radiation heat flow on the boiler-side, while condenser vacuum was fluctuating in a random fashion on the turbine side. In order to simulate high-frequency disturbances, pulse-type load disturbances were made to strike at instants which are not an integral multiple of the NPMPC sampling period. Impressive results have been obtained during both types of system disturbances and extremely high rates of load changes, right across the operating range, These results compared favourably with those from a conventional state-space generalized predictive control (GPC) method designed under similar conditions.

Simple and accurate analytical model of planar grids and high-impedance surfaces, comprising metal strips or patches

Simple analytical formulas are introduced for the grid impedance of electrically dense arrays of square patches and for the surface impedance of high-impedance surfaces based on the dense arrays of metal strips or square patches over ground planes. Emphasis is on the oblique-incidence excitation. The approach is based on the known analytical models for strip grids combined with the approximate Babinet principle for planar grids located at a dielectric interface. Analytical expressions for the surface impedance and reflection coefficient resulting from our analysis are thoroughly verified by full-wave simulations and compared with available data in open literature for particular cases. The results can be used in the design of various antennas and microwave or millimeter wave devices which use artificial impedance surfaces and artificial magnetic conductors (reflect-array antennas, tunable phase shifters, etc.), as well as for the derivation of accurate higher-order impedance boundary conditions for artificial (high-) impedance surfaces. As an example, the propagation properties of surface waves along the high-impedance surfaces are studied.

Plant-wide predictive control for a thermal power plant based on a physical plant model

A constrained non-linear, physical model-based, predictive control (NPMPC) strategy is developed for improved plant-wide control of a thermal power plant. The strategy makes use of successive linearisation and recursive state estimation using extended Kalman filtering to obtain a linear state-space model. The linear model and a quadratic programming routine are used to design a constrained long-range predictive controller One special feature is the careful selection of a specific set of plant model parameters for online estimation, to account for time-varying system characteristics resulting from major system disturbances and ageing. These parameters act as nonstationary stochastic states and help to provide sufficient degrees-of-freedom to obtain unbiased estimates of controlled outputs. A 14th order non-linear plant model, simulating the dominant characteristics of a 200 MW oil-fired pou er plant has been used to test the NPMPC algorithm. The control strategy gives impressive simulation results, during large system disturbances and extremely high rate of load changes, right across the operating range. These results compare favourably to those obtained with the state-space GPC method designed under similar conditions.

Interactions of the 67 kDa laminin receptor and its precursor with laminin

The 67LR (67 kDa laminin receptor) enables cells to interact with components of the extracellular matrix The molecule is derived from the 37LRP (37 kDa laminin receptor precursor); however, the precise molecular mechanism of this conversion is unknown. Recombinant 37LRP expressed in and purified from Escherichia colt, bound to human laminin in a SPR (surface plasmon resonance) experiment. 67LR isolated from human breast-cancer-derived cells in culture was also shown to bind to laminin by SPR. However, the kinetics of association are qualitatively different. 37LRP but not 67LR, binds to heparan sulfate. The binding of 37LRP to heparan sulfate did not affect the interaction of 37LRP with laminin In contrast, heparan sulfate reduces the extent of binding of laminin to 67LR. Taken together, these results show that 37LRP has some of the biological activities of 67LR, even prior to the conversion event. However, the conversion affects the sites of interaction with both laminin and heparan sulfate.

A charged-particle microbeam .1. Development of an experimental system for targeting cells individually with counted particles

Charged-particle microbeams provide a unique opportunity to control precisely, the dose to individual cells and the localization of dose within the cell. The Gray Laboratory is now routinely operating a charged-particle microbeam capable of delivering targeted and counted particles to individual cells, at a dose-rate sufficient to permit a number of single-cell assays of radiation damage to be implemented. By this means, it is possible to study a number of important radiobiological processes in ways that cannot be achieved using conventional methods. This report describes the rationale, development and current capabilities of the Gray Laboratory microbeam.

Low-dose hypersensitivity in Chinese hamster V79 cells targeted with counted protons using a charged-particle microbeam

The Gray Laboratory charged-particle microbeam has been used to assess the clonogenic ability of Chinese hamster V79 cells after irradiation of their nuclei with a precisely defined number of protons with energies of 1.0 and 3.2 MeV. The microbeam uses a 1-mum. silica capillary collimator to deliver protons to subcellular targets with high accuracy. The detection system is based on a miniature photomultiplier tube positioned above the cell dish, which detects the photons generated by the passage of the charged particles through an 18-mum-thick scintillator placed below the cells. With this system, a detection efficiency of greater than 99% is achieved. The cells are plated on specially designed dishes (3-mum-thick Mylar base), and the nuclei are identified by fluorescence microscopy. After an incubation period of 3 days, the cells are revisited individually to assess the formation of colonies from the surviving cells. For each energy investigated, the survival curve obtained for the microbeam shows a significant deviation below I Gy from a response extrapolated using the LQ model for the survival data above 1 Gy. The data are well fitted by a model that supports the hypothesis that radioresistance is induced by low-dose hypersensitivity. These studies demonstrate the potential of the microbeam for performing studies of the effects of single charged particles on cells in vitro. The hypersensitive responses observed are comparable with those reported by others using different radiations and techniques. (C) 2001 by Radiation Research Society.

Inverse Gaussian Modeling of Turbulence-Induced Fading in Free-Space Optical Systems

We propose the inverse Gaussian distribution, as a less complex alternative to the classical log-normal model, to describe turbulence-induced fading in free-space optical (FSO) systems operating in weak turbulence conditions and/or in the presence of aperture averaging effects. By conducting goodness of fit tests, we define the range of values of the scintillation index for various multiple-input multiple-output (MIMO) FSO configurations, where the two distributions approximate each other with a certain significance level. Furthermore, the bit error rate performance of two typical MIMO FSO systems is investigated over the new turbulence model; an intensity-modulation/direct detection MIMO FSO system with Q-ary pulse position modulation that employs repetition coding at the transmitter and equal gain combining at the receiver, and a heterodyne MIMO FSO system with differential phase-shift keying and maximal ratio combining at the receiver. Finally, numerical results are presented that validate the theoretical analysis and provide useful insights into the implications of the model parameters on the overall system performance. © 2011 IEEE.

Chemometric techniques in multivariate statistical modelling of process plant

The techniques of principal component analysis (PCA) and partial least squares (PLS) are introduced from the point of view of providing a multivariate statistical method for modelling process plants. The advantages and limitations of PCA and PLS are discussed from the perspective of the type of data and problems that might be encountered in this application area. These concepts are exemplified by two case studies dealing first with data from a continuous stirred tank reactor (CSTR) simulation and second a literature source describing a low-density polyethylene (LDPE) reactor simulation.