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.

A Soft Sensor for Viscosity Control of Polymer Extrusion

Viscosity represents a key indicator of product quality in polymer extrusion but has traditionally been difficult to measure in-process in real-time. An innovative, yet simple, solution to this problem is proposed by a Prediction-Feedback observer mechanism. A `Prediction' model based on the operating conditions generates an open-loop estimate of the melt viscosity; this estimate is used as an input to a second, `Feedback' model to predict the pressure of the system. The pressure value is compared to the actual measured melt pressure and the error used to correct the viscosity estimate. The Prediction model captures the relationship between the operating conditions and the resulting melt viscosity and as such describes the specific material behavior. The Feedback model on the other hand describes the fundamental physical relationship between viscosity and extruder pressure and is a function of the machine geometry. The resulting system yields viscosity estimates within 1% error, shows excellent disturbance rejection properties and can be directly applied to model-based control. This is of major significance to achieving higher quality and reducing waste and set-up times in the polymer extrusion industry.

Single sideband FSS with high image rejection

The design of a quasi-optical single sideband filter, which provides more than 30 dB of isolation between the frequency bands 294-305.5 and 329.5-341.5 GHz in the TM plane at 45 degrees incidence, is described. The structure, which consists of three free-standing arrays of dipole slot elements, generates a bandpass spectral response with an insertion loss below 0.5 dB at resonance. Simulated and measured transmission coefficients in the range 250-400 GHz are shown to be in good agreement.

Disturbance attenuation in linear systems via dynamical compensators: A parametric eigenstructure assignment approach

A simple approach is proposed for disturbance attenuation in multivariable linear systems via dynamical output compensators based on complete parametric eigenstructure assignment. The basic idea is to minimise the H-2 norm of the disturbance-output transfer function using the design freedom provided by eigenstructure assignment. For robustness, the closed-loop system is restricted to be nondefective. Besides the design parameters, the closed-loop eigenvalues are also optimised within desired regions on the left-half complex plane to ensure both closed-loop stability and dynamical performance. With the proposed approach, additional closed-loop specifications can be easily achieved. As a demonstration, robust pole assignment, in the sense that the closed-loop eigenvalues are as insensitive as possible to open-loop system parameter perturbations, is treated. Application of the proposed approach to robust control of a magnetic bearing with a pair of opposing electromagnets and a rigid rotor is discussed.

When does national identification lead to the rejection of immigrants? Cross-sectional and longitudinal evidence for the role of essentialist in-group definitions

Two studies were carried out in England to investigate the role of essentialist national group definitions in determining the effect of national identification on prejudice towards immigrants, and asylum seekers in particular. It was expected that the relationship between national identification and prejudice would depend on the degree to which participants endorse an essentialist (`ethnic') definition of their nationality. Consistent with this, Study 1 (N=154) found that national identification is associated with negativity towards asylum seekers only among individuals who endorse an essentialist conception of the group, and shows no significant association with prejudice among those who reject such a conception. Study 2 (N=219) used a longitudinal design conducted over 6 weeks, allowing cross-lagged analysis of causality between essentialism, identification, and behavioural intentions towards asylum seekers. A causal effect of essentialism on willingness to support a group acting against asylum seekers was observed, with no significant causal effect in the reverse direction. The reverse causal direction was observed in the case of support for a group seeking to support asylum seekers, with intended behaviours determining essentialism. The results are discussed in terms of the importance of group definitions in the study of in-group affiliations and prejudice.

The Role of Direct Presentation by Donor Dendritic Cells in Rejection of Minor Histocompatibility Antigen-Mismatched Skin and Hematopoietic Cell Grafts

Background. The success of transplantation is hampered by rejection of the graft by alloreactive T cells. Donor dendritic cells (DC) have been shown to be required for direct priming of immune responses to antigens from major histocompatibility complex-mismatched grafts. However, for immune responses to major histocompatibility complex-matched, minor histocompatibility (H) antigen mismatched grafts, the magnitude of the T-cell response to directly presented antigens is reduced, and the indirect pathway is more important. Therefore, we aimed to investigate the requirement for donor DC to directly present antigen from minor H antigen mismatched skin and hematopoietic grafts.

The inferential monitoring of the screw disturbance torque to predict process fluctuations in polymer extrusion

Polymer extrusion is one of the major methods of processing polymer materials and advanced process monitoring is important to ensure good product quality. However, commonly used process monitoring devices, e.g. temperature and pressure sensors, are limited in providing information on process dynamics inside an extruder barrel. Screw load torque dynamics, which may occur due to changes in solids conveying, melting, mixing, melt conveying, etc., are believed to be a useful indicator of process fluctuations inside the extruder barrel. However, practical measurement of the screw load torque is difficult to achieve. In this work, inferential monitoring of the screw load torque signal in an extruder was shown to be possible by monitoring the motor current (armature and/or field) and simulation studies were used to check the accuracy of the proposed method. The ability of this signal to aid identification and diagnosis of process issues was explored through an experimental investigation. Power spectral density and wavelet frequency analysis were implemented together with a covariance analysis. It was shown that the torque signal is dominated by the solid friction in the extruder and hence it did not correlate well with melting fluctuations. However, it is useful for online identification of solids conveying issues.