A novel approach to modelling and exploiting uncertainty in stochastic control systems

We consider an inversion-based neurocontroller for solving control problems of uncertain nonlinear systems. Classical approaches do not use uncertainty information in the neural network models. In this paper we show how we can exploit knowledge of this uncertainty to our advantage by developing a novel robust inverse control method. Simulations on a nonlinear uncertain second order system illustrate the approach.

Monetary models of exchange rates and sweep programs

Numerous studies find that monetary models of exchange rates cannot beat a random walk model. Such a finding, however, is not surprising given that such models are built upon money demand functions and traditional money demand functions appear to have broken down in many developed countries. In this article, we investigate whether using a more stable underlying money demand function results in improvements in forecasts of monetary models of exchange rates. More specifically, we use a sweep-adjusted measure of US monetary aggregate M1 which has been shown to have a more stable money demand function than the official M1 measure. The results suggest that the monetary models of exchange rates contain information about future movements of exchange rates, but the success of such models depends on the stability of money demand functions and the specifications of the models.

Modelling and improving maintenance decisions:Having foresight with simulation and artificial intelligence

Machine breakdowns are one of the main sources of disruption and throughput fluctuation in highly automated production facilities. One element in reducing this disruption is ensuring that the maintenance team responds correctly to machine failures. It is, however, difficult to determine the current practice employed by the maintenance team, let alone suggest improvements to it. 'Knowledge based improvement' is a methodology that aims to address this issue, by (a) eliciting knowledge on current practice, (b) evaluating that practice and (c) looking for improvements. The methodology, based on visual interactive simulation and artificial intelligence methods, and its application to a Ford engine assembly facility are described. Copyright © 2002 Society of Automotive Engineers, Inc.

Modelling and improving human decision making with simulation

Modelling human interaction and decision-making within a simulation presents a particular challenge. This paper describes a methodology that is being developed known as 'knowledge based improvement'. The purpose of this methodology is to elicit decision-making strategies via a simulation model and to represent them using artificial intelligence techniques. Further to this, having identified an individual's decision-making strategy, the methodology aims to look for improvements in decision-making. The methodology is being tested on unplanned maintenance operations at a Ford engine assembly plant

Modelling and benchmarking business processes: The supply-line example

Benchmarking techniques have evolved over the years since Xerox’s pioneering visits to Japan in the late 1970s. The focus of benchmarking has also shifted during this period. By tracing in detail the evolution of benchmarking in one specific area of business activity, supply and distribution management, as seen by the participants in that evolution, creates a picture of a movement from single function, cost-focused, competitive benchmarking, through cross-functional, cross-sectoral, value-oriented benchmarking to process benchmarking. As process efficiency and effectiveness become the primary foci of benchmarking activities, the measurement parameters used to benchmark performance converge with the factors used in business process modelling. The possibility is therefore emerging of modelling business processes and then feeding the models with actual data from benchmarking exercises. This would overcome the most common criticism of benchmarking, namely that it intrinsically lacks the ability to move beyond current best practice. In fact the combined power of modelling and benchmarking may prove to be the basic building block of informed business process re-engineering.

Mathematical modelling and optimal multivariable control of chemical processes

This work reports the developnent of a mathenatical model and distributed, multi variable computer-control for a pilot plant double-effect climbing-film evaporator. A distributed-parameter model of the plant has been developed and the time-domain model transformed into the Laplace domain. The model has been further transformed into an integral domain conforming to an algebraic ring of polynomials, to eliminate the transcendental terms which arise in the Laplace domain due to the distributed nature of the plant model. This has made possible the application of linear control theories to a set of linear-partial differential equations. The models obtained have well tracked the experimental results of the plant. A distributed-computer network has been interfaced with the plant to implement digital controllers in a hierarchical structure. A modern rnultivariable Wiener-Hopf controller has been applled to the plant model. The application has revealed a limitation condition that the plant matrix should be positive-definite along the infinite frequency axis. A new multi variable control theory has emerged fram this study, which avoids the above limitation. The controller has the structure of the modern Wiener-Hopf controller, but with a unique feature enabling a designer to specify the closed-loop poles in advance and to shape the sensitivity matrix as required. In this way, the method treats directly the interaction problems found in the chemical processes with good tracking and regulation performances. Though the ability of the analytical design methods to determine once and for all whether a given set of specifications can be met is one of its chief advantages over the conventional trial-and-error design procedures. However, one disadvantage that offsets to some degree the enormous advantages is the relatively complicated algebra that must be employed in working out all but the simplest problem. Mathematical algorithms and computer software have been developed to treat some of the mathematical operations defined over the integral domain, such as matrix fraction description, spectral factorization, the Bezout identity, and the general manipulation of polynomial matrices. Hence, the design problems of Wiener-Hopf type of controllers and other similar algebraic design methods can be easily solved.

Modelling and control of a hybrid stepping motor

The integration of a microprocessor and a medium power stepper motor in one control system brings together two quite different disciplines. Various methods of interfacing are examined and the problems involved in both hardware and software manipulation are investigated. Microprocessor open-loop control of the stepper motor is considered. The possible advantages of microprocessor closed-loop control are examined and the development of a system is detailed. The system uses position feedback to initiate each motor step. Results of the dynamic response of the system are presented and its performance discussed. Applications of the static torque characteristic of the stepper motor are considered followed by a review of methods of predicting the characteristic. This shows that accurate results are possible only when the effects of magnetic saturation are avoided or when the machine is available for magnetic circuit tests to be carried out. A new method of predicting the static torque characteristic is explained in detail. The method described uses the machine geometry and the magnetic characteristics of the iron types used in the machine. From this information the permeance of each iron component of the machine is calculated and by using the equivalent magnetic circuit of the machine, the total torque produced is predicted. It is shown how this new method is implemented on a digital computer and how the model may be used to investigate further aspects of the stepper motor in addition to the static torque.

Mathematical modelling and optimisation of a water heat pump

The purpose of the work described here has been to seek methods of narrowing the present gap between currently realised heat pump performance and the theoretical limit. The single most important pre-requisite to this objective is the identification and quantitative assessment of the various non-idealities and degradative phenomena responsible for the present shortfall. The use of availability analysis has been introduced as a diagnostic tool, and applied to a few very simple, highly idealised Rankine cycle optimisation problems. From this work, it has been demonstrated that the scope for improvement through optimisation is small in comparison with the extensive potential for improvement by reducing the compressor's losses. A fully instrumented heat pump was assembled and extensively tested. This furnished performance data, and led to an improved understanding of the systems behaviour. From a very simple analysis of the resulting compressor performance data, confirmation of the compressor's low efficiency was obtained. In addition, in order to obtain experimental data concerning specific details of the heat pump's operation, several novel experiments were performed. The experimental work was concluded with a set of tests which attempted to obtain definitive performance data for a small set of discrete operating conditions. These tests included an investigation of the effect of two compressor modifications. The resulting performance data was analysed by a sophisticated calculation which used that measurements to quantify each dagradative phenomenon occurring in that compressor, and so indicate where the greatest potential for improvement lies. Finally, in the light of everything that was learnt, specific technical suggestions have been made, to reduce the losses associated with both the refrigerant circuit and the compressor.

Modelling and measurements on a condensing counter-flow heat exchanger

Experimental investigations and computer modelling studies have been made on the refrigerant-water counterflow condenser section of a small air to water heat pump. The main object of the investigation was a comparative study between the computer modelling predictions and the experimental observations for a range of operating conditions but other characteristics of a counterflow heat exchanger are also discussed. The counterflow condenser consisted of 15 metres of a thermally coupled pair of copper pipes, one containing the R12 working fluid and the other water flowing in the opposite direction. This condenser was mounted horizontally and folded into 0.5 metre straight sections. Thermocouples were inserted in both pipes at one metre intervals and transducers for pressure and flow measurement were also included. Data acquisition, storage and analysis was carried out by a micro-computer suitably interfaced with the transducers and thermocouples. Many sets of readings were taken under a variety of conditions, with air temperature ranging from 18 to 26 degrees Celsius, water inlet from 13.5 to 21.7 degrees, R12 inlet temperature from 61.2 to 81.7 degrees and water mass flow rate from 6.7 to 32.9 grammes per second. A Fortran computer model of the condenser (originally prepared by Carrington[1]) has been modified to match the information available from experimental work. This program uses iterative segmental integration over the desuperheating, mixed phase and subcooled regions for the R12 working fluid, the water always being in the liquid phase. Methods of estimating the inlet and exit fluid conditions from the available experimental data have been developed for application to the model. Temperature profiles and other parameters have been predicted and compared with experimental values for the condenser for a range of evaporator conditions and have shown that the model gives a satisfactory prediction of the physical behaviour of a simple counterflow heat exchanger in both single phase and two phase regions.