Transactions of the Institute of Measurement and Control

Thompson, Steve

doi: 10.1177/014233129501700401pmid: N/A

Franke, Dieter

doi: 10.1177/014233129501700402pmid: N/A

The paper addresses discrete systems with a finite number of states which can be modelled by the state equations of a finite automaton. In contrast to traditional work, the paper is based on arithmetic representations of Boolean functions appearing on the right-hand side of the underlying finite state equations. This allows a unifying view of discrete-event systems and classical discrete-time systems. The paper focuses on the special class of arithmetically linear finite state machines. The design of feedback control using reduced-order observers is extended to this class of systems. The procedure will be illustrated by means of two examples.

Bartlett, H.; Whalley, R.; Seale, W.J.

doi: 10.1177/014233129501700403pmid: N/A

Analytical procedures enabling the modelling of variable geometry exhaust gas systems are considered. An automotive application is investigated. Simulation results portraying the effect of step and pulsating increases in gas flow through a vehicle exhaust system are presented.

Fletcher, I.; Wilson, I.; Cox, C.S.

doi: 10.1177/014233129501700404pmid: N/A

A large number of design strategies exist for multivariable control situations. Many of' the methods require a linear time-invariant process characterisation in the form of a state space model or transfer function matrix description. Quite often this is not available and could be evpensive to realise. If this latter route is pursued there needs to be considerable benefits in the quality of the resulting closed-loop performance, especially when compared to those methods which only require minimal system information. The main aim of this paper is to compare a range of multivariable design strategies using a commercial multivariable coupled tank experimental rig as the uncompensated plant,

Lees, M.J.; Young, P.C.; Chotai, A.; Tych, W.

doi: 10.1177/014233129501700405pmid: N/A

The paper discusses the multivariable modelling and control of a glasshouse micro-climate. A linear reduced-order control model is obtained from a nonlinear simulation model using novel data-based model reduction and linearisation techniques. This control model is then used to design two multivariable non-minimal state variable feedback (SVF) control systems. The first utilises an LQoptimal Proportional-Integral-Plus (PIP) design method incorporating multi-objective optimisation of the weighting matrices, achieving partial dynamic decoupling; while the second uses an algebraic approach to combined pole-assignment and full dynamic decoupling. These controllers are evaluated, to ensure robustness, using the nonlinear simulation model, prior to implementation and evaluation on the real glasshouse during the 1993-94 winter growing season. Control results are excellent with very tight control to the desired setpoints in all three climate variables. For example, air temperature is controlled to within 0.5°C of the setpoint for 85% of the validation period, and is shown to be very robust to model uncertainty and extreme weather conditions.

McGurn, S.; Thompson, S.

doi: 10.1177/014233129501700406pmid: N/A

This paper uses heat transfer models to monitor fouling from ash in a coal-fired power generation boiler. In particular, a counterflow heat exchanger model for the economiser and a periodic flow model for the airheater are developed. Model inputs are local measurements of flow, temperature, etc, and the outputs are fouling indices in real time.Results from tests on a transient-load full-scale power station are piesented for both models. Recurring fouling patterns are shown to suggest relationships with time, load and with changes in the in-service cleaning system.