Speed sensorless vector control of induction machines

A novel rotor velocity estimation scheme applicable to vector controlled induction motors has been described. The proposed method will evaluate rotor velocity, ωr, on-line, does not require any extra transducers or injection of any signals, nor does it employ complicated algorithms such as MRAS or Kalman filters. Furthermore, the new scheme will operate at all velocities including zero with very little error. The procedure employs motor model equations, however all differential and integral terms have been eliminated giving a very fast, low-cost, effective and practical alternative to the current available methods. Simulation results verify the operation of the scheme under ideal and PWM conditions.

Occupants' adaptive responses and perception of thermal environment in naturally conditioned university classrooms

A year-long field study of the thermal environment in university classrooms was conducted from March 2005 to May 2006 in Chongqing, China. This paper presents the occupants’ thermal sensation votes and discusses the occupants’ adaptive response and perception of the thermal environment in a naturally conditioned space. Comparisons between the Actual Mean Vote (AMV) and Predicted Mean Vote (PMV) have been made as well as between the Actual Percentage of Dissatisfied (APD) and Predicted Percentage of Dissatisfied (PPD). The adaptive thermal comfort zone for the naturally conditioned space for Chongqing, which has hot summer and cold winter climatic characteristics, has been proposed based on the field study results. The Chongqing adaptive comfort range is broader than that of the ASHRAE Standard 55-2004 in general, but in the extreme cold and hot months, it is narrower. The thermal conditions in classrooms in Chongqing in summer and winter are severe. Behavioural adaptation such as changing clothing, adjusting indoor air velocity, taking hot/cold drinks, etc., as well as psychological adaptation, has played a role in adapting to the thermal environment.

Integrated optics for nulling interferometry in the thermal infrared: progress and recent achievements

The search for Earth-like exoplanets, orbiting in the habitable zone of stars other than our Sun and showing biological activity, is one of the most exciting and challenging quests of the present time. Nulling interferometry from space, in the thermal infrared, appears as a promising candidate technique for the task of directly observing extra-solar planets. It has been studied for about 10 years by ESA and NASA in the framework of the Darwin and TPF-I missions respectively. Nevertheless, nulling interferometry in the thermal infrared remains a technological challenge at several levels. Among them, the development of the "modal filter" function is mandatory for the filtering of the wavefronts in adequacy with the objective of rejecting the central star flux to an efficiency of about 105. Modal filtering takes benefit of the capability of single-mode waveguides to transmit a single amplitude function, to eliminate virtually any perturbation of the interfering wavefronts, thus making very high rejection ratios possible. The modal filter may either be based on single-mode Integrated Optics (IO) and/or Fiber Optics. In this paper, we focus on IO, and more specifically on the progress of the on-going "Integrated Optics" activity of the European Space Agency.

Synthesis of broadband anti-reflection coatings for spaceflight infrared optics

A synthesis method is outlined for the design of broadband anti-reflection coatings for use in spaceborne infrared optics. The Golden Section optimisation routine is used to make a search, using designated non-absorptive dielectric thin film combinations, for the coating design which fulfils the required spectral requirements using the least number of layers and different materials. Three examples are given of coatings designed by this method : (I) 1µm to 12µm anti-reflection coating on Zinc Sulphide using Zinc Sulphide and Yttrium Fluoride thin film materials. (ii) 2µm to 14µm anti-reflection coating on Germanium using Germanium and Ytterbium Fluoride thin film materials. (iii) 6µm to 17µm anti-reflection coating on Germanium using Lead Telluride, Zinc Selenide and Barium Fluoride. The measured spectral performance of the manufactured 6µm to 17µm coating on Germanium is given. This is the anti-reflection coating for the germanium optics in the NASA Cassini Orbiter CIRS instrument.

Adaptive designs for Phase I dose-finding studies

Improving methodology for Phase I dose-finding studies is currently of great interest in pharmaceutical and medical research. This article discusses the current atmosphere and attitude towards adaptive designs and focuses on the influence of Bayesian approaches.

Simplified parameter adaptive control

A simple parameter adaptive controller design methodology is introduced in which steady-state servo tracking properties provide the major control objective. This is achieved without cancellation of process zeros and hence the underlying design can be applied to non-minimum phase systems. As with other self-tuning algorithms, the design (user specified) polynomials of the proposed algorithm define the performance capabilities of the resulting controller. However, with the appropriate definition of these polynomials, the synthesis technique can be shown to admit different adaptive control strategies, e.g. self-tuning PID and self-tuning pole-placement controllers. The algorithm can therefore be thought of as an embodiment of other self-tuning design techniques. The performances of some of the resulting controllers are illustrated using simulation examples and the on-line application to an experimental apparatus.

Adaptive deadbeat control of stochastic systems

This paper considers the use of a discrete-time deadbeat control action on systems affected by noise. Variations on the standard controller form are discussed and comparisons are made with controllers in which noise rejection is a higher priority objective. Both load and random disturbances are considered in the system description, although the aim of the deadbeat design remains as a tailoring of reference input variations. Finally, the use of such a deadbeat action within a self-tuning control framework is shown to satisfy, under certain conditions, the self-tuning property, generally though only when an extended form of least-squares estimation is incorporated.

Self-organising neural networks for adaptive control

Self-organizing neural networks have been implemented in a wide range of application areas such as speech processing, image processing, optimization and robotics. Recent variations to the basic model proposed by the authors enable it to order state space using a subset of the input vector and to apply a local adaptation procedure that does not rely on a predefined test duration limit. Both these variations have been incorporated into a new feature map architecture that forms an integral part of an Hybrid Learning System (HLS) based on a genetic-based classifier system. Problems are represented within HLS as objects characterized by environmental features. Objects controlled by the system have preset targets set against a subset of their features. The system's objective is to achieve these targets by evolving a behavioural repertoire that efficiently explores and exploits the problem environment. Feature maps encode two types of knowledge within HLS — long-term memory traces of useful regularities within the environment and the classifier performance data calibrated against an object's feature states and targets. Self-organization of these networks constitutes non-genetic-based (experience-driven) learning within HLS. This paper presents a description of the HLS architecture and an analysis of the modified feature map implementing associative memory. Initial results are presented that demonstrate the behaviour of the system on a simple control task.

Adaptive alarm processor for fault diagnosis on power transmission networks

The authors describe a learning classifier system (LCS) which employs genetic algorithms (GA) for adaptive online diagnosis of power transmission network faults. The system monitors switchgear indications produced by a transmission network, reporting fault diagnoses on any patterns indicative of faulted components. The system evaluates the accuracy of diagnoses via a fault simulator developed by National Grid Co. and adapts to reflect the current network topology by use of genetic algorithms.