Data structures and software tools for the computer aided design of control systems: a survey.

CAD software can be structured as a set of modular 'software tools' only if there is some agreement on the data structures which are to be passed between tools. Beyond this basic requirement, it is desirable to give the agreed structures the status of 'data types' in the language used for interactive design. The ultimate refinement is to have a data management capability which 'understands' how to manipulate such data types. In this paper the requirements of CACSD are formulated from the point of view of Database Management Systems. Progress towards meeting these requirements in both the DBMS and the CACSD community is reviewed. The conclusion reached is that there has been considerable movement towards the realisation of software tools for CACSD, but that this owes more to modern ideas about programming languages, than to DBMS developments. The DBMS field has identified some useful concepts, but further significant progress is expected to come from the exploitation of concepts such as object-oriented programming, logic programming, or functional programming.

Investigation and comparison of inverter-fed induction machine loss

This paper presents an investigation into the losses in a three-phase induction motor under different pulse width modulation (PWM) excitation conditions. The impacts of Sinusoidal PWM, Space Vector PWM and Discontinuous PWM on machine loss are compared and studied. Finite element analysis simulations are employed to predict the machine losses with the loss breakdown analysis under different PWM schemes. Direct Calorimetric measurements are utilized to verify the finite element modeling and provide direct quantifications of machine loss under modern PWM techniques. © 2008 IEEE.

The use of object oriented modelling and simulation tools in constraint satisfaction for embodiment design

The software package Dymola, which implements the new, vendor-independent standard modelling language Modelica, exemplifies the emerging generation of object-oriented modelling and simulation tools. This paper shows how, in addition to its simulation capabilities, it may be used as an embodiment design tool, to size automatically a design assembled from a library of generic parametric components. The example used is a miniature model aircraft diesel engine. To this end, the component classes contain extra algebraic equations calculating the overload factor (or its reciprocal, the safety factor) for all the different modes of failure, such as buckling or tensile yield. Thus the simulation results contain the maximum overload or minimum safety factor for each failure mode along with the critical instant and the device state at which it occurs. The Dymola "Initial Conditions Calculation" function, controlled by a simple software script, may then be used to perform automatic component sizing. Each component is minimised in mass, subject to a chosen safety factor against failure, over a given operating cycle. Whilst the example is in the realm of mechanical design, it must be emphasised that the approach is equally applicable to the electrical or mechatronic domains, indeed to any design problem requiring numerical constraint satisfaction.

Cross-Lingual spoken language understanding from unaligned data using discriminative classification models and machine translation

This paper investigates several approaches to bootstrapping a new spoken language understanding (SLU) component in a target language given a large dataset of semantically-annotated utterances in some other source language. The aim is to reduce the cost associated with porting a spoken dialogue system from one language to another by minimising the amount of data required in the target language. Since word-level semantic annotations are costly, Semantic Tuple Classifiers (STCs) are used in conjunction with statistical machine translation models both of which are trained from unaligned data to further reduce development time. The paper presents experiments in which a French SLU component in the tourist information domain is bootstrapped from English data. Results show that training STCs on automatically translated data produced the best performance for predicting the utterance's dialogue act type, however individual slot/value pairs are best predicted by training STCs on the source language and using them to decode translated utterances. © 2010 ISCA.