Energy methods for lossless systems using quadratic differential forms


Rao, Shodhan (2008) Energy methods for lossless systems using quadratic differential forms. University of Southampton, School of Electronics and Computer Science, Doctoral Thesis , 194pp.

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Description/Abstract

In this thesis, we study the properties of lossless systems using the concept of quadratic differential forms (QDFs). Based on observation of physical linear lossless systems, we define a lossless system as one for which there exists a QDF known as an energy function that is positive along nonzero trajectories of the system and whose derivative along the trajectories of the system is zero if inputs to the system are made equal to zero. Using this deffnition, we prove that if a lossless system is autonomous, then it is oscillatory. We also give an algorithm whose output is a two-variable polynomial that induces an
energy function of a lossless system and we describe a suitable way of splitting a given energy function into its potential and kinetic energy components. We further study the space of QDFs for an autonomous linear lossless system, and note that this space can be decomposed into the spaces of conserved and zero-mean quantities. We then show that there is a link between zero-mean quantities and generalized Lagrangians of an autonomous linear lossless system.

Finally, we study various methods of synthesis of lossless electric networks like Cauer and Foster methods, and come up with an abstract deffnition of synthesis of a positive QDF that represents the total energy of the network to be synthesized. We show that Cauer and Foster method of synthesis can be cast in the framework of our deffnition. We show that our deffnition has applications in stability tests for linear systems, and we also give a new Routh-Hurwitz like stability test.

Item Type: Thesis (Doctoral)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: University Structure - Pre August 2011 > School of Electronics and Computer Science > Information - Signals, Images, Systems
ePrint ID: 65886
Date Deposited: 25 Mar 2009
Last Modified: 27 Mar 2014 18:47
URI: http://eprints.soton.ac.uk/id/eprint/65886

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