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|Title:||ANALYSIS OF BIOCONTROL SYSTEM—HUMAN VISUAL CONTROL SYSTEM MODELLING|
|Authors:||Arora, Dashmesh Raj|
|Abstract:||The human visual system is classified into three main systems depending upon the closed loop feedback dynamicsthe pupillary light reflex, the eyeball movements and the lens accommodation dynamics. Further the eyeball movements are subclassifisd into vsrsional and vergence eyeball movements. The visual system models are suggested using the sinusoidal rssponse data as the gain and phase shift character istics as a function of frequency. The gain curves corres ponding to different input signal amplitudes and correspond ingly the same phase shift characteristic lead us to analyse the visual systems as the nonlinear models having an ampli tude dependent nonlinear element. This work of the thesis has used the several response data for the different visual systems. The control system techniques along with the computational techniques of system synthesis are employed to develop the nonlinear and optimal mathematical models of the visual systems. Bach nonlinear model of the system is broadly divided into two components, the controlling mechanism device and the controlled mechan ism . The controlling mechanism device is invariably found as a nonlinear element. Each nonlinear controlling device is described mathematically using a bessel function series -vitechnique. The analysis of each complex nonlinear element is psrformsd by decomposing it into several simple nonlinear components. The controlled process reveals the character istics of ths motor mechanism associated with each system. In Chapter I, the qualitative aspects of physiology and anatomy of the visual system are discussed. The visual pathways and the oculomotor system are described. Chapter II deals with the pupillary light reflex dynamics. A nonlinear model of the system is suggested. The neurological interpretations of the differ-nt components of the model are pointed out. An adaptation element in the retina is also observed. The motor mechanism as a third order filter is derived out. The transportational time delay ele ment is characterised by an exponential term. Different fiber types are associated with the motor mechanism and their time constants are studied. In Chapter III, we have developed the statistical optimal models of the pupillary light reflex dynamics taking into account the pupillary noise also. The noise signal is taken as introduced at the input signal level and the central nervous system level respectively. The optimal models show that the pupillary noise is added at the central nervous system level to the system. In Chapter IV, the versional eye movement dynamic is modelled as the nonlinear saccadic and smooth pursuit systems. Different controlling mechanisms are observed. A prediction controller is found in both the systems. The neurological control aspects of the two models are discussed and thus these neurologically distinct control systsms are compared. Chapter V covers the vergence sys movement dynamics. The nonlinear modelB of the fusional and accommodative vergence systems are developed depending on the kind of stimuli. The neuro-physiological interpretations of the two nonlinear models are carried out. The relationship between the two vergence systems is discussed. Finally the versional end vergence control dynamics are compared and their neuro logical control aspects are pointed out. Chapter VI deals with lens accommodation nonlinear modelling and its neurophysiologies! control aspects. The relationship between the lens accommodation and accommodative vergence is studied. Under the concluding remarks of Chapter VII, the overall characterisation of the visual system is outlined. Two interacted models of different visual systems are developed. An integrated model of the eye movements is also suggested. After concluding the thesis work, the scope of the further work on the field is recommended.|
|Appears in Collections:||DOCTORAL THESES (Electrical Engg)|
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