Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.

Investigations on some amino acid based single crystals for nonlinear optical applications and amino acid capped nanocrystals

Organic crystals possess extremely large optical nonlinearity compared to inorganic crystals. Also organic compounds have the amenability for synthesis and scope for introducing desirable characteristics by inclusions. A wide variety of organic materials having electron donor and acceptor groups, generate high order of nonlinearity. In the present work, a new nonlinear optical crystal, L-citrulline oxalate (LCO) based on the aminoacid L-citrulline was grown using slow evaporation technique. Structural characterization was carried out by single crystal XRD. It crystallizes in the noncentrosymmetric, orthorhombic structure with space group P21 P21 P21. Functional groups present in the sample were identified by Fourier transform infra red (FTIR) and FT-Raman spectral analysis. On studying the FTIR and Raman spectra of the precursors L-citrulline and oxalic acid, used for growing L-citrulline oxalate crystal, it is found that the significant peaks of the precursors are present in the spectra of the L-citrulline oxalate crystal . This observation along with the presence of NH3 + group in the spectra of L-citrulline oxalate, confirms the formation of the charge transfer complex