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.

Toxicity, accumulation and depuration of heavy metalsin the brown mussel perna indica

In this thesis certain important aspects of heavy metal toxicity have been worked out. Recent studies have clearly shown that when experimental media contained more than one heavy metals, such metals could conspicuously influence the toxic reaction of the animals both in terms of quantity and nature. The experimental results available on individual metal toxicity show that, in majority of such results, unrealistically high concentrations of dissolved metals are involved. A remarkable number of factors have been shown to influence metal toxicity such as various environmental factors particularly temperature and salinity, the condition of the organism and the ability of some of the marine organisms to adapt to metallic contamination. Further, some of the more sensitive functions like embryonic and larval development, growth and fecundity, oxygen utilization and the function of various enzymes are found to be demonstrably sensitive in the presence of heavy metals. However, some of the above functions could be compensated for by adaptive process. If it is assumed that the presence of a single metal in higher concentrations could affect the life function of marine animals, more than one metal in the experimental media should manifest such effects in a greater scale. Commonly known as synergism or more than additivity, majority of heavy metals bring about synergistic reaction .The work presented in this thesis comprises lethal and sublethal toxicities of different salt forms of copper and silver on the brown mussel Perna indica. during the present investigation sublethal concentrations of copper and silver in their dent effects on survival, oxygen consumption, filtration, accumulation and depuration on Perna indica. The results are presented under different sections to make the presentation meaningful .