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چكيده انگليسي :

1 Design of a localization algorithm based on distributed state estimation for wireless sensor networks Negin Sayyaf negin sayyaf@gmail com August 28 2012 Department of Electrical and Computer Engineering Isfahan University of Technology 84156 83111 IranDegree M Sc Language FarsiSupervisor Dr Jafar Ghaisari ghaisari@cc iut ac irAbstractIn recent years analysis estimation and control of distributed systems have gained considreble attention because of advances in the fields of electronics wireless communications and mems technology for sensorsimplementation Many research teams are formed around the world to model and analyze these systems State estimation of distributed systems is important to identify and control their performance A centralizedstate estimation algorithm although possibly easy to design is neither robust nor scalable The large scalesystems are very high dimensional thus they require extensive computations to implement a centralizedapproach and the span of the geographical region over which a wide area system is deployed poses a largecommunication burden to implement a centralized procedure A computationally efficient implementation isto employ a distributed algorithm that relies only on local communication and low order computation Hence design and analysis of distributed algorithms is vital for efficient and scalable operation of large scalecomplex infrastructures In this thesis distributed state estimation algorithms for both linear and nonlinearwide area systems are proposed and their convergence conditions are studied In the proposed distributedstate estimation methods after the spatial decomposition of the broad system to overlap subsystems with thefewer dimensions a recursive distributed algorithm for local state estimation is presented It should be notedthat in nonilinear systems each subsystem after model linearization around previous estimation in each timestep estimates local state variables At the end of each time step estimates of each state variable to be sharedbetween overlap subsystems by the weighted average algorithm Estimation algorithms presented in thisthesis unlike previous similar cases are completely decentralized and nowhere in the network storage communication or computation of the global system dimensional vectors and matrices are needed Inseparate theories and using the Lyapunov functional technique sufficient conditions are presented toguarantee the exponentially boundedness in mean square and bounded with probability one of the estimationerrors in both linear and nonlinear proposed estimation methods A numerical example is provided to showeffectiveness and applicability of proposed algorithm Localization is a fundamental problem in sensornetworks Information about locations of sensors is the key to process the sensors measurements accurately Due to measurement noise analytical methods are not effective enough Finally in this thesis as anapplication of wide area nonlinear systems a localization algorithm based on distributed state estimation inthe presence of noise will be presented In the proposed algorithm the minimum number of anchor nodes iscalculated and one of the most important advantages of this approach is a drastic reduction of the number ofanchors Also it will be proved that using m 1 anchor nodes in m dimansional space the proposedlocalization method is convergence and the estimation error is exponentially bounded in mean square Simulation results demonestrate the convergence of estimated coordinations to actual sensors locations Keywords Distributed state estimation Large scale systems Spatial decomposition Overlap subsystems Sensor localization Data fusion Anchor node Exponentially bounded in mean square

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