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Soft Switched Converters: Theory and Design

Soft switching Converters: Switching loss, basic principles of hard and soft switching.

Evolution of resonant converter topologies. Resonant Load Converters: analysis of series, parallel, LCC and LLC topologies. Resonant Switch Converters (quasi resonant). Resonant Transition Converters- phase modulated topologies, Soft Switched low power high frequency converters
with Auxiliary Switch. Emerging trends in low power high frequency soft switched converters.

Electronic Systems Design

Module 1: Role of Interface Electronics, Analog Electronic Blocks, OPAMP – internal structure, Open-loop gain, Input R, Output R, DC noise sources and their drifts, CMRR, PSRR, Bandwidth and stability, Slew rate, Noise – general introduction,OPAMP Circuits and Analysis - Difference and Instrumentation Amplifiers (3-opamp and 2-opamp), Effect of cable capacitance and wire-re- sistance on CMRR, IA with guards, Biomedical application, Current-mode IA (Howland), Current- input IA, filters, Filters with underdamped response, state-variable filters, All-pass filters, Current Sour

Foundations of Machine Learning

Machine learning basics: capacity, overfitting and underfitting, hyperparameters and validation sets, bias & variance; PAC model; Rademacher complexity; growth function; VC-dimension; fundamental concepts of artificial neural networks; single layer perceptron classifier; multi- layer feed forward networks; single layer feed-back networks; associative memories; introduc- tory concepts of reinforcement learning, Markhov decision process.

Optimization Techniques

Optimization: need for unconstrained methods in solving constrained problems, necessary con- ditions of unconstrained optimization, structure methods, quadratic models, methods of line search, steepest descent method; quasi-Newton methods: DFP, BFGS, conjugate-direction meth- ods: methods for sums of squares and nonlinear equations; linear programming: simplex meth- ods, duality in linear programming, transportation problem; nonlinear programming: Lagrange multiplier, KKT conditions, convex programing

Mathematical Methods

Linear Algebra: n- dimensional Euclidean spaces, linear transformation, Matrices, Eigen values and Eigen vectors, Generalised inverses, SVD.

Numerical Methods: Numerical Solution of nonlinear equations, Direct and iterative methods to solve system of linear equations, Numerical integration – Trapezoidal and Simpson’s rule, Interpolation, Splines and curve fitting, Numerical solution of ODE – Euler’s method and 4th order Runge- Kutta Method.

Emerging and Selected Topics in Power Electronics

Dynamic model of DC-DC converters in DCM: averaged switched model, small signal model- ling of the low frequency model. High frequency dynamics of converter operating in DCM.

Forced commutated AC-AC converters – Matrix Converters: operation, topologies, commutation strategies, voltage modulation – Direct and Indirect schemes.Dynamic model, design of passive elements and control scheme.

Optimal Control Systems

Basic mathematical concepts: Finite dimensional optimization, Infinite dimensional optimization, Con- ditions for optimality, Performance measures for optimal control problems. Dynamic programming: The optimal control law, The principle of optimality, Dynamic programming concept, Recurrence relation, computational procedure, The Hamilton-Jacobi-Bellman equations.

Interface Electronics

Role of Interface Electronics, Example: Linear Position Sensing, Signal conditioners + ADC, Contactless potentiometer (resistance-capacitance scheme) – Methodology, Interface Circuits, Need of Current/Pneumatic Transmission, Analog Electronic Blocks, OPAMP – internal struc- ture, Open-loop gain, Input R, Output R, DC noise sources and their drifts, CMRR, PSRR, Band- width and stability, Slew rate, Noise – general introduction and noise in opamps and their anal- ysis, Noise-equivalent Bandwidth, Output voltage swing, Compensation Techniques.

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