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ABOUT THE COURSE:Applications of convex optimization techniques, particularly semidefinite programming and linear matrix inequalities (LMIs), have significantly enriched the theory of optimal and robust control in the past few decades. In this course, first the theory of duality in convex programming and semidefinite programming will be covered. Then, problems pertaining to stability analysis, optimal state feedback controller synthesis, robust stability analysis and robust controller synthesis of linear dynamical systems will be studied and reformulated in terms of LMIs. The underlying theory of dissipativity and integral quadratic constraints will also be covered. Finally, applications of the above tools in the analysis and synthesis of convex optimization algorithms will be discussed. The mathematical treatment will be complemented with an extensive programming and implementation component.INTENDED AUDIENCE: M.Tech and PhD Students in Control Systems specialization as well faculty members from different colleges. The course will also be accessible to final year UG students.PREREQUISITES: The learners should have attended a course on linear systems/control theory from a state-space point of view. Attending an introductory course on optimization would also be helpful.INDUSTRY SUPPORT: Mathworks, General Electric, ABB, DRDO, ISRO, Tata Motors, Adani Defence and Aerospace