Optimal Control Systems

About

This is a graduate level course on optimal that will trace the journey of the subject, as it has evolved over more than two millennia. The course, while presenting the different settings under which optimal control problems are usually studied, such as fixed and variable end-points, fixed and variable terminal time, etc., will also connect these paradigms under an overarching theme of dynamic optimization, so that these different settings do not seem like specific cases that need to be memorized. The focus will be more on developing a deep conceptual understanding of the subject matter, as opposed to numerical methods for solving problems in optimal control. The centerpiece of the course would be a complete but accessible proof of Pontryagin’s Maximum Principle (PMP) which would enable the student to see how ideas from calculus of variations fit in perfectly when viewed through the lens of PMP. The course should be particularly useful to graduate students (masters and PhD students) who endeavor to solve theoretical problems in control theory, machine intelligence, data science, robust and optimal control, and related areas.

Intended audience: PGs and PhD from Electrical, Mechanical, Civil, Chem engg. Also MATHS majors and economics majors can attend

Prerequisites: Basic background in college level calculus (usually taught in first year) is necessary. Some background in optimization is helpful, though not necessary.