IISc Bangalore

Applied Optimal Control and Estimation JAN, 3:0

AE 372

Introduction and Motivation; Review of static optimization; Calculus of variations and Optimal control formulation; Numerical solution of Two-point boundary value problems: Shooting method, Gradient method and Quasi-linearization; Linear Quadratic Regulator (LQR) design: Riccati solution, Stability proof, Extensions of LQR, State Transition Matrix (STM) solution; State Dependent Riccati Equation (SDRE) design; Dynamic programming: HJB theory; Approximate dynamic programming and Adaptive Critic design; MPSP Design and Extensions; Optimal State Estimation: Kalman Filter, Extended Kalman Filter; Robust control design through optimal control and state estimation; Constrained optimal control systems: Pontryagin minimum principle, Control constrained problems, State constrained problems; Neighbouring extremals and Sufficiency conditions; Discrete Time Optimal Control: Generic formulation, Discrete LQR.

Pre-Requisite:  None, but having completed AE 371 or equivalent will be an advantage.

Text books:

Lecture Notes
D. S. Naidu: Optimal Control Systems, CRC Press, 2002.
A. Sinha: Linear Systems: Optimal and Robust Control, CRC Press, 2007.
A. E. Bryson and Y-C Ho: Applied Optimal Control, Taylor and Francis, 1975.
R. F. Stengel: Optimal Control and Estimation, Dover Publications, 1994.
A. P. Sage and C. C. White III: Optimum Systems Control (2nd Ed.), Prentice Hall, 1977.
D. E. Kirk: Optimal Control Theory: An Introduction, Prentice Hall, 1970.
F. L. Lewis: Optimal Control, Wiley, 1986.
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