Introduction and motivation; Review of linear algebra and matrix theory; Basic numerical methods in system theory; Solution of ordinary differential equations; State space representation of dynamical systems; Linearization of nonlinear systems; Time response of linear systems in state space form; Stability, Controllability and Observability of linear systems; Pole placement control design; Pole placement observer design; Linear Quadratic Regulator (LQR) for Linear time-invariant systems.
Lyapunov stability theory for Autonomous nonlinear systems; Back-stepping design; Dynamic inversion (Feedback linearization); Optimal dynamic inversion for distributed parameter systems; Applications of neural networks in control system design; Neuro-adaptive control; Nonlinear observers; Lyapunov stability theory for Non-autonomous Systems; Adaptive control for uncertain dynamical systems.
Pre-Requisite: None, but familiarity with MATLAB will be an advantage.
E. Kreyszig: Advanced Engineering Mathematics, 10th Ed., Wiley, 2015.
J. M. Ortega: Matrix Theory: A Second Course, Springer, 2013
S. K. Gupta: Numerical Methods for Engineers, New Age International Pvt. Ltd., 2015.
N. Nise: Control Systems Engineering, Wiley, 7th Ed., 2015.
K. Ogata: Modern Control Engineering, 5th Ed., Pearson, 2009.
H. J. Marquez: Nonlinear Control Systems – Analysis and Design, Wiley, 2003.
J-J E. Slotine and W. Li: Applied Nonlinear Control, Pearson, 1991.