Week 1: Introduction to Adaptive Control; Common myths in control; Vector, Matrix and Signal Norms
Week 2: Barbalat’s Lemma and Illustration of use; Equilibrium definitions;
Week 3: Lyapunov Stability definitions – stability, uniformity, attractivity, asymptotic stability, exponential stability; Stability of Linear systems.
Week 4: Function classes; Definiteness, radial boundedness, decrescence; Lyapunov stability theorems
Week 5: La Salle’s Invariance; Persistence of Excitation; Uniform Complete Observability; Alternate Exponential stability theorems
Week 6: Certainty Equivalence Adaptive control – First and Second order systems; Detectability obstacle and Ortega construction
Week 7: Introduction to Backstepping in Adaptive Control; Backstepping for unmatched unknown
Week 8: Unknown Control Gain adaptation; Model Reference Adaptive Control (MRAC)
Week 9: integrator backstepping adaptation general case; Extended Matching – integrator backstepping adaptation
Week 10: Tuning Functions based integrator backstepping adaptation, Robustness in adaptive control – sigma modification; Parameter projection
Week 11: Initial excitation adaptive control – single and double integrator
Week 12: Deep Learning – Introduction and applications, Radial Basis function based Neural Network function approximation, Multilayer Neural Networks
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