Course Details

Course details of EE6433
Course NoEE6433
Course TitleDistributed Optimization for Control
Course Content1. Preliminaries: Graph theory, consensus protocol, convex analysis, convergence analysis, Lyapunov functions 2. Distributed algorithms: Unconstrained algorithms: Distributed sub-gradient, Decentralized inexact gradient tracking, Exact first order algorithm (EXTRA), Push-sum, Push-pull Constrained algorithms: Dual averaging, Dual ascent, Alternating Direction Method of Multipliers (ADMM) 3. With network constraints: Time varying networks, Directed networks, Event-triggered, Resilient optimization, Online optimization 4. Applications in Control: Estimation problem, Power system control, Model predictive control, Coordination of autonomous agents, Rate control of communication networks
Course Offered this semesterNo
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