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Online feedback-based optimization has become a promising framework forreal-time optimization and control of complex engineering systems. Thistutorial paper surveys the recent advances in the field as well as providesnovel convergence results for primal-dual online algorithms with heterogeneousstep sizes for different elements of the gradient. The analysis is performedfor quadratic programs and the approach is illustrated on applications foradaptive step-size and model-free online algorithms, in the context of optimalcontrol of modern power systems.

Time-Varying Feedback Optimization for Quadratic Programs with Heterogeneous Gradient Step Sizes