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eess.SY2024
Safety Filter for Robust Disturbance Rejection via Online Optimization
Joyce Lai, Peter Seiler
Disturbance rejection in high-precision control applications can be significantly improved upon via online convex optimization (OCO). This includes classical techniques such as rec…
eess.SY2024
Robust Online Convex Optimization for Disturbance Rejection
Joyce Lai, Peter Seiler
Online convex optimization (OCO) is a powerful tool for learning sequential data, making it ideal for high precision control applications where the disturbances are arbitrary and u…