Online convex optimization with ramp constraints

Masoud Badiei, Na Li, Adam Wierman
2015 2015 54th IEEE Conference on Decision and Control (CDC)  
We study a novel variation of online convex optimization where the algorithm is subject to ramp constraints limiting the distance between consecutive actions. Our contribution is results providing asymptotically tight bounds on the worstcase performance, as measured by the competitive difference, of a variant of Model Predictive Control termed Averaging Fixed Horizon Control (AFHC). Additionally, we prove that AFHC achieves the asymptotically optimal achievable competitive difference within a
more » ... neral class of "forward looking" online algorithms. Furthermore, we illustrate that the performance of AFHC in practice is often much better than indicated by the (worst-case) competitive difference using a case study in the context of the economic dispatch problem.
doi:10.1109/cdc.2015.7403279 dblp:conf/cdc/BadieiLW15 fatcat:oyip6twq5rhk5gwmgqedheqsjy