Optimal Disturbance Accommodation with Limited Model Information

TL;DR

This paper develops a method for designing optimal dynamic disturbance controllers using limited local model information, analyzing their worst-case performance compared to full-information controllers.

Contribution

It extends existing limited model information control strategies to dynamic controllers and evaluates their performance via the competitive ratio metric.

Findings

Constructs subcontrollers using only local plant data

Analyzes worst-case performance of these controllers

Provides bounds on performance relative to full-information controllers

Abstract

The design of optimal dynamic disturbance accommodation controller with limited model information is considered. We adapt the family of limited model information control design strategies, defined earlier by the authors, to handle dynamic controllers. This family of limited model information design strategies construct subcontrollers distributively by accessing only local plant model information. The closed-loop performance of the dynamic controllers that they can produce are studied using a performance metric called the competitive ratio which is the worst case ratio of the cost a control design strategy to the cost of the optimal control design with full model information.