A Convex Solution of the $H_\infty$-Optimal Controller Synthesis Problem for Multi-Delay Systems

TL;DR

This paper presents a convex, operator-based approach to solve the $H_ abla$-optimal control problem for multi-delay systems, enabling efficient synthesis of optimal controllers using semidefinite programming.

Contribution

It introduces a convex formulation of the $H_ abla$-optimal control problem for systems with delays, using linear operator inequalities and positive matrices for SDP-based synthesis.

Findings

Controllers achieve minimal $H_ abla$ norm close to theoretical optimum

Method outperforms high-order Padé approximation-based controllers

Real-time implementation of the synthesized controllers is feasible

Abstract

Optimal controller synthesis is a bilinear problem and hence difficult to solve in a computationally efficient manner. We are able to resolve this bilinearity for systems with delay by first convexifying the problem in infinite-dimensions - formulating the $H_\infty$ optimal state-feedback controller synthesis problem for distributed-parameter systems as a Linear Operator Inequality - a form of convex optimization with operator variables. Next, we use positive matrices to parameterize positive `complete quadratic' operators - allowing the controller synthesis problem to be solved using Semidefinite Programming (SDP). We then use the solution to this SDP to calculate the feedback gains and provide effective methods for real-time implementation. Finally, we use several test cases to verify that the resulting controllers are \textit{optimal} to several decimal places as measured by the minimal achievable closed-loop $H_\infty$ norm, and as compared against controllers designed using high-order Pad\'e approximations.