Consensus-Based Multi-Objective Controller Synthesis

TL;DR

This paper presents a distributed controller synthesis framework for heterogeneous nonlinear agent networks, ensuring scalability and privacy by achieving network-wide consensus on dissipativity variables.

Contribution

It introduces a dissipativity-based approach using the Network Dissipativity Theorem and iterative convex overbounding for scalable, privacy-preserving distributed controller design.

Findings

Enables distributed controller synthesis with privacy preservation.

Achieves network-wide consensus on dissipativity variables.

Applicable to full-state feedback controller synthesis.

Abstract

Despite longstanding interest, controller synthesis remains challenging for networks of heterogeneous, nonlinear agents. Moreover, the requirements for computational scalability and information privacy have become increasingly critical. This paper introduces a dissipativity-based distributed controller synthesis framework for networks with heterogeneous agents and diverse performance objectives, leveraging the Network Dissipativity Theorem and iterative convex overbounding. Our approach enables the synthesis of controllers in a distributed way by achieving a network-wide consensus on agents' dissipativity variables while keeping sensitive subsystem information locally. The proposed framework is applied to full-state feedback controller synthesis.