Distributed Observer and Controller Design for Linear Systems: A Separation-Based Approach
Ganghui Cao, Xunyuan Yin
TL;DR
The paper addresses distributed stabilization for linear time-invariant multi-channel systems with unknown inputs by introducing fully distributed observers that operate without global inputs. It demonstrates that observers and distributed controllers (linear or sliding-mode) can be designed independently, effectively reinstating a separation-principle-like property in a distributed setting via discontinuous consensus and adaptive unknown-input handling. Theoretical guarantees are provided for convergence and boundedness, complemented by numerical demonstrations on heterogeneous multi-agent systems and tracking tasks. The framework offers scalable, robust distributed stabilization and tracking capabilities with practical implications for complex multi-agent networks.
Abstract
This paper investigates the problem of consensus-based distributed control of linear time-invariant multi-channel systems subject to unknown inputs. A distributed observer-based control framework is proposed, within which observer nodes and controller nodes collaboratively perform state estimation and control tasks. Consensus refers to a distributed cooperative mechanism by which each observer node compares its state estimate with those of neighboring nodes, and use the resulting discrepancies to update its own state estimate. One key contribution of this work is to show that the distributed observers and the distributed controllers can be designed independently, which parallels the classical separation principle. This separability within the distributed framework is enabled by a discontinuous consensus strategy and two adaptive algorithms developed specifically for handling the unknown inputs. Theoretical analysis and numerical simulation results demonstrate the effectiveness of the proposed framework in achieving state estimation, stabilization, and tracking control objectives.