Reaching Non-Negative Edge Consensus of Networked Dynamical Systems
IEEE Transactions on Cybernetics
|September 19, 2017
Summary
This study develops a distributed algorithm for non-negative edge consensus in networked systems. The research provides conditions for consensus and demonstrates a low-gain feedback technique effective even with input saturation.
Area of Science:
- Control Systems Engineering
- Networked Systems Theory
- Distributed Algorithms
Background:
- Networked linear time-invariant systems require consensus algorithms for coordinated behavior.
- Achieving non-negative edge consensus is crucial for applications like resource allocation and synchronization.
Purpose of the Study:
- To address the problem of non-negative edge consensus in undirected networked linear time-invariant systems.
- To develop a distributed algorithm and derive sufficient conditions for achieving this consensus.
Main Methods:
- Associating each network edge with a state variable and constructing a distributed algorithm.
- Deriving sufficient conditions based on the number of edges.
- Employing linear programming and low-gain feedback for controller design.
Main Results:
- Sufficient conditions for non-negative edge consensus were established, depending solely on the number of edges.
- A simplified design of the feedback gain matrix was achieved using linear programming and low-gain feedback.
- The low-gain feedback technique proved effective for systems with input saturation.
Conclusions:
- The proposed distributed algorithm and derived conditions effectively achieve non-negative edge consensus.
- The low-gain feedback technique offers a robust and simplified approach, particularly for systems with input saturation.
- Numerical simulations validated the theoretical findings and the practical applicability of the methods.
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