Event-triggered distributed dynamic output-feedback dissipative control of multi-weighted and multi-delayed...

Area of Science:

• Control Systems Engineering
• Networked Systems
• Cyber-Physical Systems

Background:

• Large-scale interconnected systems present challenges due to multiple coupling links with varying weights and delays.
• Quantization, packet dropouts, and stochastic deception attacks degrade system performance and stability.
• Distributed control is essential for managing complex, interconnected systems effectively.

Purpose of the Study:

• To develop an event-triggered distributed dynamic output-feedback control (DOFC) approach.
• To achieve dissipative stabilization for large-scale systems under adverse conditions.
• To ensure exponential mean square stability and strict (Q, S, R)-dissipative performance.

Main Methods:

• Construction of an event-triggered distributed dynamic output feedback controller (DOFC).
• Derivation of sufficient conditions for exponential mean square stability and strict (Q, S, R)-dissipative performance.
• Utilization of the cone complementarity linearization (CCL) algorithm to solve a nonlinear minimization problem for control gains.

Main Results:

• Sufficient conditions for the exponential mean square stability and strict (Q, S, R)-dissipative performance were established.
• The proposed event-triggered DOFC approach effectively handles quantization, packet dropouts, and stochastic deception attacks.
• Control gains were successfully determined using the CCL algorithm.

Conclusions:

• The developed event-triggered distributed dynamic output-feedback control strategy is effective for stabilizing complex large-scale systems.
• The approach guarantees stability and performance under challenging conditions including cyberattacks and data imperfections.
• Numerical verification using a continuous stirred tank reactor (CSTR) system validates the theoretical findings.