Simultaneous estimation of state and packet-loss occurrences in networked control systems

Area of Science:

• Control Systems Engineering
• Networked Systems
• Signal Processing

Background:

• Data packet loss in Networked Control Systems (NCS) impacts control performance and security.
• Accurate estimation of packet loss is crucial for system monitoring and fault detection.
• Existing methods may not simultaneously estimate plant state and packet loss effectively.

Purpose of the Study:

• To develop and evaluate novel methods for simultaneous estimation of plant state and packet loss occurrences in NCS.
• To improve control performance by accounting for data packet loss.
• To enhance the detection of communication failures and cyber-attacks in NCS.

Main Methods:

• Developed a recursive filter using an input-output NCS model for packet loss estimation, followed by Kalman filtering for state estimation.
• Designed a state-space model-based estimator employing a Kalman filter for simultaneous plant state and packet loss estimation.
• Validated proposed methods through a comparative example against an interacting multiple model approach.

Main Results:

• Demonstrated the effectiveness of both proposed estimation methods in a practical example.
• Showcased improved accuracy in simultaneous state and packet loss estimation compared to existing approaches.
• Highlighted the utility of the methods for real-time monitoring and control adjustments.

Conclusions:

• The proposed recursive filter and state-space estimator effectively address simultaneous state and packet loss estimation in NCS.
• These methods offer significant improvements for control performance and system security in networked environments.
• The findings provide valuable tools for diagnosing communication issues and potential cyber threats in NCS.