Robust Defence Against Zero-Dynamics Attacks in Power Systems

This repository contains the Simulink implementation of ideal and robust control strategies designed to compensate zero-dynamics attacks (ZDAs) in power systems, developed as part of a university project for the course System and Control Methods for Cyber-Physical Security.

🏫 Course Information

Department of Computer, Control and Management Engineering
Sapienza University of Rome
Course: System and Control Methods for Cyber-Physical Security
Author: Andrea Di Paolo and Emanuele De Bianchi

📘 Project Overview

Zero-Dynamics Attacks (ZDAs) are stealthy cyber-physical threats that exploit the internal unobservable dynamics of a power grid to destabilize it. This project studies a defense framework that includes:

• Ideal control strategy: Assumes full model knowledge and allows for perfect decoupling of the attacked and protected subsystems.
• Robust control strategy: Uses an extended high-gain observer to estimate internal states and allows effective decoupling even in the absence of full model knowledge.

🧠 Theoretical Background

The defense design is based on the work of Di Giorgio et al. (2018) which proposes a robust scheme capable of rejecting attacks targeting unobservable system dynamics.

📄 Citation
Di Giorgio, A., Pietrabissa, A., Delli Priscoli, F., Isidori, A. (2018).
Robust protection scheme against cyber-physical attacks in power systems.
IET Control Theory & Applications, 12(13), 1792–1801.

🛠️ Contents

• ideal_defence_zda.slx: Simulink model implementing the ideal defense controller
• ideal_defence_zda.m: MATLAB values for the relative Simulink model
• robust_defence_zda.slx: Simulink model with the robust control scheme using a high-gain observer
• robust_defence_zda.m: MATLAB values for the relative Simulink model
• figure_code.m: MATLAB script to plot the simulation results
• README.md: This file
• img directory: simulations results

🧪 Case Study

The models simulate the WSCC 9-bus system, in which:

• Generator 2 is under attack.
• Generator 3 is protected using the control strategy.
• Generator 1 is unprotected.

Control gains and observer parameters can be adjusted in the .m files.

👨‍🏫 Authors

• Andrea Di Paolo
• Emanuele De Bianchi

Supervised by:
Prof. Francesco Liberati
Department of Computer, Control, and Management Engineering
Sapienza University of Rome

Academic Year: 2021/2022