Security tracking control for discrete-time stochastic systems subject to cyber attacks.

Area of Science:

• Control Systems Engineering
• Cybersecurity
• Stochastic Systems

Background:

• Networked control systems (NCSs) are vulnerable to cyber attacks like false data injection and denial-of-service (DoS).
• Ensuring system security and performance under attack is crucial for reliable operation.
• Existing methods may not adequately address probabilistic aspects of attacks and system transient behavior.

Purpose of the Study:

• To design a secure tracking controller for discrete-time stochastic linear NCSs under cyber attacks.
• To achieve probabilistic secure trackability considering attack uncertainties.
• To provide a systematic method for controller design and performance bound determination.

Main Methods:

• Modeling successful attacks as a Bernoulli random sequence, incorporating network factors.
• Defining probabilistic secure trackability for transient NCS trajectories.
• Designing an observer-based dynamic output feedback controller.
• Transforming the problem into probabilistic input-to-state stability using an augmented incremental model.
• Utilizing matrix inequalities and the Schur complementary lemma for controller parameter and cost bound calculation.

Main Results:

• A novel observer-based dynamic output feedback controller is developed.
• Sufficient conditions for probabilistic secure trackability are established.
• Controller parameters and the upper bound of the quadratic cost function are determined.
• The effectiveness of the proposed control scheme is validated through simulations and practical experiments.

Conclusions:

• The proposed control scheme effectively achieves probabilistic secure trackability in NCSs under cyber attacks.
• The methodology provides a robust framework for designing secure controllers in uncertain environments.
• The results demonstrate the practical applicability and effectiveness of the developed control strategy.