Indirect Adaptive Interval Type-3 Fuzzy Tracking Control for Nonlinear Discrete-Time Networked Control Systems With...

Area of Science:

• Control Systems Engineering
• Fuzzy Logic Systems
• Cybersecurity in Control

Background:

• Networked control systems (NCSs) are susceptible to cyberattacks like denial-of-service (DoS), which disrupt normal operation.
• Unknown nonaffine nonlinear dynamics in discrete-time NCSs pose significant challenges for robust control design.
• Interval Type-3 (IT3) fuzzy systems offer enhanced uncertainty handling capabilities compared to traditional fuzzy logic.

Purpose of the Study:

• To develop an indirect adaptive interval type-3 (IT3) tracking fuzzy control for unknown nonaffine nonlinear discrete-time NCSs under DoS attacks.
• To propose a novel two-mode attack compensator for estimating unavailable system outputs during attacks.
• To ensure robust tracking performance and bounded tracking errors in NCSs despite uncertainties and DoS attacks.

Main Methods:

• An IT3 fuzzy model (IT3FM) and an IT3 fuzzy controller (IT3FC) are designed using the same IT3 fuzzy sets to reduce computational complexity.
• A two-mode attack compensator is integrated to estimate system outputs during DoS attacks.
• A parameter updating algorithm, guaranteed to converge via Lyapunov theory, is presented for adaptive control.
• A direct defuzzification method is employed to bypass the iterative Karnik-Mendel approach.

Main Results:

• The proposed indirect adaptive IT3 fuzzy control method effectively mitigates the adverse effects of DoS attacks.
• Theoretical analysis confirms the boundedness of the tracking error, demonstrating robust performance.
• The use of IT3 fuzzy sets for both the model and controller, along with direct defuzzification, reduces computational complexity.
• Simulations on three nonlinear NCSs validate the robustness and effectiveness of the proposed control strategy.

Conclusions:

• The developed indirect adaptive IT3 fuzzy control provides a robust solution for NCSs facing DoS attacks and unknown nonlinear dynamics.
• The novel attack compensator and simplified IT3 fuzzy system design enhance practical applicability by reducing computational load.
• The control method ensures reliable system operation and accurate tracking performance in challenging networked environments.