Adaptive fuzzy output-feedback event-triggered control for fractional-order nonlinear system

Area of Science:

• Control Engineering
• Nonlinear Systems Theory
• Fractional Calculus

Background:

• Fractional-order nonlinear systems (FONS) present unique control challenges due to their complex dynamics and unmeasurable states.
• Event-triggered control (ETC) strategies are crucial for efficient communication resource management in networked control systems.
• Adaptive fuzzy logic systems (FLSs) offer a powerful approach for approximating unknown nonlinearities in complex systems.

Purpose of the Study:

• To develop an adaptive fuzzy output-feedback event-triggered control (ETC) scheme for fractional-order nonlinear systems (FONS).
• To address the challenge of unmeasurable states in FONS using fuzzy logic systems (FLSs) and state observers.
• To ensure system stability, convergence of tracking and observer errors, and exclusion of the Zeno phenomenon while optimizing communication.

Main Methods:

• Utilizing fuzzy-logic systems (FLSs) for approximating unknown nonlinear functions within the FONS.
• Designing a fuzzy state observer to estimate the unmeasurable states of the system.
• Employing Lyapunov functions and the backstepping dynamic surface control (DSC) technique for controller design.
• Implementing an event-triggered control (ETC) strategy to minimize data transmission.

Main Results:

• The proposed adaptive fuzzy output-feedback ETC scheme guarantees the stability of the controlled fractional-order nonlinear system.
• Tracking errors and observer errors are demonstrated to converge to a small neighborhood around zero.
• The Zeno phenomenon, characterized by infinitely frequent triggering, is successfully excluded by the control design.
• Simulation results validate the effectiveness and availability of the developed ETC algorithm.

Conclusions:

• The adaptive fuzzy output-feedback ETC is an effective approach for controlling fractional-order nonlinear systems with unmeasurable states.
• The integration of FLSs, state observers, and ETC significantly enhances control performance and communication efficiency.
• The proposed method provides a robust solution for complex nonlinear systems, ensuring stability and performance.