Fuzzy Adaptive Tracking Control of Constrained Nonlinear Switched Stochastic Pure-Feedback Systems

Area of Science:

• Control Systems Engineering
• Nonlinear Dynamics
• Stochastic Processes

Background:

• Switched stochastic nonlinear systems present significant control challenges due to their complex dynamics and inherent uncertainties.
• Output constraints in these systems are critical for practical applications but complicate controller design.
• Pure feedback structures further limit traditional control methodologies.

Purpose of the Study:

• To develop a robust fuzzy adaptive control strategy for switched stochastic nonlinear systems with output constraints.
• To ensure semiglobal uniform ultimate boundedness of all system states.
• To achieve precise output tracking while strictly adhering to imposed output constraints.

Main Methods:

• A novel nonlinear mapping was proposed to transform the constrained system into an equivalent unconstrained system.
• Fuzzy adaptive control principles were employed to design a controller for the transformed system.
• Lyapunov stability theory was utilized to rigorously prove the system's boundedness and tracking performance.

Main Results:

• The proposed fuzzy adaptive controller guarantees that all signals within the closed-loop system are semiglobally uniformly ultimately bounded.
• The output constraint is effectively satisfied throughout the system's operation.
• The output tracking error converges to a predefined small neighborhood around zero, demonstrating high accuracy.

Conclusions:

• The developed fuzzy adaptive control method offers a viable solution for controlling switched stochastic nonlinear systems with output constraints.
• The nonlinear mapping technique provides an effective way to handle output constraints in this class of systems.
• Simulation results confirm the controller's effectiveness and applicability in practical scenarios.