Command Filtering-Based Fuzzy Control for Nonlinear Systems With Saturation Input.

Area of Science:

• Control Engineering
• Nonlinear System Dynamics
• Fuzzy Logic Systems

Background:

• Existing control methods struggle with uncertain multi-input multi-output (MIMO) nonlinear systems, particularly those with input saturation.
• The complexity of virtual controller derivatives in traditional approaches can lead to computational challenges.

Purpose of the Study:

• To design a robust command filtering-based fuzzy control strategy for uncertain MIMO nonlinear systems with input saturation.
• To address the computational complexity arising from derivative calculations in virtual controllers.
• To enhance system stability by ensuring all signals remain bounded.

Main Methods:

• Implementation of command filtering to mitigate the explosion of complexity associated with virtual controller derivatives.
• Utilization of fuzzy logic systems for approximating the unknown nonlinear functions within the MIMO systems.
• Incorporation of an error compensation mechanism to overcome limitations of the dynamics surface approach.

Main Results:

• The proposed control method guarantees the boundedness of all system signals, ensuring overall system stability.
• Demonstration of the effectiveness and advantages of the developed control strategy through a simulation example.

Conclusions:

• The command filtering-based fuzzy control approach provides a viable solution for stabilizing uncertain MIMO nonlinear systems with input saturation.
• The method effectively manages system complexity and enhances robustness, as validated by simulation results.