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Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

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Stabilization of nonlinear systems using sampled-data output-feedback fuzzy controller based on

¹Department of Electronic Engineering, Division of Engineering, King’s College London, WC2R 2LS London, U.K. hakkeung.lam@kcl.ac.uk

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|September 9, 2011

Summary

This study introduces a novel sampled-data output-feedback (SDOF) fuzzy control approach for nonlinear systems. The sum-of-squares method ensures stability for polynomial fuzzy models, enhancing control system reliability.

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Area of Science:

Control Systems Engineering
Fuzzy Logic Systems
Nonlinear System Analysis

Background:

Investigates the stability challenges in sampled-data output-feedback (SDOF) polynomial-fuzzy-model-based control systems.
Highlights the increased complexity due to relying solely on system output for feedback and the impact of zero-order hold in sampled-data systems.

Purpose of the Study:

To propose and analyze SDOF fuzzy controllers for nonlinear plants represented by polynomial fuzzy models.
To develop stability conditions for systems with SDOF fuzzy controllers, considering variations in fuzzy rule configurations.

Main Methods:

Employs polynomial fuzzy models to represent nonlinear systems.
Utilizes Lyapunov stability theory combined with the sum-of-squares (SOS) approach for stability analysis.
Considers two distinct cases for SDOF fuzzy controllers based on fuzzy rule sharing.

Main Results:

Derives SOS-based stability conditions to ensure the stability of the closed-loop system.
Successfully synthesizes SDOF fuzzy controllers that guarantee system stability.
Simulation examples validate the effectiveness of the proposed control strategy.

Conclusions:

The proposed SDOF fuzzy control approach, utilizing the SOS method, effectively addresses stability concerns in nonlinear sampled-data systems.
The developed stability conditions provide a robust framework for designing reliable fuzzy controllers when only output feedback is available.