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Updated: May 7, 2026

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

Fuzzy sampled-data control for uncertain vehicle suspension systems.

Hongyi Li, Xingjian Jing, Hak-Keung Lam

IEEE Transactions on Cybernetics

|September 18, 2013

Summary

This study introduces fuzzy control for uncertain active suspension systems, ensuring stability and performance with sampled-data controllers. The fuzzy logic approach effectively addresses system uncertainties and meets performance constraints.

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Last Updated: May 7, 2026

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

Area of Science:

Control Engineering
Automotive Systems
Fuzzy Logic Systems

Background:

Active suspension systems are crucial for vehicle dynamics and ride comfort.
Uncertainties in vehicle parameters pose challenges for traditional control methods.
Sampled-data control is essential for modern digital control implementations.

Purpose of the Study:

To design sampled-data H∞ controllers for uncertain active suspension systems.
To ensure asymptotic stability and H∞ disturbance attenuation.
To meet specific suspension performance constraints using a fuzzy control approach.

Main Methods:

Utilized the Takagi-Sugeno (T-S) fuzzy model to represent uncertain active suspension systems.
Developed state-feedback and output-feedback sampled-data controllers.
Employed Lyapunov stability theory and optimization techniques to derive controller existence conditions.

Main Results:

Derived conditions for the existence of both state-feedback and output-feedback sampled-data controllers.
Demonstrated the effectiveness of the proposed fuzzy control method through simulations.
Achieved guaranteed asymptotic stability and H∞ disturbance attenuation for the closed-loop system.

Conclusions:

The proposed Takagi-Sugeno fuzzy model-based sampled-data H∞ control is effective for uncertain active suspension systems.
The method successfully guarantees system stability and performance constraints.
Simulation results validate the practical applicability of the fuzzy control strategy.