Fractional-order adaptive fuzzy decentralized tracking control for steer-by-wire system

Area of Science:

• Automotive Engineering
• Control Systems Theory
• Mechatronics

Background:

• Steer-by-wire (SbW) systems are crucial for accurate vehicle steering.
• D-Q axes coupling, time-varying motor parameters, and load disturbances degrade tracking accuracy.
• Existing control strategies struggle with the complex dynamics of SbW systems.

Purpose of the Study:

• To develop a robust control strategy for accurate front wheel angle tracking in SbW systems.
• To address challenges posed by D-Q axes coupling, parameter variations, and external disturbances.
• To enhance the overall performance and reliability of SbW systems.

Main Methods:

• A fractional-order SbW interconnected system model was developed to capture nonlinearities and time-varying dynamics.
• Second-order adaptive fuzzy logic systems (FLSs) with auxiliary functions were designed for function estimation and error compensation.
• A fractional-order command-filtered adaptive backstepping controller was integrated with FLSs for precise tracking control.

Main Results:

• The proposed fractional-order adaptive fuzzy decentralized tracking control (FAFDTC) strategy demonstrated superior performance.
• FAFDTC reduced front wheel angle tracking error by 48.58% and 59.78% compared to existing controllers.
• The controller ensured high tracking accuracy and robustness against disturbances.

Conclusions:

• The FAFDTC strategy effectively mitigates tracking accuracy degradation in SbW systems.
• The proposed method offers significant improvements in steering precision and system robustness.
• This research validates the effectiveness and superiority of the FAFDTC approach for SbW applications.