An improved adaptive position tracking strategy for automatic shift actuator with uncertain parameters.

Area of Science:

• Control Engineering
• Mechatronics
• Automotive Systems

Background:

• Precise gear position control is difficult due to system nonlinearity, parameter uncertainty, and external disturbances.
• Traditional adaptive control methods face limitations in achieving high-speed convergence and precision.

Purpose of the Study:

• To develop an improved adaptive control strategy for electromechanical clutch actuators.
• To enhance position tracking precision and convergence rate for gear control systems.
• To address challenges posed by nonlinearity and uncertainty in clutch systems.

Main Methods:

• A theoretical model of the electromechanical clutch actuator system was established.
• An enhanced adaptive controller was designed incorporating finite time theory and a power function in the virtual control.
• A parameter update rate was integrated into the control action.

Main Results:

• The stability of the proposed control system was theoretically proven.
• Matlab simulations demonstrated the effectiveness of the finite time-based adaptive control.
• Experimental tests confirmed accurate position tracking and fast convergence speed.

Conclusions:

• The proposed finite time-based adaptive control strategy significantly improves electromechanical clutch position control.
• The method achieves satisfactory performance with enhanced accuracy and speed compared to traditional approaches.
• This research offers a robust solution for precise gear position control in dynamic environments.