Parametric adaptive estimation and backstepping control of electro-hydraulic actuator with decayed memory filter

Area of Science:

• Control Systems Engineering
• Robotics
• Hydraulic Systems

Background:

• Electro-hydraulic systems (EHS) often face parameter uncertainties and external disturbances in practical applications, complicating controller design.
• Accurate parameter estimation and robust control are crucial for improving the dynamic behavior and precision of EHS.

Purpose of the Study:

• To propose a parametric adaptive backstepping control method for EHS to address unknown parameter estimation and disturbances.
• To enhance the dynamic performance and motion control accuracy of EHS, specifically demonstrated on a Two-DOF robotic arm.

Main Methods:

• Utilizing a parametric adaptive estimation law to estimate unknown parameters of the EHS model.
• Designing a recursive backstepping controller with Lyapunov techniques for displacement control.
• Implementing a decayed memory filter to mitigate virtual control explosion and re-estimate external load.

Main Results:

• The proposed adaptive backstepping controller demonstrated superior dynamic performance compared to controllers lacking adaptive and filter estimation.
• Experimental results under critical working conditions validated the effectiveness of the approach.
• Successful motion control of a Two-DOF robotic arm was achieved, showcasing improved dynamic behavior.

Conclusions:

• The developed parametric adaptive backstepping control method effectively handles parameter uncertainties and disturbances in EHS.
• The integration of a decayed memory filter significantly improves the stability and performance of the backstepping controller.
• This approach offers a robust solution for precise motion control in applications involving electro-hydraulic systems.