Position tracking control of electro-hydrostatic actuators via adaptive finite-time backstepping and state...

Area of Science:

• Control Systems Engineering
• Robotics
• Mechatronics

Background:

• Electro-hydrostatic actuators (EHSCs) are crucial in modern automation.
• Controlling EHSCs is challenging due to unmeasured states and external disturbances.
• Existing control methods may struggle with finite-time stability under these conditions.

Purpose of the Study:

• To develop an adaptive finite-time backstepping control strategy for EHSCs.
• To address challenges posed by unmeasured states and system disturbances.
• To enhance the tracking performance and stability of EHSCs.

Main Methods:

• A state observer (SOB) was designed to estimate unmeasured system states.
• An adaptive law utilizing radial basis function neural networks (NNs) was introduced to handle unknown system dynamics.
• A finite-time backstepping control scheme was synthesized incorporating the SOB and adaptive law.

Main Results:

• Theoretical analysis using Lyapunov functions and the backstepping approach confirmed finite-time stability.
• The proposed control scheme effectively guarantees stability even with unmeasured states and disturbances.
• Simulation and experimental results validated the practical applicability and performance of the control algorithm.

Conclusions:

• The proposed adaptive finite-time backstepping control is effective for EHSCs.
• The integration of a state observer and neural network-based adaptive law ensures robust performance.
• The study demonstrates a viable solution for precise control of EHSCs in complex environments.