An Adaptive Predictor-Based Control Approach for Tracking Control of a Hydraulic Actuator System

• Autorzy: Liem, Dao Thanh , Huy, Nguyen Minh , Nam, Le Van , Nu, Ho Thi My
• Języki publikacji: EN

Abstrakty

EN

Electro-hydraulic actuators offer advantages over traditional hydraulic actuators, particularly for high-precision force or position control, but their nonlinear dynamics complicate modelling and control. This study proposes a predictor-integrated adaptive controller to address these challenges. By combining a proportional-integral-derivative controller with a sliding surface, the system tracks desired trajectories, while a parameter optimization rule minimizes errors. Additionally, a smart grey prediction model with dynamic step size adjusts parameters and generates control signals to reduce noise and disturbances. Simulations show improved accuracy and control performance, with a root mean square error reduction of over 50% compared to traditional control algorithms. This adaptive approach ensures precise control in varying conditions, making it suitable for aerospace, automotive, and robotics applications.

Słowa kluczowe

EN

power hydraulics; adaptive control; electrohydraulic actuator; grey predictor; system modelling

• Czasopismo: Advances in Science and Technology. Research Journal
• Rocznik: 2024
• Tom: Vol. 18, no 7
• Strony: 419--436
• Opis fizyczny: Bibliogr. 31 poz., fig., tab.

Twórcy

autor

Liem, Dao Thanh

• Faculty of Mechanical Technology, Ho Chi Minh City University of Industry and Trade, 140 Le Trong Tan, Ho Chi Minh City, Vietnam,

autor

Huy, Nguyen Minh

• Faculty of Mechanical Technology, Ho Chi Minh City University of Industry and Trade, 140 Le Trong Tan, Ho Chi Minh City, Vietnam

autor

Nam, Le Van

• Faculty of Mechanical Technology, Ho Chi Minh City University of Industry and Trade, 140 Le Trong Tan, Ho Chi Minh City, Vietnam

autor

Nu, Ho Thi My

• Faculty of Mechanical Technology, Ho Chi Minh City University of Industry and Trade, 140 Le Trong Tan, Ho Chi Minh City, Vietnam

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Identyfikatory

DOI

10.12913/22998624/193862