Open Access

ARTICLE

Fault-Tolerant Control of the Piston Position via Pressure Sensor and Its Estimation for Mini Motion Package of Electro-Hydraulic Actuator

Huy Q. Tran¹, Tan Nguyen Van^2,*, Cheolkeun Ha³

1 Robotics and Mechatronics Research Group, Faculty of Engineering and Technology, Nguyen Tat Thanh University, Ho Chi Minh City, 754000, Vietnam
2 School of Engineering-Technology, Thu Dau Mot University, Thu Dau Mot City, 590000, Vietnam
3 Robotics and Mechatronics Lab, University of Ulsan, Ulsan, 680749, Republic of Korea

* Corresponding Author: Tan Nguyen Van. Email:

(This article belongs to the Special Issue: Advancements in Machine Fault Diagnosis and Prognosis: Data-Driven Approaches and Autonomous Systems)

Computers, Materials & Continua 2025, 85(1), 1053-1072. https://doi.org/10.32604/cmc.2025.064386

Received 13 February 2025; Accepted 22 April 2025; Issue published 29 August 2025

Abstract

Hydraulic-electric systems are widely utilized in various applications. However, over time, these systems may encounter random faults such as loose cables, ambient environmental noise, or sensor aging, leading to inaccurate sensor readings. These faults may result in system instability or compromise safety. In this paper, we propose a fault compensation control system to mitigate the effects of sensor faults and ensure system safety. Specifically, we utilize the pressure sensor within the system to implement the control process and evaluate performance based on the piston position. First, we develop a mathematical model to identify optimal parameters for the fault estimation model based on the Lyapunov stability principle. Next, we design an unknown input observer that estimates the state vector and detects pressure sensor faults using a linear matrix inequality optimization algorithm. The estimated pressure faults are incorporated into the fault compensation control system to counteract their effects via a fault residual coefficient. The discrepancy between the feedback state and the estimated state determines this coefficient. We assess the piston position’s performance through pressure control to evaluate the proposed model’s effectiveness. Finally, the system simulation results are analyzed to validate the efficiency of the proposed model. When a pressure sensor fault occurs, the proposed approach effectively minimizes position control errors, enhancing overall system stability. When a pressure sensor fault occurs, the proposed model compensates for the fault to mitigate the impact of pressure problem, thereby enhancing the position control quality of the EHA system. The fault compensation method ensures over 90% system performance, with its effectiveness becoming more evident under pressure sensor faults.

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