Abstract

In recent years, electro-hydraulic systems have been widely used in many industries and have attracted research attention because of their outstanding characteristics such as power, accuracy, efficiency, and ease of maintenance. However, such systems face serious problems caused simultaneously by disturbances, internal leakage fault, sensor fault, and dynamic uncertain equation components, which make the system unstable and unsafe. Therefore, in this paper, we focus on the estimation of system fault and uncertainties with the aid of advanced fault compensation techniques. First, we design a sliding mode observer using the Lyapunov algorithm to estimate actuator faults that produce not only internal leakage fault but also disturbances or unknown input uncertainties. These faults occur under the effect of payload variations and unknown friction nonlinearities. Second, Lyapunov analysis-based unknown input observer model is designed to estimate sensor faults arising from sensor noises and faults. Third, to minimize the estimated faults, a combination of actuator and sensor compensation fault is proposed, in which the compensation process is performed due to the difference between the output signal and its estimation. Finally, the numerical simulations are performed to demonstrate the effectiveness of the proposed method obtained under various faulty scenarios. The simulation results show that the efficiency of the proposed solution is better than the traditional PID controller and the sensor fault compensation method, despite the influence of noises.

Highlights

  • We consider the influence of actuator fault f a on the electro-hydraulic actuator (EHA) system that is given by Equation (88) in Matlab/Simulink environment with a sinusoidal input signal, as shown in Equation (87)

  • The actuator error compensationbased fault-tolerant control (FTC) process is applied through the actuator fault estimation of the SMO model

  • position and velocity sensor (PVS) fault estimation is effectively executed under the support of the unknown input observer (UIO) model, which is shown in Figures 4b and 5b

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Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. An unknown input observer (UIO) using the extended Kalman-Bucy algorithm is suggested in the combination with the robust sensor FDI model, system states estimator, and time-domain fault information. A fault-tolerant control approach based on a robust fault estimator is carried out to reduce the impact of disturbance, actuator, and sensor fault, applied to electro-hydraulics actuator systems in the presence of simultaneous faults. A fault estimator is designed by integrating the UIO model based on the LMI optimization algorithm and augmented system, such that the control error dynamic reaches the asymptotic state stability. A UIO model integrating the LMI optimization algorithm and augmenting system to estimate sensor fault and to determine residual are described for Lipschitz nonlinear EHA systems.

Modelling Mini Motion Package Electro-Hydraulics Actuator
Robust Actuator Fault Estimation for Nonlinear System
Sliding Mode Observer Design
Actuator Fault Estimation
Actuator and Sensor Fault-Tolerant Control
Actuator and Sensor Fault Compensation
Evaluating the Control Error Performance
Simulation Results for Actuator Fault
Sensor Fault Estimation
Simulation Results for Sensor Faults
Conclusions
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