With the rapid development of computer science and information and communication technology (ICT), increasingly intelligent, and complex systems have been applied to industries as well as human life. Fault-tolerant control (FTC) has, therefore, become one of the most important topics attracting attention from both engineers and researchers to maintain system performances when faults occur. The ultimate goal of this study was to develop a sensor fault-tolerant control (SFTC) to enhance the robust position tracking control of a class of electro-hydraulic actuators called mini motion packages (MMPs), which are widely used for applications requiring large force-displacement ratios. First, a mathematical model of the MMP system is presented, which is then applied in the position control process of the MMP system. Here, a well-known proportional, integrated and derivative (PID) control algorithm is employed to ensure the positional response to the reference position. Second, an unknown input observer (UIO) is designed to estimate the state vector and sensor faults using a linear matrix inequality (LMI) optimization algorithm. Then an SFTC is used to deal with sensor faults of the MMP system. The SFTC is formed of the fault detection and the fault compensation with the goal of determining the location, time of occurrence, and magnitude of the faults in the fault signal compensation process. Finally, numerical simulations were run to demonstrate the superior performance of the proposed approach compared to traditional tracking control.

Electro-hydraulic actuators (EHAs) have been widely used in modern industries. However, sensor faults and actuator faults in EHA systems can arise due to aging during operation, making the system unstable and unsafe. To solve these issues, fault-tolerant control (FTC) techniques for EHA systems have been studied intensively. In this paper, an FTC is proposed and developed for the mini motion package (MMP) EHA system. First, a mathematical model of the MMP system is formulated and improved to provide position tracking control using a well-known proportional-integral-derivative (PID) controller. Second, an unknown input observer (UIO) reconstruction is performed to estimate the states, disturbances, and sensor faults so that an asymptotically stable control error can be obtained by a linear matrix inequality (LMI) optimization algorithm through Lyapunov’s stability condition. Third, the FTC designed for the nonlinear discrete-time system is formed from fault compensation based on a residual logic signal to implement the fault compensation process and ensure stability and tracking performance with respect to minimizing impacts of disturbances and sensor faults. Here, residual is defined by the difference between state response and state estimation. Finally, numerical simulations and experiments of the MMP system are presented to illustrate the efficiency of the proposed FTC technique.

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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.