Electro-hydraulic servo system is often affected by parameter uncertainties and mismatched random disturbances, which are two major obstacles to achieving high-performance servo control. In this article, a sliding mode adaptive controller is proposed to solve these two problems. The proposed controller employs sliding mode control method to eliminate unknown mismatched disturbances, adaptive design to deal with parametric uncertainties. A new smooth and continuous sliding mode control law is proposed to solve the design conflicts between sliding mode control technology and back-stepping adaptive control technology. The stability of the algorithm is proved based on the Lyapunov theory. Theoretically, the algorithm can make the position tracking error arbitrarily small. Through the co-simulation platform of AMESim and MATLAB/Simulink, the control performance of the developed control algorithm is verified. The results show that the developed sliding mode adaptive controller scheme can achieve high-performance tracking under the condition of parametric uncertainties and unknown mismatched disturbances.

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A sliding mode control method is adapted to the trajectory tracking and positioning control of a heavy-duty hydraulic manipulator in this article, which shows high performance with the drive of hydraulic proportional valve. The dynamic model of the system is established, the complexity of which is reduced based on the singular perturbation theory to simplify the analysis and the online calculation of the control variable. The extended state observer is developed in the control loop to estimate the real-time disturbances including the parameter uncertainties and load changes of the system. The integral sliding mode control law is designed combining the extended state observer, and the stability of the system is proved theoretically. The experimental results on a heavy-duty hydraulic manipulator show that the proposed control method has high dynamic tracking performance and positioning accuracy, and the proposed extended state observer can effectively resist disturbances.

A fault diagnosis system based on LabVIEW is researched to analyze the rotating machinery fault. By developing data acquisition, signal analysis, processing and simulation, pattern recognition and fault diagnosis modules, this system can automatically measure and identify the shaft orbit of a rotor and get fault results. A pattern recognition method on the basis of the invariant moment algorithm is studied with LabVIEW and used to recognize shaft orbit shapes. The experimental results show that the shaft orbit of a rotor can be identified through invariant moment calculation. Because the shape of the shaft orbit of the rotor is close to the ellipse the main fault is imbalance. The fault result is proved to be correct by spectrum analysis. This study is helpful to develop a online fault diagnosis system based on LabVIEW.