The model-free adaptive controller (MFAC) for continuous rotary electro-hydraulic servo motor was proposed to deal with uncertainties such as friction, leakage and noise. The model of electro-hydraulic servo motor system was replaced by universal model, and the structure adaptive control and parameter adaptive control were combined, and MFAC controller of the motor system was designed by using the input and output data of the system to realize the low speed and tracking control of the motor system. It is proved by simulation and experiment that MFAC controller effectively improves the low-speed stability and anti-interference ability of electro-hydraulic servo system compared with traditional PID control, and MFAC controller widens the frequency response of the system and realizes the precise control of continuous rotary motor servo system.

Aiming at the problem that the blasting vibration signal contains trend items and noise interference, a signal processing method based on the Fourier decomposition method (FDM) is introduced. Firstly, based on the FDM theory, the original blasting vibration signal is decomposed to obtain several modal components; then, the dominant component of the signal is filtered according to the dominant frequency of the modal component and its correlation with the original signal; finally, the dominant component is reconstructed to remove the trend item and noise at the same time; spectrum analysis is carried out to verify the effectiveness of the method. The results show that FDM can effectively disperse low‐frequency trend items, high‐frequency noise, and useful signal information while decomposing signals containing trend terms and noise; compared with the existing common methods, it can more effectively retain the original information, which provides a reference for the trend item and noise removal of similar blasting vibration signals.

Due to the uncertainties caused by high non‐linearity, friction, leakage and other external factors existing in the flight simulator with continuous rotary electro‐hydraulic servo motor and the traditional control strategies discontenting with the high‐performance requirements, the mathematical model of continuous rotary electro‐hydraulic position servo system is established and the compound control theory combining proportional‐integral‐derivative (PID) and the predictive function control (PFC) method is proposed. In order to enable the servo system to estimate the influence of uncertainties and correct it by repeating online optimisation continuously, PID–PFC compound controller basing on the structure of internal model control is designed and then applied to continuous rotary electro hydraulic servo system. The simulation results show that compared with the traditional PID, PFC controller, PID–PFC compound control can effectively inhibit the interferences of the electro‐hydraulic servo system, and greatly improve the response speed and tracking performances and expanding the system frequency band width. The accurate control of motor's position can be realised by applying PID–PFC compound control, which can make the servo system has stronger robustness.

A robust control strategy based on Adaboost prediction was proposed for the effects of dynamic uncertainty, parameter perturbation and nonlinear factors such as friction and leakage on the robustness and low-speed performance of the electro-hydraulic servo system. Based on the establishment of the Pol-Ind friction model, according to the mathematical model of the continuous rotary electro-hydraulic servo motor, the structural uncertainty model of the system under parameter perturbation and external perturbation and the generalized state equation of the system are established. The robust controller is designed according to the [ ] control theory. The system feedback mechanism is designed by using the AdaBoost based on the RBF neural network algorithm. The real-time input and output of the system are used as the training sample set for repeated training, and the multiple weak neural network predictors obtained by training are used to form a strong predictor to calculate the forecast output and error of the electro-hydraulic servo system, and the robust controller was used for real-time control. Simulation and experiment show that: compared with the wavelet neural network control, the robust controller based on AdaBoost prediction has a good tracking performance to the slope signal with an input signal of 0.001°/s, and has a high response speed to sinusoidal signal. Under the condition of satisfying the requirement of double 10 index, the maximum response frequency reaches 15 Hz. It can effectively improve the low-speed performance and anti-interference ability of the electro-hydraulic servo system, greatly improve the robustness of the system and expand the frequency band of the system.