Electro-hydrostatic actuation system double-closed-loop model reference adaptive control method

Abstract

The invention discloses an electro-hydrostatic actuation system double-closed-loop model reference adaptive control method which includes the following steps: an actuator pressure difference inner loop control system is constructed, and the damping of an electro-hydrostatic actuator is increased; a feedback channel high-pass filter is added to the actuator pressure difference inner loop control system to eliminate the reduction in stiffness of the electro-hydrostatic actuator caused by damping increase; a model reference adaptive control method is adopted to improve the adaptability to the inherent uncertainty of the actuation system; and a signal-based control output compensator is used to make compensation for the equivalent output control of an adaptive regulator to get the equivalent output of the adaptive regulator after compensation, and the response precision and sensitivity of the system under small signal task instructions are improved. Through the method, the dynamic performance of the system can be adjusted flexibly according to the actual working condition, the speed of response under large signal task instructions is increased, and the sensitivity and accuracy of the system under small signal task instructions are improved significantly.

Description

technical field [0001] The invention relates to a control method of an electrostatic fluid actuator, in particular to a double closed-loop model reference self-adaptive control method of an electrostatic fluid actuation system. technical background [0002] Electrostatic hydraulic actuator is a new type of actuator, which has the advantages of small size, high reliability, light weight, high efficiency, simple pipeline structure, etc. It is used in jacking systems, support systems, flight control systems, advanced Manufacturing and other fields have broad application prospects. However, due to the large moment of inertia of the motor and pump, and insufficient bandwidth and stiffness, the dead zone characteristics of the valve itself, and the non-linear factors of the sub-mechanism itself, the long-term operation caused the drift of parameters such as oil temperature and density, etc. Uncertainty All factors will affect the control performance of the system. In particular,...

AI Technical Summary

Problems solved by technology

However, there are still some difficulties in using intelligent optimization algorithms such as genetic algorithms to solve real-time control problems of electrostatic fluid systems.

In addition, the results presented by the algorithm are accompanied by an overshoot of 4.76%, and its control performance needs to be further improved to expand its scope of application

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