The Control Algorithm Of Damper Gear Based On MR

The damper landing gear based on magneto rheological fluid has characteristics of nonlinearity and time-varying volatility, which can not be precisely controlled by the traditional PID because of its good control effect only for the linear system and no self-adaption for parameter setting. Therefore, the self-learning algorithm combined with the traditional PID become a research focus to solve controller system problem of the damper landing gear based on magneto rheological.Firstly, the dynamic mechanical model of magneto rheological damper on landing gear was established and dynamic differential equations were listed according to the model. The simulation curve was analyzed from the time domain and frequency domain simulation of the dynamic characteristics in MATLAB. From the simulation response curve, the conclusion can be made that the relative displacement and acceleration can be used as the feedback information and the measure of effect of shock absorption on the control system.The neural network has formidable ability to solve nonlinear mapping problems, and combine it with the traditional PID, not only to overcome the shortcomings of traditional PID controller that cannot adjust the parameters in real time online, but also reflect the characteristics of self-learning and adaptive on neural network. For characteristics of nonlinearity and time-varying volatility of landing gear based on MR damper, a BP neural network PID controller with a momentum was designed on basis of established dynamic mathematical model. BP neural network would adjust three parameters of PID online in time.The controller was inputted the energy which was combined by the feedback of acceleration and displacement of the control system, which simplify the network structure inside the controller and reduced the computation time of controller. After compared with PID, the simulation and experiment have showed that BP neural network PID has a better effect.Finally, the control algorithm was brought out on the experimental stage through the design on software and hardware of the controller. Experimental results show that BP-PID had a damping effect to shock absorber of landing gear when controlling displacement and acceleration which validated that the control algorithm is effective to some extension.