The Study Of Semi-active Control Based On The Magneto Rheological Damper In Landing Gear

As an important part of aircraft, landing gear bears the weight of aircraft, absorbs the loadings while the aircraft taking off, landing and taxing. It's great significance to improve the safety and comfort of aircraft. And most of the shock absorption effect is done by the damper in the landing gear. Magneto rheological damper is a new kind of semi-active control type of damper, with the advantage of short response time and high reliability. By making a proper semi-active algorithm and applying on the landing gear, it can retard the vibration of aircraft and improve its comfort. This is the objective of this thesis.Firstly, the mechanics model of the landing gear damper system is established by this thesis, and then, the model on the passive control and semi-active control simulation is simulated by Simulink with time domain and frequency domain respectively, and its dynamic characteristics by the result of simulation is analyzed. At last, an evaluation system is set to evaluate the control effect between different algorithms.Secondly, the optimal control algorithm and particle swarm optimization algorithm is studied by this thesis. By improving the weight matrix, setting an optimal control strategy, to realize the simulation control on Simulink. The simulation results show that the traditional optimal control algorithm can only make the landing gear achieve better control effect on a certain aspect but not on every aspect. And the PSO-optimal control algorithm can achieve a better effect on comprehensive performance, but the actual application will be more complex.And then, the fuzzy control algorithm is studied by this thesis, and a variable universe fuzzy PID control algorithm is proposed. And its simulation is made in Matlab. The results show that this algorithm is greatly superior to the traditional passive control, and compared with the optimal control algorithm, this algorithm solved the local performance deterioration problems which produced by optimal control algorithm, and it's much simpler than the former algorithm in actual application.Finally, combining with the existing experimental data and the simulation experiments in the simulation platform, found that the simulation result is consistent with the experimental results, this control method is effective.