Vibration Adaptive Control of the Flexible Lunar Regolith Sampler

With respect to the problem of big volume, large weight and high power consumption of lunar sampler nowadays, the paper firstly described a novel flexible mini lunar regolith sampler. Then the vibration model of it is established while drilling. The drilling efficiency can be improved more effectively by controlling the lunar regolith sampler always in the resonance state. But the dynamical modeling of the sampler-regolith system is difficult to obtain and time varies when the sampler is in different depth in the lunar regolith. So we present a method of the vibration frequency fuzzy adaptive control based on the dynamic prediction by using the Levenberg-Marquardt Back Propagation (LMBP) neural networks. The LMBP with a FIR filter in series is used to predict the resonant frequency dynamically. And the fuzzy adaptive control is used to calculate the sweeping frequency bandwidth with the input of the amplitude and variation. The simulation and experimental results show that the control algorithm can improve the drilling depth, drilling efficiency and the discarding efficiency effectively