A novel intelligent based controller for fast atomic force microscopy - Mahmood, Iskandar Al-Thani (IIUM Press, 2015)
Piezoelectric tube scanner is a major component that used in nanoscale imaging tools such as atomic force microscopy (AFM). This is because it can provide precise nanoscale positioning. However the precision is limited by vibration and some nonlinear drawbacks represented by hysteresis and creep. Hysteresis problem intensifies when positioning is needed at wide range. In this research work, two approaches using artificial intelligent based controllers have been developed. In the first approach, a feed forward multi-layer neural network (MLNN) is trained to shape a proper control signal based on reference input and actual output signals in time domain. In the second approach, the control signal is calculated in frequency domain. A neural network (NN) is trained offline using set of reference signal harmonics to produce the required control signal harmonics. An Inverse Fourier Transform is performed to obtain the time domain control signal. Experimental results obtained from both approaches show that the developed control schemes improves the performance of the system by minimizing the effect of hysteresis.