The Fuzzy Control Of Flexible Cantilever In AFM

As a basic research tool of nanometer science and technology, atomic force microscopy (AFM) has been widely used in various research fields. The micro-cantilever used to manipulate nano-samples, is easily deformed by the interaction of atoms between the tip and sample due to its flexible and micro property. Environmental noises, such as voice and concussion of the ground, can affect the micro-cantilever too. Those deformer and noises may damage the micro-cantilever and deteriorate the control performance. Thus, how to improve its control performance is very important for nano detection and operation. A general control method needs the accurate mathematical model of the micro-cantilever. However, the accurate mathematical model is difficultly obtained because of nonlinear, spatio-temporal property, disturbances, etc.. As an intelligent control, fuzzy logic control (FLC) has a good robustness and not depend on the accurate mathematical model. Motivated by previous discussion, a distributed parameter system model of micro-cantilever is build, and a fuzzy PID control strategy is presented. Analysis and control have been studied on the AFM experimental platform. The main works and achievements are shown as follows:(1) According to the dynamic property of the AFM flexible micro-cantilever and the model of the interaction between the tip and sample, a distributed parameter system model is used for micro-cantilever based on Euler Bernoulli theory. In view of hysteresis and nonlinear characteristics of the piezoelectric tube, the dynamic model of piezoelectric actuator is build using the system identification methods. The overall dynamics model is build by analysising the interaction relationship between micro-cantilever and piezoelectric tube.(2) According to the distributed parameter system model of AFM cantilever, a separation of variables method is used for analysis. Because FLC is widely used in industrial processes due to its inherent robustness under unknown environment, a fuzzy PID control strategy based on separation of variables method is presented. The simulation results show that the control and robust performance is proved by this control strategy.(3) In view of the fuzzy PID control strategy designed, a parameters tuning method with given phase margin is used for the controller. So we can obain the parameters of each fuzzy PID controller with the PID characteristics of fuzzy PID controller. The simulation results show that the parameter tuning method is effective.(4) According to the scanning principle of AFM, the AFM fast scanning experiment with fuzzy PID control based on separation of variables is designed. Combined with the advantages of variable-speed scanning, the scanning performance is improved. The experimental results demonstrate that the fuzzy PID control strategy based on separation of variables method has good control performance, and the variable-speed scanning method based on the fuzzy control strategy is effective.