| As high-tech of 21st century, nanometer science and technology have been focused on by the world. And almost all countries are competing more and more heatedly in the R&D of nanometer microscope in order to have an advantage in the nanometer research. It is an objective for nanometer instrument researcher to improve the measurement precision of scanning probe microscope (SPM), the eye and hand of nanometer science and technology. In this paper, I analyze the working mechanism of SPM and research deeply the key automation problems, which include: 1) delay compensation control; 2) hysteresis nonlinearity correction; 3) nonorthogonality correction; and 4) SPM calibration. The main contributions are as follows:(1) A robust auto-tuning Smith prediction controller was designed to resolve the long delay time problem of the general controlled object, which consisted of Z-PZT, probe and scanned sample etc. The simulation results indicate that the closed system not only is stable robustly when gain, time constant and delay time of the process vary with the time in the given scope, but also is of good dynamic characteristics, which are small overshoots, fast response and strong ability to eliminate noise and so on.(2) An adaptive-range DNA (ARDNA) soft computing was brought forward. ARDNA solves the contradiction between long coding and high computing precision, which exists in the traditional DNA soft computing. The method is used in function optimization and the simulation results show that ARDNA not only does not need the prior knowledge about the range of the design variables, but also is of strong ability to search globally.(3) Based on the analysis of the nonlinearity of the X-PZT and Y-PZT of SPM, the structure of parameterized hysteresis model was constructed. And the optimized model of PZT was attained by ARDNA, which could optimize the structure and parameters of model simultaneously. Then, the model was used as the reference model, and an incremental feedback controller was designed to get the pseu-inverse model of PZT. In order to eliminate the error between PZT and its reference model, recursive least square (RLS) was introduced to identify the PZT on line. When RLS was stable, thepseu-inverse model of PZT converged to its inverse model. At last, the PZT was in series with its pseu-inverse model to correct its nonlinearity. The simulation results indicate that the nonlinearity correction method is effective.(4) A forward-backward polynomial model was given, which could describe the hysteresis of PZT approximately. In order to get the model, the characteristic data measurement algorithm was investigated from the SPM image of one-dimension or two-dimension raster to get the input-output of PZT. Based on the model, the nonlinearity correction algorithm was put forward to eliminate the image distortion. In addition, we researched the measurement algorithm for the degree of nonorthogonality of X-PZT and Y-PZT and the corresponding nonorthogonality correction algorithm.(5) In this paper, the system identification algorithm is incorporated with Smith predictor to realize Smith on-line identification prediction control in order to compensate the delay of the general controlled object. And it was successfully applied in the AJ-I STM, which was manufactured in the Shanghai Aijian Nanometer Sci. & Tech. Corporation Ltd. The experiment results demonstrate that the method is of strong self-adaptability. And it meets the requirement on tunneling current in AJ-I STM. The nonlinearity correction algorithm, nonorthogonality correction algorithm and SPM calibration algorithm were successfully used in AJ-III AFM which was manufactured in the Shanghai Aijian Nanometer Sci. & Tech. Corporation Ltd.. And a corresponding software was developed by Visual C in order to obtain the parameters for the above-metioned algorithms. The experiment results demonstrate that: 1) all of parameters can be obtained only through few mouse pressing and the image distortion can be eliminated; and 2) the SPM calibration can be realiz...
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