LQG Controller with Sinusoidal Reference Signal Modeling for Spiral Scanning of Atomic Force Microscope


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1 LQG Controller with Sinusoidal Reference Signal Modeling for Spiral Scanning of Atomic Force Microscope Habibullah, I. R. Petersen, H. R. Pota, and M. S. Rana Abstract In this paper, we present a spiral scanning method using an atomic force microscope (AFM). Spiral motion is generated by applying slowly varying amplitude sine wave in the Xaxis and cosine wave in the Yaxis of the piezoelectric tube (PZT) scanner of the AFM. An LQG controller also designed for damping the resonant mode of a PZT scanner for the lateral positioning of the AFM scanner stage. In this control design, an internal model of the reference sinusoidal signal is introduced with the plant model and an integrator with the system error is introduced. A vibration compensator is also designed and included in feedback loop with the plant to suppress the vibration of the PZT at the resonant frequency. Experimental results demonstrate the effectiveness of the proposed scheme. I. INTRODUCTION Rapid progress of nanotechnology is due to the ability to measure, manipulate, and control of matters in nanoscale. Atomic force microscope (AFM) is one of them and it is being used as a tool for characterizing surface topography of material surfaces, biological specimens, etc. with ultrahigh accuracy [. The inventions of scanning tunneling microscope (STM), scanning probe microscope such as the AFM, scanning electron microscope (SEM) and transmission electron microscope (TEM) have revolutionized research in various areas such as material science, nanobiotechnology, nanomedicine, nanopharmaceutics, precision mechanics, optics, microelectronics, etc. [, [3. In spite the enormous reputation of the STM, it has some basic demerits, e.g., with STM one can scan only the conductive samples or those coated with conductive layers. This complicacy was overcome with the invention of the AFM by Binnig [3. A commercially available AFM scans by applying triangular signal in the XPZT and a staircase or ramp signal to the YPZT. In raster scanning, usually scanning speed is kept limited to  percent of the rst resonant frequency of the PZT scanner [. For faster scanning a high frequency triangular signal is needed to be applied. A triangular signal has such characteristics that it contains all odd harmonics of the fundamental frequency. When a triangular signal is input to the PZT, one of the high frequency harmonics excites the resonance and as a result it produces the distorted triangular signal at the free end of the PZT along the Xaxis and generates distorted image. In SPM and other scanner devices such as selective laser sintering machines (SLS) tracking of triangular signal is a major challenge [4. Habibullah, H. R. Pota and I. R. Petersen are with the school of EIT, University of New South Walse, Canberra, ACT6, Australia. and Researchers are concerned about these challenges and many of them have taken steps to use other feedback control techniques instead of PI controllers to improve the accuracy and speed of the AFM. The signal transformation method is implemented to track the reference triangular signal in AFM [5. The H controller is implemented to improve the scanning speed and image quality, and it achieves a scan rate of 5 Hz [6. Creep, hysteresis, and vibration effects are minimized by implementing a proportional plus derivative high gain feedback controller and a feed forward controller [7. The PZT materials have resonant nature due to their mechanical properties, which is also responsible for distorting the output triangular signal and the scanned images. Therefore the damping of the resonant peak of the PZT is also second major issue in the accurate positioning of the AFM scanner. A survey of damping controller is given in Ref. [8. Integral resonant controller is another approach for attenuating the vibration due to the resonant mode of the PZT [9. In spite of the signi cant improvements it remains dif culty to track fast triangular signal due to the nonlinearities and lower bandwidth of the scanner tube. To avoid the dif culties associated with the triangular signal, in this paper we propose a new scanning pattern instead of raster scanning for fast AFM imaging. In this scanning, an externally generated slowly varying amplitudes sinewave and cosinewave are applied to the PZT scanner in XYaxes to force it to move in spiral lines of varying instantaneous radius. This spirals are called Archimedean spiral as shown in Fig.. The distance between two consecutive lines is known as pitch p, which has a property that it will be constant over the sample surface [ and it makes possible to scan uniformly over the surface without missing surface information. As both the axes are forced by sinusoidal signals with single frequency, the resulting system is in steadystate region and avoid the transient behavior that might be occurred in raster scans because of the probe moving from one line to the next. The proposed scanning method can be included in the faster scanning of the AFM with some software modi cation. The reminder of this paper is organized as follows. Description of the AFM and other experimental setup for this work is demonstrated in SectionII. SectionIII explains the modeling of the piezoelectric tube actuator. SectionIV discusses the controller design procedure for tracking the reference sinusoids and damping the resonant mode of the PZT. SectionV presents The performance of the controller and nally SectionVI concludes the paper /3/$3. c 3 IEEE 474
2 y (m) x p and scanning mode was constant force mode. Scan range (X,Y, Z): μm μm μm and resonant frequency for both X and Y is 9 Hz, and 5 khz for ZPZT, that performs X, Y,andZ positioning in the AFM. Displacement from X, Y, andzpzt can be taken from capacitive position sensors which are incorporated with the AFM. The experimental connection is shown in Fig x (m) x 9 Fig.. Spiral lines. II. GENERATION OF SPIRAL MOTION The area of a sample to be scanned in a spiral trajectory of pitch p at a linear velocity v and if the instantaneous radius R with angular velocity ω (rad/sec) at any time t, ω = v R and dr dt = pω π Integrating eqn. we have R = pωt π where R= at t= and pitch p calculated as: p = R number o f spiral curves where number of spiral curves is the number of crossing points on y = orx = line. The spirals generated with de ned parameter is applied to move PZT scanner of AFM in spiral scanning. To do this eqn. 3 is transformed into Cartesian coordinate from polar, as follows: () () (3) (4) Vx= Rsinωt (5) Vy= Rcosωt (6) where Vx and Vy are the input sine and cosine wave with varying amplitude to the X and Y PZT of the AFM scanner respectively. III. EXPERIMENTAL SETUP DETAILS In this work, our experimental setup consists of the NT MDT Ntegra scanning probe microscope (SPM) that is formed a con guration of the AFM as shown in the Fig.. The experimental setup contains some other parts such as signal access module (SAM), control electronics, vibration isolator and a computer to operate the NOVA software. There are some other accessories, these are the signal analyzer (SA), DSP dspace board and high voltage ampli er (HVA) with constant gain of 5 to supply power to the X, Y,and ZPZT by using the SAM as an intermediate device. The scanner is a NTMDT z533cl PI type: scan by sample Fig.. Block diagram of experimental setup used in the AFM positioning. There are three output ports in the SAM marked as LVX, LVY, and LVZ, which permit external access of the signal come out from the controller. The controller is implemented with a dspace board RT3 rapid prototyping system in real time. In this implementation, Simulink block diagram is used, which is run in dspace RT3 to interface with the AFM. The SAM allows to directly access the signals from the internal HVA. The signal coming out from the SAM through channel LVX and LVY have been used as reference signal to implement the proposed controller. The vertical positioning of the AFM is achieved using the existing AFM control software. The dspace is also equipped with control desk software that is interfaced to the AFM by connecting position sensor measurement and control signal which is supplied to the scanner tube. From the experiment, displacement sensor output and generated images are recorded. The experiment is carried out in the AFM laboratory at the Canberra, Australia. IV. MODELING OF PIEZOELECTRIC TUBE SCANNER The PZT is modeled as a singleinput singleoutput (SISO) system when designing the proposed control scheme and experimental frequency response was obtained using a dual channel HP3567A SA. The frequency response generated in the SA is processed in MATLAB and using the prediction error method (PEM), the system s model is characterized [, [. The best t model frequency responses for the X and YPZTs are shown in Fig. 3. The following statespace model is found to be the best t for the XPZT, as illustrated in Fig. 3 where the resonant mode of the PZT is at about to Hz. x x = a x x x + b x u x (7) y x = c x x x + d x u x (8) 3 IEEE 8th Conference on Industrial Electronics and Applications (ICIEA) 475
3 3 4 Measured open loop Model open loop Model open loop Measured open loop 3 Let the state vector x be, x = x x x 3. One of the objective of this control design is to control the system error. This error is incorporated in the controller, and to do this, one of the states of the plant is replaced by the error of the system, e.g., x [. The system error is de ned as the difference between the reference input and plant output as in the following equation: e = y r y (3) Fig. 3. Frequency plot of measured and identi ed system model for input to XPZT and output from X position sensor input to YPZT and output from Y position sensor a x = b x = c x = [ d x = [. Similarly, the following statespace model is found to be the best t fortheypzt, as illustrated in Fig. 3 where the resonant mode of the PZT is at about to 85. Hz. x y = a y x y + b y u y (9) y y = c y x y + d y u y () a y = b y = c y = [ d y = [. From Fig. 3, we can see that both the PZT plants have a 8 phase at low frequencies and zeros in the right half plane. In the modeling of the PZTs only the rst resonant modes are considered. V. CONTROLLER DESIGN A. Design of LQG Controller for Reference Tracking The purpose of this section is to present the design of an LQG controller for minimizing the steadystate error and tracking the reference sinusoidal signal. An internal reference model based optimal LQG controller is designed for both the X and Y axes of the PZTs. In this control design, two SISO identi ed statespace plant models are considered for both the X and YPZTs. Let the identi ed statespace model for the X or YPZT be: x = ax + bu () y = cx + du () where a, b, c, andd are the statespace matrices of the model plant (XPZT/YPZT), as stated in eqns. (7), (8), (9), and () u the input, y the measured output, and x the state vector with dimensions of 3 3. where y r is the reference input to the plant and assumed to satisfy the differential equation: y ˆ r = A r yˆ r (4) [ ω A r = [ yr yˆ r = y r where A r is the state matrix for the reference signal and ω the frequency of the input signal. In this design the sinusoidal reference input is modeled and the error dynamic equation is: e = y r y (5) and to account for the steadystate error an integral action is considered with the error state (e ), i.e., e I = e dt. (6) Now, the error dynamics, i.e., the converted statespace is: x e = Ax e + Bu e + Ey r (7) y e = Cx e (8) where A, B, and C are the statespace matrices of the modi ed plant, E the exogenous input matrix, u e the input of the modi ed plant, y e the measured output of that plant, and x e the state vector with dimensions of a 4 matrix, and the state vector of the modi ed error dynamics model (x e )is: e I x e = e. Hence, the entire states (metastate) of eqn. (4) and (7) satis es the following differential equation [, x x 3 x m = A m x m + B m u m (9) y m = C m x m () [ A E A m = A r IEEE 8th Conference on Industrial Electronics and Applications (ICIEA)
4 [ B B m = C m = [ C where A m, B m, and C m are the statespace matrices of the metasystem, u m the input of the metasystem, y m the measured output of the plant, and x m is the metastate vector. The x e is the substate of the x m. Since the exogenous states are generally not controllable, the appropriate performance integral is: J = [x e Qx e + u e Ru e dt () where Q is the state weighting matrix and R the control weighting, which is scalar. The weighting matrix for the meta system (9) is as follows: Q m = [ Q The performance matrix for the metasystem (9) is [: [ Mˆ Mˆ ˆM = ˆ ˆ M where ˆM is the performance matrix for the metasystem, Mˆ, Mˆ, Mˆ,and Mˆ 3 are the performance matrices corresponding to the subsystems of the metasystem. Now the gain for the metasystem is: ˆ G m = [ R B ˆ M M 3 R B ˆ M where G m is composed of the gains G e = R B Mˆ and G r = R B Mˆ. The G e is a state feedback gain for the modi ed plant and G r the feedforward gain for the reference input signal which acts against the exogenous effect. The effect of reference signal and external disturbance is known as exogenous effects. An exogenous variable is a factor that is outside of a plant model. The minimizing matrix ˆM that is resulting from minimizing gain Gˆ m must satisfy the differential equation for the performance matrices as follows: ˆM = ˆMA m + A m ˆM ˆMB m R B m ˆM + Q m. () The solution to this equation will give the gain matrix ˆ G m.by putting the value of the performance matrix ˆM in eqn. 6 and performing matrix multiplication the differential equations for the submatrices are obtained as follows: ˆ M = ˆ M A + A ˆ M ˆ M BR B ˆ M + Q ˆ M = ˆ M E + ˆ M A r + A c ˆ M A c = A BR B ˆ M (3) where A c is the closedloop dynamics matrix of the regulator subsystem and it is seen from Gˆ m that the submatrix Mˆ 3 of the performance matrix ˆM is not needed to nd the gain for the metasystem, this is a welcome fact only [. The steadystate solution for Mˆ can be found and must satisfy: = Mˆ E + Mˆ A r + A c Mˆ (4) Fig Block diagram for implementation of the proposed controller. 3 5 Open loop bode plot Closed loop bode plot 3 3 Open loop bode plot Closed loop bode plot 3 Fig. 5. Comparison of the frequency responses using an optimal LQG controller with a vibration compensator and openloop XPTS and (c) Y PTS Gxy Measured open loop Measured closed loop Gyx Measured open loop Measured closed loop 6 3 Fig. 6. Comparison of crosscoupling between the openloop and closedloop (LQG controller with the vibration compensator) input to XPZT and output from YPZT and input to YPZT and output from XPZT. where Mˆ is the solution to the algebraic Ricatti equation of the regulatory subsystem and Mˆ can be found from the above equation. Thus, we have the necessary gains to realize the control law as in [. u m = R B ˆ M x e R B ˆ M y r. (5) 3 IEEE 8th Conference on Industrial Electronics and Applications (ICIEA) 477
5 B. Design of Kalman observer Kalman observer can be used as a stateobserver and noise lter [3. The displacements of the PZTs are taken from the subnanometer resolution position sensors [4. However, the sensor adds unwanted noise and disturbances to the output displacement taken. To remove this noise we design a Kalman state observer as a noise lter. The sensor measures the output of the PZT plant not the states. As for a regulator system all states of the plant should be known, the Kalman state observer estimates the states from the measured output [. The Kalman observer dynamics is follows: ˆx = (a Lc) ˆx + bu + Ly (6) ŷ = ĉ ˆx (7) where ˆx the estimated states, ŷ the estimated state output, ĉ the identity matrix of dimension n n, andl is the observer gain which depends on the Gaussian white noise, process noise covariance, and measurement noise covariance. C. Design of a vibration compensator In this section, we discuss the design of a vibration compensator for damping the resonant mode of the PZT. However, an LQG controller has itself the damping capacity, a notch lter is introduced to achieve better damping and higher bandwidth. From the experimental frequency responses of the PZTs, we know that the rst resonance occurs at Hz for the XPZT and 85. Hz for the Y PZT. The compensator is designed to damp the rst resonant mode of the PZT with a bandwidth close to its rst resonance frequency. The general form of the resonant compensator K i is given in [5, [6 is: K i = n i= k ci (s + ζ i ω i s) s + ζ i ω i s + ω i (8) where ω i is the i th controller s center frequency which is the frequency at the i th resonant peak of the plant, k ci the controller gain, and ζ the damping factor of the corresponding mode. In fact the controller (K i ) is a secondorder bandpass lter and has high gain at the resonant frequency of the plant which is means of suppressing the vibration so that the gain suddenly drops away from the resonant frequency. Among the controller parameters, i.e., ω and ζ, ω has a greater effect on damping of the resonant mode than the damping factor (ζ). If we vary ζ by ± percent, there will be a noticeable effect on damping. But if we vary ω by ± 5 percent, the attenuation performance will be decreased signi cantly and once the value of ω is xedup the k ci has an important role on damping. VI. EXPERIMENTAL RESULTS The proposed controller is implemented on the AFM and the frequency domain performance evaluation is presented by the comparison of the measured openloop and closedloop frequency response as shown in Figs. 5 for X and Y PZT, respectively. The comparison of measured openloop and closedloop frequency response shows the signi cant damping of the resonant mode of the PZT and higher closedloop bandwidth close to the rst resonant frequency. As a result, the vibration of the PZT is reduced signi cantly. The frequency plot of the XPZT has achieved about 9 db and Y PZT is about 4 db damping. The Fig. 6 compares the comparison of the closedloop and openloop crosscoupling: input to XPZT output from YPZT and Fig. 6 compares the comparison of the closedloop and openloop crosscoupling: input to YPZT output from XPZT, from which it is seen that both the axes has achieved around db reduction of crosscoupling. The tracking performance of the proposed controller is shown in Fig. 7 at Hz (tracking of sine and cosine wave) and 3 Hz (tracking of sine and cosine wave). The result shows that the proposed control approach has obtained excellent tracking of the reference signal. The cantilever probe de ection along the Zaxis is shown in Fig. 8, where the proposed method tracks better height pro le. Spiral tracking of the proposed scheme is shown in Fig. 9. It shows that at Hz phase error is lower than at 3 Hz x 3 x 3 Reference V x Tracked V x Reference V y Tracked V y (c) x 3 x 3 Reference V x Tracked V x Reference V y Tracked V y Fig. 7. Sinusoidal tracking performance of the proposed controller Hz (sine wave), 3 Hz (sine wave), (c) Hz (cosine wave), and (d) 3 Hz (cosine wave) Fig (d) Cantilever probe de ection along the Zaxis Hz, Hz. The improved positioning is applied to the AFM for spiral scanning of a TGQ standard calibration grating with nm IEEE 8th Conference on Industrial Electronics and Applications (ICIEA)
6 Fig. 9. Spiral tracking performance of the proposed controller Hz, 3 Hz. surface height and 3 Jm pitch (period). Instantaneous radius of the spiral was maintained at 6 Jm and 5 line, i.e., diameter of the image contains 5 pixel. Constant force AFM imaging mode was setup for spiral scanning and Z deflection was recorded to construct the spiral image. Here, image scanning results have been observed by implementing the proposed controller in the X and Y axes with the help of the real time dspace system. The generated spiral images are shown in Fig. scanned at Hz, 3 Hz, 5 Hz, and Hz. The images up to 5 Hz looks undistorted and regular profile of the calibration grating. The effect of nonlinear hysteresis and creep, tracking, and vibration of the scanner are not noticeable on the images scanned at Hz, 3 Hz, and 5 Hz. But, Hz image contains effects ofvibrational and dynamics ofhigh speed scanning. At higher speed scanning this effect is severe. The tilting effect of the image can also be observed at high frequencies. One straight forward thing is that, the planes of the images are not subtracted, that is why there are some uneven illumination in the images. This is for imperfections i.e. small misalignments, dust, and additional physical properties. VII. CONCLUSION A spiral imaging technique using AFM is reported in this paper. The proposed controller is implemented on AFM for spiral image scanning and experimental results are presented, where it is shown that high speed ArM imaging can be achieved by minimizing hysteresis, creep, vibration and crosscoupling effects. However, at higher frequency scanning, the image is tilted because ofphase error due to the crosscoupling among the scanners axes and vibration effect is also noticeable. The phase error could be compensated using phase compensating method. ACKNOWLEDGEMENT The authors would like to thank very sincerely Mr. Shane Brandon who helps us in every step of our experiments. REFERENCES [ I. A. Mahmood and S. O. R. Moheimani, "Making a commercial atomic force microscope more accurate and faster using positive position feedback control," Review of Scientific Instruments, vol. 8, no. 6, pp ( )63 75(8), 9. [ M. Yves, Scanning Probe Microscope, Bellingham, 995. [3 G. Binnig, C. F. Quate, and C. Gerber, "Atomic force microscope," Physical Review Letters, vol. 56, pp , Mar Fig.. Spiral scanned images with the proposed controller Hz, (c) 3 Hz, 5 Hz, and (d) Hz. [4 D. Zhiqiang, Z. Zude, A. Wu, and C. Youping, "A linear drive system for the dynamic focus module of SLS machines," The International Journal of Advanced Manufacturing Technology, vol. 3, pp. 6, May. 7. [5 A. Bazaei, Y Yong, S. O. R. Moheirnani, and A. Sebastian, "Tracking of triangular references using signal transformation for control of a novel AFM scanner stage," IEEE Transactions on Control Systems Technology, vol., no., pp , Mar.. [6 N. Chuang, I. R. Petersen, and H. R. Pota, "Robust Hoc control in fast atomic force microscopy," in Proceedings American Control Conference, pp ,. [7 K. Leang and S. Devasia, "Feedbacklinearized inverse feedforward for creep, hysteresis, and vibration compensation in AFM piezoactuators," IEEE Transactions on Control Systems Technology, vol. 5, no. 5, pp , Sep. 7. [8 S. Devasia, E. Eleftheriou, and S. O. R. Moheimani, "A survey of control issues in nanopositioning," IEEE Transactions on Control Systems Technology, vol. 5, no. 5, pp. 883, Sep. 7. [9 B. Bhikkaji and S. O. R. Moheimani, "Integral resonant control of a piezoelectric tube actuator for fast nanoscale positioning," IEEE/ASME Transactions on Mechatronics, vol. 3, no. 5, pp , Oct. 8. [ L. Ljung, "Prediction error estimation methods," Circuits, Systems and Signal Processing, vol., issue, pp. , Jan./Feb.. [ P. Kabaila, "On outputerror methods for system identification," IEEE Transactions on Automatic Control, vol. 8, no., pp. 3, Jan [ B. Friedland, Control system design, An introduction to state space methods. New York: McGrawHill, 986. [3 K. Chen, Y. Zhang, B. Lazzerini, and R. Yang, "Stochastic noise tolerance: Enhanced full state observer vs. kalman filter from video tracking perspective," Journal of Electronics (China), vol. 7, no. 4, pp , Jul.. [4 A. E. Holman, P. M. L. O. Scholte, W. C. Heerens, and F. Tuinstra, "Analysis of piezo actuators in translation constructions," Review of SCientific Instruments, vol. 66, issue 5, pp , May 995. [5 I. R. Petersen and A. Lanzon, "Feedback control ofnegativeimaginary systems," IEEE control system magazine on flexible structure, vol. 3, no. 5, pp. 547, Oct.. [6 H. R. Pota, S. O. R. Moheimani, and M. Smith, "Resonant controllers for smart structures," Smart Materials and Structures, vol., no., pp. 8, Feb.. 3 IEEE 8th Conference on Industrial Electronics and Applications (ICIEA) 479
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