| Nonlinear control techniques for an atomic force microscope system |
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| 引用本文： | Yongchun FANG,Matthew FEEMSTER,Darren DAWSON,Nader M.JALILI. Nonlinear control techniques for an atomic force microscope system[J]. 控制理论与应用(英文版), 2005, 3(1): 85-92. DOI: 10.1007/s11768-005-0066-6 |
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| 作者姓名： | Yongchun FANG Matthew FEEMSTER Darren DAWSON Nader M.JALILI |
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| 作者单位： | [1]InstituteofRoboticsandAutomancInformationSystem,NankaiUniversity,Tianjin300071,China [2]WeaponsandSystemEngineeringDeparment,Annapolis,Maryland,USA,21402-5025 [3]ClemsonUniversity,Clemson,SC29634-0915 |
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| 摘 要： | Two nonlinear control techniques are proposed for an atomic force microscope system. Initially, a learning-based control algorithm is developed for the microcantilever-sample system that achieves asymptotic cantilever tip tracking for periodic trajectories. Specifically, the control approach utilizes a learning-based feedforward term to compensate for periodic dynamics and high-gain terms to account for non-periodic dynamics. An adaptive control algorithm is then developed to achieve asymptotic cantilever tip tracking for bounded tip trajectories despite uncertainty throughout the system parameters. Simulation results are provided to illttstrate the efficacy and performance of the control strategies.
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| 关 键 词： | 非线性控制 原子力显微镜 自适应控制 稳定性 |
| 收稿时间： | 2004-12-18 |
| 修稿时间： | 2005-03-10 |
Nonlinear control techniques for an atomic force |
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| Yongchun FANG,Matthew FEEMSTER,Darren DAWSON,Nader M.JALILI. Nonlinear control techniques for an atomic force[J]. Journal of Control Theory and Applications, 2005, 3(1): 85-92. DOI: 10.1007/s11768-005-0066-6 |
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| Authors: | Yongchun FANG Matthew FEEMSTER Darren DAWSON Nader M.JALILI |
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| Affiliation: | Institute of Robotics and Automatic Information System ,Nankai University , Tianjin 300071 , China ; Weapons and System Engineering Department ,Annapolis ,Maryland ,USA ,21402 - 5025; Clemson University , Clemson ,SC 29634 - 0915: |
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| Abstract: | Two nonlinear control techniques are proposed for an atomic force microscope system. Initially ,a learning- based control algorithm is developed for the microcantilever-sample system that achieves asymptotic cantilever tip tracking for periodic trajectories. Specifically ,the control approach utilizes a learning- based feedforward term to compensate for periodic dynamics and high- gain terms to account for non-periodic dynamics. An adaptive control algorithm is then developed to achieve asymptotic cantilever tip tracking for bounded tip trajectories despite uncertainty throughout the system parameters. Simulation results are provided to illustrate the efficacy and performance of the control strategies. |
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| Keywords: | Atomic force microscope Adaptive control Learning control Lyapunov- based stability analysis |
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