Cantilevers fabricated by means of micromachining techniques are usually used for atomic force microscopy. In this paper, the spring constant of an atomic force microscope (AFM) cantilever is determined by using a large-scale cantilever. Since the spring constant of the large-scale cantilever is calibrated accurately, the spring constant of the AFM cantilever is determined precisely by measuring the deflections of both cantilevers simultaneously using heterodyne interferometry. The slope of the force curve gives the spring constant of the AFM cantilever. It is not necessary to measure the dimensions of the AFM cantilever in the proposed method. Although this method is simple, the spring constant of the AFM cantilever is obtained accurately.

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AbsZruct-This paper presents a nonlinear compensator using neural networks for trajectory control of robotic manipulators. The adaptive capability of the neural network controller to compensate unstructured uncertainties is clarified. A model learning scheme is also proposed in this paper. The learning procedure is effective and efficient in learning the manipulator dynamics, and error convergence with untrained trajectories is fast.

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