This paper addresses the problem of hysteresis and presents a new control scheme for hysteresis compensation of piezo-electrically actuated micro-nano manipulators. The technology employs an Inverse Dahl model based feed-forward mechanism in combination with a feedback control algorithm along with simultaneous voltage and displacement dither strategy. The actuator performance is seen to improve as a function of injected noise level into the plant -a phenomenon known as dithering. The notion of stochastic resonance for nano positioning is studied to determine the optimal dither level for efficient plant performance. The efficacy of the proposed control scheme has been confirmed through rigorous simulations in terms of two specific tests -a) tracking error test and b) hysteresis curve area test. Results show an enhanced positioning precision of the manipulator with the proposed dither control than without it. Owing to its algorithmic simplicity, the proposed control genre can be extended to the parlance of other nano-scale applications.

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Hysteresis is a major impediment in achieving precise position tracking through piezo actuated micro nano manipulator. In our study it has been shown that the effect of hysteresis can be mitigated by the proper application of a suitably selected dither sequence. The objective of the paper is to compare the various types of dither viz, Sinusoidal, Gaussian, Rayleigh and Rician, as to which gives the optimal system performance in terms of two tests-tracking error and area under the hysteresis curve. This paper starts with the analysis of a piezoelectric actuator based on the Dahl model. An inverse Dahl model based feed-forward mechanism in conjunction with a feedback control is used for the study of the actuator's performance. Dither injection is applied at three different places in the system and accordingly three different schemes namely displacement dither, voltage dither and combined dither have been developed and compared. Based on the simulations, the best type of dither and its corresponding intensity for a given place of dither injection has been established. Results ascertain dither based control as a simple and an efficient algorithm capable of providing very accurate micro-nano positioning.

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The Discrete Wavelet Transform has been widely used as a mathematical tool for vibration signal analyses in Condition Monitoring Systems for the past couple of decades. But like any transformation, an effective analysis is largely dependent on the noise characteristics associated with the acquired signal, which inevitably degrades its performance. A quantitative evaluation of the impact of both filtering regimen and wavelet family on vibration analysis is presented in this paper. The classification error associated with the training of a Radial Basis Function (RBF) Neural Network is used to quantify the performance of different filtering routines and wavelet families. Faults associated with mechanical rubbing have been considered in the present research and the results indicate that a generous performance enhancement, reaching as high as 28 percent is possible when an effective filter-wavelet combination is used leading to a more reliable detection of mechanical rubbing faults in rotating machinery.

Piezoelectric-stack actuated platforms are very popular in the parlance of nanopositioning with myriad applications like micro/nanofactory, atomic force microscopy, scanning probe microscopy, wafer design, biological cell manipulation, and so forth. Motivated by the necessity to improve trajectory tracking in such applications, this paper addresses the problem of rate dependent hysteretic nonlinearity in piezoelectric actuators (PEA). The classical second order Dahl model for hysteresis encapsulation is introduced first, followed by the identification of parameters through particle swarm optimization. A novel inversion based feedforward mechanism in combination with a feedback compensator is proposed to achieve high-precision tracking wherein the paradoxical concept of noise as a performance enhancer is introduced in the realm of PZAs. Having observed that dither induced stochastic resonance in the presence of periodic forcing reduces tracking error, dither capability is further explored in conjunction with a novel output harmonics based adaptive control scheme. The proposed adaptive controller is then augmented with an internal model control based approach to impart robustness against parametric variations and external disturbances. The proposed control law has been employed to track multifrequency signals with consistent compensation of rate dependent hysteresis of the PEA. The results indicate a greatly improved positioning accuracy along with considerable robustness achieved with the proposed integrated approach even for dual axis tracking applications.

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