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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.

One of the most important tasks in industries is considered to be the condition monitoring of induction motors. However, most of the traditional methods employed for this purpose suffer from certain limitations in accomplishing this task. A successful implementation of condition monitoring requires the development of a simple but reliable detector of various faults. This paper investigates the performance of Discrete Wavelet Transform and Radial Basis Function based Neural Network for incipient stator fault diagnosis in induction motors. Wavelet analysis helps in the extraction of important features from the faulty signal and neural network classifies the fault type depending on the nature of fault. A mean absolute percentage error of 1.4236% between the actual values and the predicted values by the neural network show the effectiveness of the proposed approach.

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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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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This paper proposes a novel and robust Sliding Mode Control (SMC) technique for hysteresis linearization of a stack actuated piezoelectric micro/nano positioner. This work documents a classical second order Dahl model to capture the effects of rate dependent hysteresis. An advantage of this model is its easier implementation and better depiction of asymmetric hysteresis loops than a same order Bouc-Wen model. In existing works on SMC with piezoelectric actuators, Dahl model has received scant attention. In contrast, this work explores second order Dahl model as a candidate for SMC implementation. The proposed approach is unique in the sense that it does not need a separate hysteresis observer. The stability of the controller is verified by Lyapunov stability analysis and zero steady state error is theoretically proved. SMC strategy accounts for the uncertain hysteresis as well as unanticipated fluctuations in the input. Simulation results establish the trajectory tracking robustness and effectiveness of the proposed control technique.