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Self-Tuning Neuro-PID Controller for Piezoelectric Actuator

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The purpose of this study was to design a tracking controller for micro-piezoelectric motion platform applications. The hysteresis effect is an inherent element of piezoelectric actuated platforms often leading to nonlinearity in the behavior of the system. We constructed a Prandtl-Ishlinskii model to describe the hysteresis behavior of piezoelectric actuators, and derived the weights of the model using the LMS (Least-Mean-Square) algorithm. Based on the Prandtl-Ishlinskii model, we developed a feed-forward controller to compensate for hysteresis nonlinearity, and implemented a self-tuning neuro-PID controller to suppress tracking error due to modeling inaccuracy. The efficacy of this approach was numerically and experimentally verified, demonstrating the performance and applicability of the proposed designs under a variety of operating conditions.
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Document Type: Research Article

Publication date: 2012-07-01

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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