An RST Control Design Based on Interval Technique for Piezomicropositoning Systems with Rate-Dependent Hysteresis Nonlinearities

Rakotondrabe, Micky; Janaideh, Mohammad Al

doi:10.1109/cdc40024.2019.9030232

Cited by 4 publications

(1 citation statement)

References 19 publications

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“…A polynomial RST digital controller was designed in parallel with an inverse LSSVM hysteresis model. The RST controller has been successfully applied in many applications [29][30][31][32]; it uses polynomial functions R and S to create robust feedback control components and the polynomial T in the feedforward path to improve tracking performance. The most interesting aspect of this paper was the ability to reduce tracking error by imposing certain constraints on the shape of the closed-loop sensitivity functions.…”

Section: Introductionmentioning

confidence: 99%

Robust Tracking Control of Piezo-Actuated Nanopositioning Stage Using Improved Inverse LSSVM Hysteresis Model and RST Controller

et al. 2022

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Nanopositioning technology is widely used in high-resolution applications. It often uses piezoelectric actuators due to their superior characteristics. However, piezoelectric actuators exhibit a hysteresis phenomenon that limits their positioning accuracy. To compensate for the hysteresis effect, developing an accurate hysteresis model of piezoelectric actuators is very important. This task is challenging, requiring some considerations of the multivalued mapping of hysteresis loops and the generalization capabilities of the model. This challenge can be dealt with by developing a machine learning-based model, whose inverse model can be used to efficiently design an accurate feedforward controller for hysteresis compensation. However, this approach depends on model accuracy and the type of data used to train the model. Thus, accurate prediction of the hysteresis behavior may not be guaranteed in the presence of disturbances. In this paper, a machine learning-based model is used to design a hysteresis compensator and then combined with a robust feedback controller to enhance the robustness of a nanopositioning control system. The proposed model is based on hysteresis operators, the least square support vector machine (LSSVM) method, and particle swarm optimization (PSO) algorithm. The inverse model is used to design the feedforward controller, and the RST controller is employed to develop feedback control. Our main contribution is the introduction of a hybrid controller capable of compensating for the hysteresis effect, and at the same time, eliminating remaining modeling errors and rejecting disturbances. The performance of the proposed approach is evaluated through MATLAB simulation, as well as through real-time experiments. The experimental results of our approach demonstrate superior tracking performance compared with the PID-LSSVM controller.

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Section: Introductionmentioning

confidence: 99%

Robust Tracking Control of Piezo-Actuated Nanopositioning Stage Using Improved Inverse LSSVM Hysteresis Model and RST Controller

et al. 2022

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Piezo-actuated smart mechatronic systems: Nonlinear modeling, identification, and control

Yuan,

Zhou,

Zhang

et al. 2024

Mechanical Systems and Signal Processing

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Output-Feedback Control of a Piezomicropositioning Tube Actuator with Uncertain Nonlinearities

Janaideh

Boker

Rakotondrabe

2020

2020 59th IEEE Conference on Decision and Control (CDC)

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An RST Control Design Based on Interval Technique for Piezomicropositoning Systems with Rate-Dependent Hysteresis Nonlinearities

Abstract: An RST control design based on interval technique for piezomicropositoning systems with rate-dependent hysteresis nonlinearities.

Cited by 4 publications

References 19 publications

Robust Tracking Control of Piezo-Actuated Nanopositioning Stage Using Improved Inverse LSSVM Hysteresis Model and RST Controller

Robust Tracking Control of Piezo-Actuated Nanopositioning Stage Using Improved Inverse LSSVM Hysteresis Model and RST Controller

Piezo-actuated smart mechatronic systems: Nonlinear modeling, identification, and control

Output-Feedback Control of a Piezomicropositioning Tube Actuator with Uncertain Nonlinearities

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