Identification of Hammerstein-Weiner System for Normal and Shading Operation of PhotovoltaicSystem

Hussain, Mohd Najib Mohd; Omar, Ahmad Maliki; Saidin, Pais; Samat, Ahmad Asri Abd; Hussain, Z.

doi:10.7763/ijmlc.2012.v2.122

Cited by 5 publications

(2 citation statements)

References 12 publications

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“…In this case, g(.) is a function of a nonlinear model that represents system nonlinearities [45]. The function g(.)…”

Section: Nonlinear Black-box Model Of Magnetorheological Fluidmentioning

confidence: 99%

“…For nonlinear estimators, the model order is defined as the number of past outputs, past inputs, and input delays used for predicting the output at a given time. Typically, the model orders are chosen by trial and error [45]. However, we utilized the Akaike information criterion (AIC) because it provides a preliminary order set [46,47].…”

Section: Nonlinear Black-box Model Of Magnetorheological Fluidmentioning

confidence: 99%

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Application of a Nonlinear Hammerstein-Wiener Estimator in the Development and Control of a Magnetorheological Fluid Haptic Device for Robotic Bone Biopsy

et al. 2018

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A force generator module (FGM) based on magnetorheological fluid (MRF) was developed to provide force-feedback information for applications in tele-robotic bone biopsy procedures. The FGM is capable of rapidly re-producing a wide range of forces that are common in bone biopsy applications. As a result of the nonlinear nature of MRF, developing robust controllers for these mechanisms can be challenging. In this paper, we present a case study motivated by robotic bone biopsy. We use a non-linear Hammerstein-Wiener (H-W) estimator to address this challenge. The case is presented through three studies. First, an experiment to develop design constraints is presented and describes biopsy force measurements for various animal tissues. Required output forces were found to range between <1 N and <50 N. A second study outlines the design of the FGM and presents the experimental characterization of the hysteretic behavior of the MRF. This data is then used as estimators and validators to develop the nonlinear Hammerstein-Wiener (H-W) model of the MRF. Validation experiments found that the H-W model is capable of predicting the behavior of the MRF device with 95% accuracy and can eliminate hysteresis in a closed-loop control system. The third study demonstrates the FGM used in a 1-DOF haptic controller in a simulated robotic bone-biopsy. The H-W control tracked the input signal while compensating for magnetic hysteresis to achieve optimal performance. In conclusion, the MRF-based device can be used in surgical robotic operations that require a high range of force measurements.

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“…In this case, g(.) is a function of a nonlinear model that represents system nonlinearities [45]. The function g(.)…”

Section: Nonlinear Black-box Model Of Magnetorheological Fluidmentioning

confidence: 99%

Section: Nonlinear Black-box Model Of Magnetorheological Fluidmentioning

confidence: 99%