Encoder position feedback based indirect integral method for motor parameter identification subject to asymmetric friction

Li, Yang Rui; Peng, Chao-Chung

doi:10.1016/j.ijnonlinmec.2023.104386

Cited by 7 publications

(7 citation statements)

References 34 publications

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“…Moreover, the filter-based approach offers a more efficient approach to mitigate the influence of quantization noise. Experimental results presented in [24] affirm that filter-based SPI surpasses differentiation-based SPI in terms of parameter estimation accuracy. However, a simple stable motor system was presented [24].…”

Section: Introductionsupporting

confidence: 53%

“…Experimental results presented in [24] affirm that filter-based SPI surpasses differentiation-based SPI in terms of parameter estimation accuracy. However, a simple stable motor system was presented [24]. To exploration the potential capability of the filter-based method, this work applied it to highly nonlinear unstable wheel-driven pendulum system.…”

Section: Introductionsupporting

confidence: 53%

“…Similar to ( 16) and (24), and considering the regression model (39), the LS equation can now be modified by the filtered normal equation…”

Section: Filtering-based Regression Modelmentioning

confidence: 99%

“…We have transformed (41) under the assumption of zero-order hold to a discrete equation for numerical iteration. Further details regarding the numerical integration can be found in the Appendix A of reference [24]. Moreover, for the computation of the optimal solution using the least-squares method, a significant amount of memory may be required to allocate measurement matrices Φ 2 f .…”

Section: Filtering-based Regression Modelmentioning

confidence: 99%

“…Therefore, the command trajectories should be properly designed. Recent research [24] has emphasized the significance of coarse encoder quantization errors in angular measurements, which introduce noise affecting the estimation of velocity and acceleration. Consequently, the article addresses this issue by applying the filter-based method.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Application of an Output Filtering Method for an Unstable Wheel-Driven Pendulum System Parameter Identification

Peng,

Cheng,

Tsai

2023

Electronics

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This research aims to apply an output filtering method to conduct the system parameter identification of an unstable wheel-driven pendulum system. First, the nonlinear dynamic model of the system is established by utilizing the Lagrangian dynamic theorem. Next, the Least-Square (LS) is introduced for system parameter identification formulation. Nevertheless, considering the real scenario, the wheel displacement is acquired from encoders subject to quantization errors. The pitch angle of the pendulum cart is also accompanied by Gaussian noise. Therefore, using numerical differentiation for angular acceleration in the LS estimations directly would induce incorrect state information seriously. To address this practical issue, an output filtering method is considered. The developed parameter identification algorithm could attenuate the influence of the quantization effect as well as noisy data and thus obtain much more accurate parameter identification results. Comparative simulation reveals that the output filtering method has a superior parameter estimation performance than the direct numerical difference method.

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Section: Introductionsupporting

confidence: 53%

Section: Introductionsupporting

confidence: 53%

“…Similar to ( 16) and (24), and considering the regression model (39), the LS equation can now be modified by the filtered normal equation…”

Section: Filtering-based Regression Modelmentioning

confidence: 99%

Section: Filtering-based Regression Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%