An improved tracking-differentiator filter based on Taylor's formula

Feng, Jinping; Wang, Wei; Chen, Yu

doi:10.1016/j.ijleo.2017.12.198

Cited by 13 publications

(9 citation statements)

References 13 publications

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“…The basic filter method can be carried out by the following steps [5]: Firstly, we should deal with the input signal ( ) v t with n-order cascade of DNTD. Secondly, we get the output signals 1 ( ) i x t (the tracking signals) and i -order differential signals 2 ( ) i x t from DNTD at 1 t , where 1 ( ) i x t is the filter and approximation of ( 1) , 1,2, ,…”

Section: The Improved Tracking-differentiator Filters [5 6]mentioning

confidence: 99%

“…But there exist some limitations in the wavelet method, such as lack of shift invariance, poor direction selectivity [3][4]. In this paper, we intend to deal with the denoising problem by using some of the improved tracking-differentiator filters (ITDFs), which are introduced by Feng et al [5], simply referred to as ITDF1, and another ITDF proposed by Feng et al [6], simply signed as ITDF2.…”

Section: Introductionmentioning

confidence: 99%

“…From the simulation results from the early researchers, there are phase lags in the outputs of TD. Many advanced algorithms are proposed, such as TD which using an ingenious technique based on Taylor's expansion [5,6,13], the time lagging phenomenon is reduced effectively. In this paper, we mainly consider frequency interference filtering technique introduced by references [5,6], and we also compare their filtering performance.…”

Section: Introductionmentioning

confidence: 99%

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The Application of Improved Tracking-differentiator Filter in ECG Data

Feng¹,

Li²,

Wang³

et al. 2018

dtcse

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Abstract. Denoising is very important in signal processing. Electrocardiogram (ECG) data always contains 50 or 60 Hz power line interferences (PLI), PLI may affect the detection of P wave, QRS complex and T wave. So the pre-processing of ECG data is necessary. In order to remove PLI, in this paper, we use two improved tracking-differentiator filters (ITDFs), which are signed ITDF1 and ITDF2 respectively. The simulation results for ECG signals obtained from MIT-BIH database indicate that ITDFs are good methods for filtering noises, and ITDF2 does better than ITDF1.

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Section: The Improved Tracking-differentiator Filters [5 6]mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Application of Improved Tracking-differentiator Filter in ECG Data

Feng¹,

Li²,

Wang³

et al. 2018

dtcse

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“…TD based on Taylor's formula is clarified and analyzed in [17], aiming at tackling the phase-delay issue from TD.…”

Section: Introductionmentioning

confidence: 99%

A Novel Active Disturbance Rejection Control with a Super‐Twisting Observer for the Rocket Launcher Servo System

Shi

Hou

et al. 2021

Shock and Vibration

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In this paper, a novel active disturbance rejection control (NADRC) with a super-twisting extended state observer (SESO) is utilized in the rocket launcher servo system. The main arguments in the shipborne rocket launcher system are control accuracy and antidisturbance ability, which are closely related to phase delay and bandwidth. Firstly, we use Taylor’s formula approach to compensate the phase delay in traditional tracking differentiator (TD). Secondly, we design the parallel structured SESO to improve the observation bandwidth, so that it can estimate states with desired accuracy in NADRC. Finally, sinusoidal simulation results show Taylor’s formula-based TD can suppress noise and compensate phase delays effectively. In comparison with traditional ADRC, the proposed NADRC is shown to have better tracking performance and stronger robustness. Semiphysical experiments are conducted to prove the feasibility of NADRC.

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“…e research studies of the convergence, rapidity improvement and its high-order form application are carried out in [10][11][12][13]. Cataloging former references, Jinping Feng proposes a Taylor's formula-based phase compensation method to decrease phase lags [14]. e disturbance estimator is the critical part of ADRC, which is used to compensate the difference between the real model and the nominal model caused by external disturbances and changes of model parameters.…”

Section: Introductionmentioning

confidence: 99%

Improved Finite Control Set Optimal Control for PMSM in Rocket Launcher Servo System

Shi

Hou

et al. 2020

Shock and Vibration

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Permanent magnet synchronous motors (PMSMs) have been widely applied in the shipborne rocket launcher systems due to their high torque density and high efficiency. However, since there are many external disturbances from the shipborne rocket launcher, the tracking performance under random noises needs to be improved. In this paper, an improved finite control set optimal control (IFCSOC) based on a super-twisting extended state observer (SESO) is investigated for position tracking control of PMSMs. The SESO can improve the anti-interference ability of the proposed controller. Moreover, in order to improve tracking accuracy, Taylor’s formula is used to solve the phase-lag problem of nonlinear tracking differentiator in IFCSOC. Simulation shows that compared with conventional FCSOC, IFCSOC exhibits better robustness under random disturbances. Furthermore, the semiphysical experiment is conducted to verify the proposed IFCSOC strategy.

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An improved tracking-differentiator filter based on Taylor's formula

Cited by 13 publications

References 13 publications

The Application of Improved Tracking-differentiator Filter in ECG Data

The Application of Improved Tracking-differentiator Filter in ECG Data

A Novel Active Disturbance Rejection Control with a Super‐Twisting Observer for the Rocket Launcher Servo System

Improved Finite Control Set Optimal Control for PMSM in Rocket Launcher Servo System

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