An improved self-adaptive tracking differentiator

Qiao, Guohui; Sun, Minmin; Zhang, Rong; Zong, Guanghua; Li, Shouzhong

doi:10.1109/icinfa.2009.5205060

Cited by 4 publications

(3 citation statements)

References 1 publication

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“…To increase the tracking differentiator's performance, it's required to remove the tracer's complex solution, particularly the solution on the imaginary axis, and to meet the condition that the tracking differentiator converge rapidly [29], [30]. As illustrated in [31], a better tracking differentiator can be obtained in the following form:-…”

Section: C-mtd-adrcmentioning

confidence: 99%

Modified Tracking Differentiator for Enhancing the Performance of Exoskeleton Knee System Based on Active Disturbance Rejection Control

2023

IJCCCE

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Exoskeleton robots help users with mechanical forces by recognizing their intentions, and they require a lot of energy efficiency, a lot of load capacity, and a good fit. A basic one degree of freedom (DOF) construction was devised in this work, which was mostly used in the knees of exoskeleton robots. The exoskeleton is a small robotic device used for knee injury training. It is a nonlinear mathematical model with many mechanical factors that might vary and produce uncertainty, as well as external disturbances that can be utilized to monitor control. The transitioning process is frequently organized using tracking differentiator TD to resolve the conflict between system speed and overshoot. An active disturbance rejection control (ADRC) with a modified tracking differentiator is described to tackle these challenges, enhance control accuracy, and reduce settling time for exoskeleton modified trajectory differentiator (MTD).Simulation tests showed that (MTD) reduced the tracking error by 36%, when compared with the improved TD1 and 37.5% for Hans TD2 at uncertainty case . Despite the presence of several model uncertainties, the suggested training knee exoskeleton robot system using the MTD-ADRC was able to achieve the necessary target value. Control design and analysis can be done with Matlab and Simulink. Index Terms— Exoskeleton system, ADRC, MTD, nonlinear calculus, robustness

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Section: C-mtd-adrcmentioning

confidence: 99%

Modified Tracking Differentiator for Enhancing the Performance of Exoskeleton Knee System Based on Active Disturbance Rejection Control

2023

IJCCCE

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“…The centroid of the combined shape is related to the centroid coordinates and area of sub-shapes. The centroid coordinates G j and area S j (x) is obtained from Equations (16) and (17). The centroid of the combined shape is obtained from Equation (18).…”

Section: Defining Inference and Defuzzificationmentioning

confidence: 99%

“…Due to above issues, some tracking differentiators with adaptive properties were proposed. A self-adaptive second-order tracking differentiator which can automatically adjust its tracking rate is proposed by [17], where an approximate sigmoid function is designed as the rate switching function. However, due to the change of switching function, the local signal quality cannot be guaranteed.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Self-tuning Tracking Differentiator for Motion Measurement Sensors and Application in Wide-Bandwidth High-accuracy Servo Control

Gao

Tian

Wang

2020

Sensors

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Sensor differential signals are widely used in many systems. The tracking differentiator (TD) is an effective method to obtain signal differentials. Differential calculation is noise-sensitive. There is the characteristics of low-pass filter (LPF) in the TD to suppress the noise, but phase lag is introduced. For LPF, fixed filtering parameters cannot achieve both noise suppression and phase compensation lag compensation. We propose a fuzzy self-tuning tracking differentiator (FSTD) capable of adaptively adjusting parameters, which uses the frequency information of the signal to achieve a trade-off between the phase lag and noise suppression capabilities. Based on the frequency information, the parameters of TD are self-tuning by a fuzzy method, which makes self-tuning designs more flexible. Simulations and experiments using motion measurement sensors show that the proposed method has good filtering performance for low-frequency signals and improves tracking ability for high-frequency signals compared to fixed-parameter differentiator.

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Double-loop control in air–ground cooperation for a switched-trajectory quadrotor under gust winds

Cui,

Liang,

Yang

et al. 2024

Transactions of the Institute of Measurement and Control

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In this paper, a double-loop tracking control strategy with finite-time convergence is investigated for a switched-trajectory quadrotor subjected to gust winds in air–ground cooperation. To handle the complexity of switched-trajectory tracking, an adaptive tracking differentiator is presented in an outer loop to arrange transition processes. Fast integral terminal sliding mode control is also used in the outer loop to improve convergence speed and tracking accuracy. The gust winds are estimated and compensated by a nonlinear extended state observer and a nonlinear controller with finite-time convergence in an inner loop, respectively. Convergency analyses are presented with the double-loop tracking control strategy for the switched-trajectory quadrotor. Comparison experiments with existing studies show superior performances of the proposed control method for the quadrotor in air–ground cooperation under gust winds.

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An improved self-adaptive tracking differentiator

Cited by 4 publications

References 1 publication

Modified Tracking Differentiator for Enhancing the Performance of Exoskeleton Knee System Based on Active Disturbance Rejection Control

Modified Tracking Differentiator for Enhancing the Performance of Exoskeleton Knee System Based on Active Disturbance Rejection Control

Fuzzy Self-tuning Tracking Differentiator for Motion Measurement Sensors and Application in Wide-Bandwidth High-accuracy Servo Control

Double-loop control in air–ground cooperation for a switched-trajectory quadrotor under gust winds

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