Research on hysteresis compensation control of GMM

Meng, Aihua; Yang, Jianfeng; Li, Mingfan; Jiang, Sunquan

doi:10.1007/s11071-015-2316-6

Cited by 17 publications

(8 citation statements)

References 9 publications

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“…Step(M-step) [24]. Because the goal is to solve the distribution parameters of GMM, and the implicit and unobserved data is unknown, the EM algorithm of E-step first guess the implicit data of the model to get the expected value and the Gaussian distribution [25]. Then maximum likelihood estimation is performed for complete data and the parameters of GMM are solved, namely M-step.…”

Section: A Principle Of Gmm-em and Anomaly Detectionmentioning

confidence: 99%

Research on a Pattern Recognition Method of Cyclic GMM-FCM Based on Joint Time-Domain Features

Wang

Zhao³

et al. 2021

IEEE Access

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Section: A Principle Of Gmm-em and Anomaly Detectionmentioning

confidence: 99%

Research on a Pattern Recognition Method of Cyclic GMM-FCM Based on Joint Time-Domain Features

Wang

Zhao³

et al. 2021

IEEE Access

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“…The speed loop outputs a set position to the NN feed-forward module. The NN is responsible for transmitting a target position to a target current, then the current loop exports a PWM duty cycle [19]. The initial weight coefficient of the NN inverse model is obtained from offline training.…”

Section: Neural Network Based Inverse Model Controlmentioning

confidence: 99%

Study of Nonlinear Characteristics and Model Based Control for Proportional Electromagnet

Song

Zhao

Yao

et al. 2018

Mathematical Problems in Engineering

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The nonlinear characteristics of proportional electromagnet caused by hysteresis bring great difficulties on its accurate position tracking control by current. In order to enhance the practicability and reliability of long stroke electromagnet in case of position sensor fault and improve the position tracking performance during current closed-loop control, experimental investigations on the electromagnet actuator hysteresis characteristics of diesel engine governor are carried out to analyze the system dynamic features and the effects of hysteresis on actuator position tracking performance. It is clear that hysteresis can significantly hinder the accurate position control of the electromagnet actuator. Consequently, the fuel injection will be delayed, which will lead to hysteresis of engine speed control as well as deterioration of engine performance. In this paper, the hysteresis phenomenon of an actuator and its influence on control performance of engine are investigated. The model of proportional electromagnet actuator (PEA) is established and the hysteresis principle is analyzed. Then the inverse model control strategy based on neural network (NN) is proposed to linearize the transfer behavior of electromagnet and compensate for the magnet hysteresis. Rapid control prototyping (RCP) experiment based on MicroAutoBox is further implemented to validate the real-time performance of the proposed control strategy in D6114 diesel engine. The results show that the speed fluctuation (SF) under steady-state conditions (especially under idle speed condition) and the recovery time as well as the overshoot under transient conditions are significantly improved. This makes it possible to develop redundant electromagnet driving control strategy.

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“…But the output characteristics of GMA are affected by many nonlinear factors especially in complex dynamic environment such as high frequency, multi-frequencies, heavy load and so on, which can lead to poor tracking precision and even nonlinear instability [4], [5]. In order to reduce the effect of material hysteresis nonlinearity, the different control algorithms based on the inverse mode are studied and achieve good tracking results [6]- [8] on the low frequency or quasi-static situations. With the development of intelligent control strategies, adaptive control [9], neural network control [10], optimal control [11], [12] are studied to improve the tracking characteristics by constantly adjusting control parameters.…”

Section: Introductionmentioning

confidence: 99%

Research on Control Strategy in Giant Magnetostrictive Actuator Based on Lyapunov Stability

Gao

Liu

2019

IEEE Access

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The output characteristics of giant magnetostrictive actuator (GMA) are affected by many nonlinear factors, such as hysteresis, load, driving frequency and so on, which would lead to lower positioning precision, poorer repeatability, and even fall into nonlinear instability especially in complex dynamic environment. First, the accurate dynamic mathematical model for GMA is established after analyzing its working principle. Then, the inverse model feed-forward compensation fuzzy PD control based on Lyapunov stability is put forward and applied into the GMA control system. The experiment results indicate that Lyapunov direct method that is integrated into inverse model feed-forward compensation fuzzy PD controller can effectively improve the dynamic output features especially in the complex dynamic environment, reduce the root mean square error from 1.275 to 0.332 and maximum error rate from 26.89% to 7.12%, which not only greatly improve performance and expand the application domain of GMA, but also have very important theoretical significance and high application value in modeling and control approach for some hysteresis systems.

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Research on hysteresis compensation control of GMM

Cited by 17 publications

References 9 publications

Research on a Pattern Recognition Method of Cyclic GMM-FCM Based on Joint Time-Domain Features

Research on a Pattern Recognition Method of Cyclic GMM-FCM Based on Joint Time-Domain Features

Study of Nonlinear Characteristics and Model Based Control for Proportional Electromagnet

Research on Control Strategy in Giant Magnetostrictive Actuator Based on Lyapunov Stability

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