Self-adaptive interval type-2 neural fuzzy network control for PMLSM drives

Chen, Chaio-Shiung; Lin, Wei‐Chieh

doi:10.1016/j.eswa.2011.05.014

Cited by 42 publications

(7 citation statements)

References 34 publications

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“…In [23], for a PMSM drive with dead time, an adaptive self-tuning speed control is posed. In [24], due to achieve the high-precision motion control for PMSLM drives, a self-adaptive interval type-2 neural fuzzy network control system is presented. Whereas in [25], a method is mentioned, which can realize the speed control of PMSLM by using two degrees of freedom PI controller based on instant learning method.…”

Section: Adaptive Controlmentioning

confidence: 99%

A Speed Disturbance Control Method Based on Sliding Mode Control of Permanent Magnet Synchronous Linear Motor

Jiang

Wang

et al. 2019

IEEE Access

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Permanent magnet synchronous linear motor (PMSLM) is a linear motion device, which has the characteristics of simple structure, low loss, high precision, repeatability, large stroke, and simple maintenance. Simultaneously, due to its feature of non-linearity, time-varying, strong coupling, and external load uncertainty, a speed disturbance control method base on sliding mode control of PMSLM is proposed in this paper. The method of sliding mode control uses the power function to smooth the processing. It replaces the symbolic function based on the exponential approach method; therefore, the buffeting of the conventional sliding mode can be well suppressed by this method. When considering different disturbances, the simulation proves that the sliding mode control system can overcome the influence of system parameter changes and external disturbances. Therefore, the control of the PMSLM can be achieved. Meanwhile, the simulation results show that the proposed new sliding mode approach rate can better suppress chattering compared with the traditional approach rate. Additionally, the stability of the system and anti-interference is improved.

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Section: Adaptive Controlmentioning

confidence: 99%

A Speed Disturbance Control Method Based on Sliding Mode Control of Permanent Magnet Synchronous Linear Motor

Jiang

Wang

et al. 2019

IEEE Access

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“…Therefore, most T2FNN research is only concerned with interval type-2 fuzzy systems. The complete IT2FNN theory can be found in [11], [12]. Fig.…”

Section: Problem Statement and Solutionmentioning

confidence: 99%

“…Nowadays; fuzzy neural network controllers that can combine the advantages of fuzzy logic controllers and neural networks have been widely applied in many real word applications [10][11][12][13]. One way to build IT2FNN is to fuzzify a conventional neural network.…”

Section: Problem Statement and Solutionmentioning

confidence: 99%

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A Methodology to Improve Cash Demand Forecasting for ATM Network

Darwish¹

2013

IJCEE

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Abstract-Developing cash demand forecasting model for ATM network is a challenging task as the chronological cash demand for every ATM fluctuates with time and often superimposed with non-stationary behavior of users. In order to improve the forecasting precision of ATM cash demand, an Interval Type-2 Fuzzy Neural Network (IT2FNN) has been utilized in this paper. The antecedent parts in each rule of the IT2FNN are interval type-2 fuzzy sets in view of conditions regarding time, location, cash residual and other factors that could lead to consider cash upload able to keep cash at the right levels to meet user demand. The employed IT2FNN has both on-line structure and parameter learning abilities. Simulation results for ATM cash forecasting show the feasibility and effectiveness of the proposed method.

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“…IT2 FLCs have been used in AC motors, such as permanent magnet synchronous motors (PMSM) [66] or permanent magnet linear synchronous motor (PMLSM) [67].…”

Section: It2mentioning

confidence: 99%

Review of Recent Type-2 Fuzzy Controller Applications

et al. 2016

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Type-2 fuzzy logic controllers (T2 FLC) can be viewed as an emerging class of intelligent controllers because of their abilities in handling uncertainties; in many cases, they have been shown to outperform their Type-1 counterparts. This paper presents a literature review on recent applications of T2 FLCs. To follow the developments in this field, we first review general T2 FLCs and the most well-known interval T2 FLS algorithms that have been used for control design. Certain applications of these controllers include robotic control, bandwidth control, industrial systems control, electrical control and aircraft control. The most promising applications are found in the robotics and automotive areas, where T2 FLCs have been demonstrated and proven to perform better than traditional controllers. With the development of enhanced algorithms, along with the advancement in both hardware and software, we shall witness increasing applications of these frontier controllers.

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Self-adaptive interval type-2 neural fuzzy network control for PMLSM drives

Cited by 42 publications

References 34 publications

A Speed Disturbance Control Method Based on Sliding Mode Control of Permanent Magnet Synchronous Linear Motor

A Speed Disturbance Control Method Based on Sliding Mode Control of Permanent Magnet Synchronous Linear Motor

A Methodology to Improve Cash Demand Forecasting for ATM Network

Review of Recent Type-2 Fuzzy Controller Applications

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