Chaos detection in velocity control of induction motor and its control by using neural network

Asakura, Toshiyuki; Yoneda, K.; Saitō, Yoshio; Shioya, Makoto

doi:10.1109/icosp.2000.893414

Cited by 8 publications

(5 citation statements)

References 7 publications

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“…In order to simplify the calculation of the Poincare map, the rotor position 0 rather than time t is selected as the independent variable of the system. Hence, the system equation becomes [11]: (2) where co is the rotor speed, ik(, VJk) and k (0, ik) (k =1, 2) are the kth phase current and flux linkage, R is the phase resistance, B is the viscous damping, J is the load inertia, T, is the load torque.…”

Section: Modelling Of Chaos In Switched Reluctance Motor Drivesmentioning

confidence: 99%

“…Most of them are based on the identification of chaos, the avoidance of chaos and the stabilization of chaos in various types of electric motor drives [1][2][3][4][5][6]. Many methods deriving form the idea of parameter disturbing, namely OGY method, are employed to stabilize an aperiodic or chaotic rotor speed into a periodic or regular steady state [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

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Chaoization of switched reluctance motor drives

Huang

Chen

Chau³

2005

2005 International Conference on Electrical Machines and Systems

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This paper presents a new technique for the chaoiztion of switched reluctance motor (SRM) drivers. Based on the chaotic modeling of SRM drives, effects of feedback controller gains on the stability of the rotor speed are investigated. In accordance, a control strategy combining piecewise proportional feedback and time-delayed feedback is proposed to produce bound-controllable oscillation around any specific rotor speed. To estimate the continuous influence of a certain control parameter, a Poincare map sampling at every extreme points is constructed, then the bifurcation diagrams are drawn. Theoretical analysis and numerical simulation for a practical 12/8 motor driver are also given.

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Section: Modelling Of Chaos In Switched Reluctance Motor Drivesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Chaoization of switched reluctance motor drives

Huang

Chen

Chau³

2005

2005 International Conference on Electrical Machines and Systems

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“…In 2000, Chen et al [11] studied the time-delayed feedback approach to stabilize the chaotic dynamics in an experimental DC drive. Asakura et al [12] opted neural networks to stabilize the chaotic dynamics of an induction drive system. Nonlinear feedback control [13], sliding mode control [14], and adaptive backstepping control [15] have all been applied towards stabilization of chaos in electrical systems.…”

Section: Introductionmentioning

confidence: 99%

No Chattering and Adaptive Sliding Mode Control of a Fractional‐Order Phase Converter with Disturbances and Parameter Uncertainties

et al. 2018

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Discussing the dynamical properties of various power system models is of significant importance in order to understand its complete behavior. Even though there are many literatures discussing about the chaotic behavior shown by phase converter circuits, none of them have reported the hazardous phenomenon of multistability. In this paper, we derive the fractional-order model of a phase converter circuit and investigate its dynamics. Bifurcation of the system with the parameters and fractional order are investigated. A forward and backward continuation scheme is adopted to display various coexisting attractors; the property of multistability is also discussed. Using forward and backward continuation, various coexisting attractors and the property of multistability are discussed. Two different sliding mode controllers for controlling chaotic oscillations with model disturbances and parameter uncertainties are derived, and the effectiveness of the controllers is discussed with numerical simulations.

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“…As mentioned, these drives may represent stable, unstable and chaotic responses. There are some researches that show the bifurcated and chaotic response of these drives caused by different reasons like inverter malfunction [8,9], error in parameters' values like rotor and stator resistances [10][11][12][13] or even because of an inherent nonlinearity of the system [14]. Some researchers used Poincare map to study these behaviors.…”

Section: Introductionmentioning

confidence: 99%

A Lyapunov Function for Vector Control Drives in Induction Machines

Sangrody¹,

Shariatmadar²

2016

Eng. Technol. Appl. Sci. Res.

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In this paper a useful Lyapunov function for vector control of induction machines is introduced. To do this, some beneficial theorems are reviewed and by applying these theorems and state equations to a vector control drive, its candidate Lyapunov function is achieved. Range of set points such as reference speed, reference flux linkage values and speed controller gain is obtained for such a drive and therefore these values can be set offline to avoid unstable behavior. The simulated and experimental results are given in the last section of the paper to show the efficacy of the given Lyapunov function.

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Chaos detection in velocity control of induction motor and its control by using neural network

Cited by 8 publications

References 7 publications

Chaoization of switched reluctance motor drives

Chaoization of switched reluctance motor drives

No Chattering and Adaptive Sliding Mode Control of a Fractional‐Order Phase Converter with Disturbances and Parameter Uncertainties

A Lyapunov Function for Vector Control Drives in Induction Machines

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