# Dynamical analysis of the permanent-magnet synchronous motor chaotic system

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## Abstract

This paper is concerned with some dynamics of the permanent-magnet synchronous motor chaotic system based on Lyapunov stability theory and optimization theory. The innovation of the paper lies in that we derive a family of mathematical expressions of globally exponentially attractive sets for this chaotic system with respect to system parameters. Numerical simulations confirm that theoretical analysis results are correct.

### Keywords

permanent-magnet synchronous motor chaotic attractors Lyapunov stability numerical simulations## 1 Introduction

Since Lorenz *et al.* were the first to investigate the Lorenz equations in 1963, chaotic systems have played an important role in a variety of industrial fields [1, 2, 3, 4, 5, 6, 7, 8]. As is well known, the research on chaos is not limited to the fields of mathematics and physics. It is found that chaos widely exists in the fields of meteorology, medicine, computer science, economics, mechanical engineering, cryptography, and so on [9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]. However, it was not until the 1990s that chaos has gradually attracted enough attention due to the findings in practical engineering. From the point of view of the potential application of chaos theory in practical engineering, many efforts have been made to study chaos in the past 20 years.

This paper mainly focuses on the chaotic system model from a permanent-magnet synchronous motor (PMSM) which is a nonlinear, multivariable, and strong coupling system. A permanent-magnet synchronous motor is a kind of highly efficient and high-powered motor, which has been widely used in the industry. Usually, the dynamics of a PMSM is modeled as a three-dimensional autonomous differential equation [20, 21]. Dynamical behaviors of the PMSM, such as periodic solutions, chaos phenomena, phase portraits, bifurcation diagrams, Lyapunov exponents, chaos anti-control and chaos synchronization, have been widely studied in [20, 21].

In recent years, dynamical behaviors of chaotic systems, such as stability, periodic solutions, circuit implementation, image encryption algorithm, chaos synchronization, chaos attractors, heteroclinic orbits and homoclinic orbits, have been extensively investigated [22, 23, 24]. However, little seems to be known about the global exponential attractive set of chaotic systems [22, 23, 24]. Despite the fact that many qualitative and quantitative results on the permanent-magnet synchronous motor system have been obtained [20, 21], there is a fundamental question that has not been completely answered so far: is there a global exponential attractive set for the permanent-magnet synchronous motor system? Global exponential attractive sets play an important role in dynamical systems. The global exponential attractive set is also very important for engineering applications, since it is very difficult to predict the existence of hidden attractors and they can lead to crashes [10]. Therefore, how to get the global attractive sets of a chaotic dynamical system is particularly significant both for theoretical research and practical applications. In [25, 26], one shows that Lyapunov functions can be used to study chaos synchronization. However, Lyapunov-like functions used in [16, 18, 25, 26] cannot be used to study the global attractive sets for the permanent-magnet synchronous motor system. In this paper, a new Lyapunov-like function is constructed to investigate the global attractive sets of the permanent-magnet synchronous motor system.

Motivated by the above discussion, we will investigate the global attractive sets of the permanent-magnet synchronous motor system. The meaning of the contribution of this article is that not only do we derive a family of mathematical expressions of global exponential attractive sets for permanent-magnet synchronous motor systems in [20, 21] with respect to the parameters of the system, but we also get the rate of the trajectories of the system going from the exterior of the trapping set to the interior of the trapping set.

The rest of the paper is organized as follows. The permanent-magnet synchronous motor (PMSM) model is given in Section 2. In Section 3, we prove that there exist global exponential attractive sets for the chaotic PMSM system. Some numerical simulations are also given in Section 3. Section 4 gives conclusions.

## 2 Permanent-magnet synchronous motor model

*ω*are the state variables, which represent currents and motor angular frequency, respectively; \(u_{d}\) and \(u_{q}\) represent the direct- and quadrature-axis stator voltage components, respectively;

*J*represents the polar moment of inertia; \(T_{L}\) represents the external load torque;

*β*represents the viscous damping coefficient; \(R_{1}\) represents the stator winding resistance; \(L_{d}\) and \(L_{q}\) represent the direct- and quadrature-axis stator inductors, respectively; \(\psi_{r}\) represents the permanent-magnet flux, and \(n_{p}\) represents the number of pole-pairs, the parameters \(L_{d}\), \(L_{q}\),

*J*, \(T_{L}\), \(R_{1}\), \(\psi_{r}\),

*β*are positive.

*x*,

*y*and

*z*are the new variables of the system (3), and the parameters

*γ*and

*σ*are positive constants.

*x*,

*y*and

*z*are the new variables of the system (4), and the parameters

*γ*and

*σ*are positive constants. There exist complex nonlinear dynamical behaviors in the system (4) including chaos and periodic orbit. The butterfly chaotic attractor of the system (4) with \(\gamma= 100\) and \(\sigma= 10\) in the \(xoyz\) space is shown in Figure 1. Chaotic attractors of the system (4) with \(\gamma= 100\) and \(\sigma= 10\) on the

*x*-

*y*,

*x*-

*z*, and

*y*-

*z*planes are shown in Figure 2.

The periodic and chaos phenomena, phase portraits, bifurcation diagrams, Lyapunov exponents, chaos anti-control of the permanent-magnet synchronous motors (2), (3) and (4) are widely studied in [20, 21] in detail. But the global exponential attractive sets of systems (2)-(4) are still unknown. Our principal aim here is to investigate the global exponential attractive sets of (2), (3) and (4).

## 3 Dynamics of the PMSM

In this section, we will discuss the global exponential attractive sets of PMSM system (2), (3) and (4). We have the following results.

### Theorem 1

*For*\(\forall\lambda> \frac{1}{\vert \varepsilon \vert } > 0\), \(L_{q} > 0\), \(L_{d} > 0\), \(\sigma> 0\),

*with*

*When*\(V_{\lambda} ( X ( t ) ) > L_{\lambda}\), \(V_{\lambda} ( X ( t_{0} ) ) > L_{\lambda}\),

*we can get the exponential estimate of the system*(2),

*given by*

*That is to say*,

*the set*

*is the global exponential attractive set of the permanent*-

*magnet synchronous motor system*(2).

### Proof

*t*along the trajectory of system (2) yields

This completes the proof. □

### Theorem 2

*For*\(\forall\lambda> 0\), \(\sigma> 0\),

*with*

*When*\(V_{\lambda} ( X ( t ) ) > M_{\lambda}\), \(V_{\lambda} ( X ( t_{0} ) ) > M_{\lambda}\),

*we can get the exponential estimate of the system*(3),

*given by*

*That is to say*,

*the set*

*is the global exponential attractive set of the permanent*-

*magnet synchronous motor system*(3).

### Proof

This completes the proof. □

### Remark 1

*x*and

*z*in system (4), the PMSM model (4) can be written in the form of the Lorenz system (11) as follows:

## 4 Conclusions

In this paper, the global attractive sets of the permanent-magnet synchronous motor have been obtained based on dynamical systems theory. This method can be applied to consider other chaotic systems. In the future we will conduct research on how to control the PMSM to avoid the chaotic behavior and protect the motors in practical applications.

## Notes

### Acknowledgements

This work is supported by National Natural Science Foundation of China (Grant Nos. 11501064, 11426047), the Basic and Advanced Research Project of CQCSTC (Grant No. cstc2014jcyjA00040), the Scientific and Technological Research Program of Chongqing Municipal Education Commission (Grant No. KJ1500605), the Research Fund of Chongqing Technology and Business University (Grant No. 2014-56-11), China Postdoctoral Science Foundation (Grant No. 2016M590850) and the Program for University Innovation Team of Chongqing (Grant No. CXTDX201601026). We thank professors Min Xiao in the College of Automation, Nanjing University of Posts and Telecommunications and Gaoxiang Yang at the Department of Mathematics and Statistics of Ankang University for their help. The authors wish to thank the editors and reviewers for their conscientious reading of this paper and their numerous comments for improvement which were extremely useful and helpful in modifying the paper.

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