Mathematical Problems in Engineering

Volume 2011 (2011), Article ID 964240, 10 pages

http://dx.doi.org/10.1155/2011/964240

## Quasi-Sliding Mode Control of Chaos in Permanent Magnet Synchronous Motor

^{1}Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan^{2}Department of Electrical Engineering, Far East University, Tainan 744, Taiwan^{3}Department of Computer and Communication, Shu-Te University, Kaohsiung 824, Taiwan

Received 24 May 2011; Revised 4 August 2011; Accepted 14 September 2011

Academic Editor: Moez Feki

Copyright © 2011 Cheng-Fang Huang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### Abstract

A quasi-sliding mode control (QSMC) to suppress chaos for a permanent magnet synchronous motor (PMSM) with parameters fall into a certain area is proposed in this paper. Especially, based on the new concept of QSMC, continuous control input is obtained to avoid chattering phenomenon. As expected, the system states can be driven to zero or into a predictable and adjustable bound even when uncertainties are present. Numerical simulations demonstrate the validity of the proposed QSMC design method.

#### 1. Introduction

Since chaotic attractors were found by Lorentz in 1963, many chaotic systems have been constructed. A chaotic system is a very special nonlinear dynamical system and it possesses several properties such as the sensitivity to initial conditions, as well as an irregular, unpredictable behavior and thereby confines the precise operation of physical systems, such as mechanical systems, biological systems, and power converters. In the past twenty years, the idea of controlling chaos with the aim of stabilizing the unstable periodic orbits of a chaotic system has received a great deal of interest, due to its complexity and wide varieties of application. The first research was introduced by Ott et al. [1]. Now, many control techniques for chaos control were used, such as feedback control [2], variable structure control [3], sliding mode control [4, 5], observer-based control [6], and adaptive control [7, 8].

Chaos phenomena in the motor drive with parameters fall into a certain area was introduced by Kuroe and Hayashi in 1980 [9]. Up to now, many classes of motor drive systems have been found with rich phenomena of chaos [10–12]. Since undesired chaotic behavior can extremely destroy the stabilization of the motor or even induce drive system collapse. Therefore, control and suppress chaotic behavior of the motor drive systems is an important problem. The chaotic behavior of permanent magnet synchronous motors (PMSM) has been extensively studied in [12]. Since then, many chaos control methods for PMSM have been proposed [13–15]. Due to physical limitations, practical systems are frequently subjected to uncertainty and the robustness is very important to the control performance. However, in [13–15], the robustness of controlled PMSM systems was only verified by simulation analysis. No complete theoretical discussions are included in their works. On the other hand, sliding mode control has been widely recognized as a powerful approach regarding robust control problems. The main advantage is that the sliding mode control can potentially be exploited to improve control performance such as robustness and fast time response. However, in [16–19], ideal sliding mode only exists for infinite frequency switching operation. From practical point of view, thus control input is impossible to implement and will cause the undesired chattering phenomenon [20, 21]. Thereby, it is necessary to develop a new robust control method without chattering to deal with the PMSM systems with uncertainties.

In this paper, controlling chaos in PMSM was considered. The main contribution of this paper is to introduce a new concept of quasi-sliding mode control (QSMC) technique and propose a continuous controller for avoiding the chattering phenomenon. Furthermore, the chaos of the considered PMSM subjected to uncertainties or disturbances can be fully suppressed or driven into a predictable and adjustable bound. Finally, we present numerical simulation results to illustrate the effectiveness and robustness of the proposed QSMC scheme.

This paper is organized as follows. Section 2 describes the dynamics of a PMSM and formulates the chaos control problem. Definition of the quasi-sliding manifold and the bounds of the states of controlled PMSM in the quasi-sliding manifold will be given in Section 3. In Section 4, the QSMC design is derived. Finally, an illustrative example and conclusions are presented in Sections 5 and 6, respectively.

#### 2. System Description and Problem Formulation

In this section, we consider the chaos suppression of a PMSM model via a quasi-sliding mode controller.

##### 2.1. Mathematical Model of PMSM Drive Systems and Problem Formulation

The transformed model of PMSM with smooth air gap can be described as follows [12]: where and are state variables, which denote angle speed and the direct and quadrature axis currents, respectively. The state can be directly measured while states and can be calculated by the transformation mentioned in [22]. are the transformed axis stator voltage components, respectively, is the transformed external load torque, and are system parameters. In system (2.1), the external inputs are set to zero, that is, , then the system (2.1) becomes an unforced system as: The bifurcation and chaos phenomena of PMSM driver system have been extensively studied in [12] using the modern nonlinear theory. It was pointed out that PMSM drives would display chaotic behavior when parameters of motor fall into a certain area. Figure 1 shows the chaotic motion of system (2.1) in the case of , . This chaotic behavior will cause the torque of PMSM oscillation in a wide range and it can destroy the stabilization of the PMSM drive system. In order to remove chaos, we will consider the chaos control in the PMSM and give an explicit and simple procedure to establish a quasi-SMC to achieve the control goal.

##### 2.2. Problem Formulation

Consider the PMSM as shown in (2.2), to control the system effectively, we use as the manipulated variable which is accessible. By adding this input, the equation of the controlled system with matched uncertainty can be expressed by where is the uncertainty of parameter disturbances and external noise perturbation applied to the PMSM. In general, is assumed to be bounded by where , and are known positive constants.

The considered goal of this paper is to design a QSMC such that the resulting states of PMSM with uncertainties can be driven to predictable and desired bounds.

In consequence, to achieve this control goal for PMSM, there exist two major phases. First, it needs to select an appropriate switching surface for the system such that the motion on the quasi-sliding manifold defined in the next section can ensure all the closed-loop signals bounded. Second, it needs to determine a QSMC such that the existence of the quasi-sliding manifold can be guaranteed.

#### 3. Definition of Quasi-Sliding Manifold and Switching Surface Design

Before completing the above two phases, we first give the definition of quasi-sliding manifold as follows.

*Definition 3.1. *The system (2.2) is said to be in the quasi-sliding manifold if there exist and such that any solution of controlled system (2.2) satisfies , for all .

When the controlled system (2.2) is trapped into the quasi-sliding manifold, the system behavior can be governed by some equivalent dynamics which is relative to the switching surface. Therefore, to make it easy for analyzing the behavior of controlled PMSM in the quasi-sliding manifold, the switching surface is defined as where and is a designed constant. When the system operates in the quasi-sliding manifold, that is, for , from (2.2) and (3.1), the following dynamics of quasi-sliding manifold can be obtained as Solving the differential equation (3.2) for when results in If the system enters the quasi-sliding manifold, according to Definition 3.1, one has . Furthermore, since is determined such that , the bound for state is obtained as Equation (3.4) with shows that Furthermore, by (3.1), the bound for when the time can be also obtained as Meanwhile, after and , solving the differential equation (2.2) for state results in Obviously, by (3.5)–(3.7), the bounds of are relative to . Therefore, to control the system with a smaller value of is important and the solution is given in the following section.

#### 4. QSMC Design for Quasi-Sliding Manifold

Having established an appropriate switching surface and estimating the bounds of the states of system in the quasi-sliding manifold, this section aims to design a QSMC to drive the dynamics (2.2) into the quasi-sliding manifold . To ensure the occurrence of the quasi-sliding manifold, the continuous controller is proposed as where , and .

The proposed control scheme above will guarantee the occurrence of quasi-sliding manifold for the system (2.2), and is proven in the following theorem.

Theorem 4.1. *Consider the system (2.2), if this system is controlled by in (4.1). Then the system trajectory converges to the quasi-sliding manifold, .*

*Proof. *Let the Lyapunov function of the system be , then taking the derivative of and introducing (2.2) and (3.1), one has
Since , we have
Since has been chosen in the controller (4.2), (4.3) implies that , whenever . That is to say that will converge to the region of . Thus the proof is achieved completely.

*Remark 4.2. *From the switching surface (3.1) and [23, Definition 10.10], the relative degree of system (2.3) is 1. Obviously, the states and in (2.3) are controllable while is the internal state which is bounded input-bounded output (BIBO) stable as shown in (2.3). Furthermore, according to the results in (3.4)–(3.6), the state variables of system (2.3) are all bounded.

*Remark 4.3. *Since the controller in (4.1) is continuous, the control is without infinite frequency switching operation and chattering is eliminated.

*Remark 4.4. *In fact, is a design parameter, therefore, one can select a sufficient small value of to make as well as arbitrarily bounded in the neighborhood of zero.

*Remark 4.5. *From the above analysis, a procedure for the robust control of chaos in PMSM is proposed as follows.

*Step 1. *Select to ensure .

*Step 2. *Obtain the switching function from (3.1) and select the control parameters.

*Step 3. *Calculate the predictable bounds by (3.5)–(3.7).

*Step 4. *Obtain the QSMC from (4.1).

#### 5. A Numerical Example

In this section, simulation results are presented to demonstrate and verify the effectiveness and robustness of the proposed QSMC scheme. The system parameters and initial conditions keep the same as those in Figure 1. And then, we impose in the control system. As mentioned in Remark 4.5, the QSMC design procedure for chaos suppression in the PMSM driver can be summarized as follows.

*Step 1. *According to (4.1), parameter is selected such that .

*Step 2. *Consequently, the switching surface is constructed as
Select the control parameters in (4.1) as and and according to Theorem 4.1, we have .

*Step 3. *By (3.5), (3.6), and (3.7), we can calculate the predictable bounds as

*Step 4. *Construct the QSMC from (4.1) as
where ; .

The simulation results are shown in Figures 2–4. Figure 2 shows the three state responses of the PMSM driver (2.3) with . It can be seen from Figure 2 that the three state variables are chaotic when . The corresponding state responses, switching surface , and control input under the proposed QSMC (5.3) under the effect of are shown in Figures 3 and 4, respectively. From the simulation results in Figure 3, it shows that the three state variables are able to converge to the predicted bounds as calculated in (5.2). Also the trajectory of controlled system quickly converges to quasi-sliding manifold and the chattering does not appear due to the continuous control input as shown in Figure 4. Thus the proposed continuous QSMC works well and the chaotic behavior in the PMSM driver is indeed suppressed as desired.

#### 6. Conclusions

In this paper, the chaos suppression problem for permanent magnet synchronous motor is studied. The new concept of quasi-sliding mode control has been introduced to avoid chattering phenomenon as frequently in the conventional sliding mode control systems. As expected, the chaos of the considered PMSM with uncertainties can be suppressed or driven to neighborhood of zero or into predictable bounds without chattering. Numerical simulations have verified the effectiveness of the proposed method.

#### Acknowledgment

This paper was supported by the National Science Council of Republic of China under Contract 100-2221-E-366-001 and 100-2632-E-366-001-MY3.

#### References

- E. Ott, C. Grebogi, and J. A. Yorke, “Controlling chaos,”
*Physical Review Letters*, vol. 64, no. 11, pp. 1196–1199, 1990. View at Publisher · View at Google Scholar · View at Zentralblatt MATH - T. Wang, K. Wang, and N. Jia, “Chaos control and hybrid projective synchronization of a novel chaotic system,”
*Mathematical Problems in Engineering*, vol. 2011, Article ID 452671, 13 pages, 2011. View at Publisher · View at Google Scholar · View at Zentralblatt MATH - J. S. Lin, N. S. Pai, and H. T. Yau, “Robust controller design for modified projective synchronization of Chen-Lee chaotic systems with nonlinear inputs,”
*Mathematical Problems in Engineering*, vol. 2009, Article ID 649401, 10 pages, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH - M. Roopaei, B. Ranjbar Sahraei, and T. C. Lin, “Adaptive sliding mode control in a novel class of chaotic systems,”
*Communications in Nonlinear Science and Numerical Simulation*, vol. 15, no. 12, pp. 4158–4170, 2010. View at Publisher · View at Google Scholar - L. Boutat-Baddas, J. P. Barbot, D. Boutat, and R. Tauleigne, “Sliding mode observers and observability singularity in chaotic synchronization,”
*Mathematical Problems in Engineering*, no. 1, pp. 11–31, 2004. View at Publisher · View at Google Scholar · View at Zentralblatt MATH - X. S. Yang and G. Chen, “Some observer-based criteria for discrete-time generalized chaos synchronization,”
*Chaos, Solitons and Fractals*, vol. 13, no. 6, pp. 1303–1308, 2002. View at Publisher · View at Google Scholar · View at Zentralblatt MATH - W. P. Guo and D. T. Liu, “Adaptive control of chaos in chua's circuit,”
*Mathematical Problems in Engineering*, vol. 2011, Article ID 620946, 14 pages, 2011. View at Publisher · View at Google Scholar - J. S. Lin and J. J. Yan, “Adaptive synchronization for two identical generalized Lorenz chaotic systems via a single controller,”
*Nonlinear Analysis. Real World Applications*, vol. 10, no. 2, pp. 1151–1159, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH - Y. Kuroe and S. Hayashi, “Analysis of bifurcation in power electronic induction motor drive systems,” in
*Proceedings of the 20th Annual IEEE Power Electronics Specialists Conference (PESC '89)*, pp. 923–930, Milwaukee, Wis, USA, 1989. View at Publisher · View at Google Scholar - Z. Suto, I. Nagy, and E. Masada, “Avoiding chaotic processes in current control of AC drive,” in
*Proceedings of the 29th Annual IEEE Power Electronics Specialists Conference (PESC '98)*, pp. 255–261, Fukuoka , Japan, 1998. - J. H. Chen, K. T. Chau, and C. C. Chan, “Analysis of chaos in current-mode-controlled dc drive systems,”
*IEEE Transactions on Industrial Electronics*, vol. 47, no. 1, pp. 67–76, 2000. View at Publisher · View at Google Scholar - Z. Li, J. B. Park, Y. H. Joo, B. Zhang, and G. Chen, “Bifurcations and chaos in a permanent-magnet synchronous motor,”
*IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications*, vol. 49, no. 3, pp. 383–387, 2002. View at Publisher · View at Google Scholar - A. M. Harb, “Nonlinear chaos control in a permanent magnet reluctance machine,”
*Chaos, Solitons and Fractals*, vol. 19, no. 5, pp. 1217–1224, 2004. View at Publisher · View at Google Scholar - H. Ren and D. Liu, “Nonlinear feedback control of chaos in permanent magnet synchronous motor,”
*IEEE Transactions on Circuits and Systems II*, vol. 53, no. 1, pp. 45–50, 2006. View at Publisher · View at Google Scholar - D. Q. Wei, X. S. Luo, B. H. Wang, and J. Q. Fang, “Robust adaptive dynamic surface control of chaos in permanent magnet synchronous motor,”
*Physics Letters A*, vol. 363, no. 1-2, pp. 71–77, 2007. View at Publisher · View at Google Scholar - H. Guo, S. Lin, and J. Liu, “A radial basis function sliding mode controller for chaotic Lorenz system,”
*Physics Letters A*, vol. 351, no. 4-5, pp. 257–261, 2006. View at Publisher · View at Google Scholar - T. Y. Chiang, M. L. Hung, J. J. Yan, Y. S. Yang, and J. F. Chang, “Sliding mode control for uncertain unified chaotic systems with input nonlinearity,”
*Chaos, Solitons and Fractals*, vol. 34, no. 2, pp. 437–442, 2007. View at Publisher · View at Google Scholar · View at Zentralblatt MATH - T. Yang and L. O. Chua, “Impulsive stabilization for control and synchronization of chaotic systems: theory and application to secure communication,”
*IEEE Transactions on Circuits and Systems I*, vol. 44, no. 10, pp. 976–988, 1997. View at Publisher · View at Google Scholar - M. C. Pai, “Sliding mode control of vibration in uncertain time-delay systems,”
*Journal of Vibration and Control*, vol. 16, no. 14, pp. 2131–2145, 2010. View at Publisher · View at Google Scholar - M. Roopaei and M. Z. Jahromi, “Chattering-free fuzzy sliding mode control in MIMO uncertain systems,”
*Nonlinear Analysis. Theory, Methods & Applications*, vol. 71, no. 10, pp. 4430–4437, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH - H. Lee and V. I. Utkin, “Chattering suppression methods in sliding mode control systems,”
*Annual Reviews in Control*, vol. 31, no. 2, pp. 179–188, 2007. View at Publisher · View at Google Scholar - J. Šimánek, J. Novák, R. Doleček, and O. Černý, “Control algorithms for permanent magnet synchronous traction motor,” in
*Proceedings of the EUROCON International Conference on “Computer as a Tool”*, pp. 1839–1844, 2007. View at Publisher · View at Google Scholar - H. J. Marquez,
*Nonlinear Control Systems: Analysis and Design*, John Wiley & Sons, New York, NY, USA, 2003.