1、PDF外文：http:/ Linear Matrix Inequality-Based Fuzzy Control for Interior Permanent Magnet Synchronous Motor with integral sliding mode control FaGuang Wang, SeungKyuPark, Ho Kyun Ahn Department of Electrical Engineering, Changwon National University, Korea Abstract-Recently, interior permanent m
2、agnet synchronous motor (IPMSM) is widely used in various applications, such as electric vehicles and compressors. It has a high requirement in wide load variations, high speed condition, stability, providing a fast response and most important thing is that it can be applied easily and efficiently.
3、However, the control of IPMSM is more difficult than surface permanent magnet synchronous motor (SPMSM) because its nonlinearity due to the non-zero daxis current which can be zero in SPSM but not IPMSM. In this paper, the IPMSM is controlled very efficient algorithm by using the combination of line
4、ar control and fuzzy control with linear models depending on certain operating points. The H linear matrix inequality (LMI) based integral sliding mode control is also used to ensure the robustness. The membership functions of this paper are easy to be determined and implemented easily. Index Terms-
5、Fuzzy control, H control, integral sliding mode control, interior permanent magnet synchronous motor (IPMSM), linear matrix inequality. I. INTRODUCTION From 1980s , with the development of semiconductor, IPMSM supplied by converter source has been widely studied 1 2. The development of microco
6、mputer made the vector control system of IPMSM well controlled by single chip. IPMSM possesses special features for adjustable-speed drives which distinguish it from other classes of ac machines, especially surface permanent magnet synchronous motor. The main criteria of high performance drives are
7、fast and accurate speed response, quick recovery of speed from any disturbances and insensitivity to parameter variations 3. In order to achieve high performances, the vector control of IPMSM drive is employed 4-6. Control techniques become complicated due to the nonlinearities of the developed torq
8、ue for non-zero value of d-axis current. Many researchers have focused their attention on forcing the daxis current equals to zero in the vector control of IPMSM drive, which essentially makes the motor model linear 4,7. However, in real-time the electromagnetic torque is non-linear in nature. In or
9、der to incorporate the nonlinearity in a practical IPMSM drive, a control technique known as maximum torque per ampere (MTPA) is devised which provides maximum torque with minimum stator current 3. This MTPA strategy is very important from the limitation of IPMSM and inverter rating points of
10、view, which optimizes the drive efficiency. The problem associated MTPA control technique is that its implementation in real time becomes complicated because there exists a complex relationship between d-axis and q-axis currents. Thus, one of the main objectives of this paper is to make a new effici
11、ent control method for IPMSM and its calculation easy and efficient. The LMI fuzzy H control has been applied and solved the nonlinearity of the IPMSM model to a set of linear model. To increase the robustness for disturbances, an ISMC technique is added to the H controller. By ISMC, the proposed co
12、ntroller gives performances of the H control system without disturbances which satisfy the matching condition. It has a good compatible with linear controllers. T-S fuzzy control 8 is based on the mathematical model which is the combination of local linear models depending on the operating points. L
13、inear controllers are designed for each linear model and they are combined as a controller and make it possible to use linear control theories for nonlinear systems. Linear controls via parallel distributed compensation (PDC) and linear matrix inequality (LMI) is a most popular method considering th
14、e stability of the system with PDC 9. H LMI T-S fuzzy controller is considered as a practical H controller which eliminates the effects of external disturbance below a prescribed level, so that a desired H control performance can be guaranteed 10-12. In this paper, the robustness of SMC 13 is added
15、to the H LMI T-S fuzzy controller for the control of IPMSM. We can divide the disturbances in the IPMSM into two parts. First part is that SMC can deal with and other part is dealt by H LMI fuzzy controller. By using ISMC, the robustness of SMC and H performance can be combined. Integral sliding mod
16、e control (ISMC) is a kind of SMC which has sliding mode dynamics with the same order of the controlled system and can have the properties of the other control method. II. H T-S FUZZY CONTROL AND ISMC A. H T-S fuzzy control Consider a nonlinear system as follows. x(t)f (x)g(x)u(t)w(t) (1) where |w(t
17、)| Wb and Wbis the boundary of disturbance. Depending on the operating points, the nonlinear system can be expressed as follows. The i-th model is that in the case z1(t) is Mi1 and and z p(t) is Mip , (2) And H T-S fuzzy feedback controller is uikiX(t) (3) where i=1,2, ,r an
18、d Mij is the fuzzy set and r is the number of model rules Given a pair of (x(t),u(t), the fuzzy systems are inferred as follows: where and i(z(t) is the membership for every fuzzy rule. From (1) we get (7) Take (6) into (7), we can get the closed loop system equations. If we set Apresent the error boundary of every rule and satisfy the following condition:
