T-S Fuzzy Tracking Control of Surface-Mounted Permanent Magnet Synchronous Motors with a Rotor Acceleration Observer

Abstract

This paper proposes a fuzzy speed tracking controller and a fuzzy rotor angular acceleration observer for a surface-mounted permanent magnet synchronous motor (SPMSM) based on the Takagi-Sugeno (T-S) fuzzy model. The proposed observer-based controller is robust to load torque variations since it utilizes rotor angular acceleration information instead of the load torque value. Linear matrix inequality (LMI) sufficient conditions are given to compute the gain matrices of the speed tracking controller and the observer. In addition, it is mathematically verified that the proposed observer-based control system is asymptotically stable. Simulation and experimental results are presented to confirm that the proposed control algorithm assures a better transient behavior and less sensitivity under model parameter variations than the conventional PI control method.

Sliding Mode Control of SPMSM Drivers: An Online Gain Tuning Approach with Unknown System Parameters

“…Consequently, the system parameter variations can strongly affect the control performance of these conventional schemes. Moreover, most of the previous methods require an assumption that the time derivative of the load torque is equal to zero [4]- [6], [8]- [11], and [13]. Therefore, these two problems limit the accuracy of the speed regulator.…”

“…In most of the previous speed control methods, z 1 (t), z 2 (t), and z 3 (t), and their time derivatives are commonly ignored and the nominal values of the system parameters (k 1 , k 2 ,..., k 6 ) are used to construct the feedforward control term regardless of these system uncertainties [4], [5], [8], [9], and [13]. However, when the system parameters change during the operation of the drive system, the system parameters used in these controllers are mismatched with their actual values.…”

“…This can have a strong influence on the control performance of these conventional schemes. Another limitation is that, these control methods [4]- [6], [8]- [11], and [13] also need an assumption that the time derivative of the load torque is equal to zero. This may lead to a slow transient behavior of the load torque observer.…”

“…Meanwhile, the feedforward control term is the main and common term of these controllers, which is employed to compensate for the nonlinear coupling factors using nominal parameters. However, a big disadvantage of these control methods as in [4], [5], [8], [9], and [13] is that the feedforward control term requires full knowledge of the system parameters and load torque conditions with a sufficient accuracy. In general, PMSM systems are always met with unavoidable and immeasurable disturbances or some parameter variations.…”

“…First, the feedback control term is designed to make the system dynamics stable. Many researchers are interested in applying the feedback control term into well-known design techniques such as the sliding mode controller [4], [5], feedback linearization controller (FLC) [6], [7], fuzzy logic controller [8], [9], state-dependent Riccati equation controller [10], [11], linear matrix inequality (LMI) controller [12], [13], etc. Meanwhile, the feedforward control term is the main and common term of these controllers, which is employed to compensate for the nonlinear coupling factors using nominal parameters.…”