Robust Control Method f or PMSM Based o n Internal Model Control w ith Speed a nd Load Torque Estimator

Abstract

A Robust controller designed by employing internal model control (IMC) is presented for permanent magnet synchronous motor (PMSM) drive with estimation of both the rotor speed and the load torque with a predictive state observer. It is to achieve accurate control performance in the presence of uncertainties and system parameters variation. The Experimental results prove that the IMC controller with the presence of the predictive state observer greatly improves the performances of the speed loop and simplifies the design procedure. The robustness of this scheme is analysed, and the bounds of control parameters that ensure the drive stability are obtained. Keywords:Internal model control, permanent magnet synchronous motor, PI controller, speed estimator. IntroductionDuring these last decades, the PMSM found a very great interest in many industrial applications, due to considerations of cost, size, low maintenance, speed capability and simplicity of design. However, the PMSM presents a coupled non-linear multi variable control structure which requires a complex nonlinear control in order to achieve good dynamic performances [1][2][3][4][5].The machine drive systems with high performances must allow the development of control strategies which offer a strict follow-up in position and in speed. Moreover, these performances must be insensitive to the variations of the machine parameters, especially the mechanical parameters such as the inertia moment of the rotating mass.Improved and robust control of these processes is becoming necessary due to increasing competition and environmental considerations. Also, the availability of advanced technology and inexpensive computing power are a consequent for design and implementation of advanced control strategies. Many control techniques have been proposed and analyzed for nonlinear processes, and a good review of these is available in literature [6][7][8]. Linear internal model control as a general structure that uses a model in parallel with the process has become very popular among practicing engineers [9][10][11][12][13][14][15][16][17][18].IMC was widely used in the chemical industries, mostly in the form of proportionalintegral-derivative (PID) controllers, in which a clear tradeoff between closed loop performance and robustness to model uncertainty is provided [12][13][14]. Besides its industrial importance, IMC also provides a convenient theoretical framework for understanding the performance limitations due to non minimum-phase behavior and model uncertainty [15][16][17][18].In this work, an IMC strategy is proposed and applied to the PMSM speed control with estimating the rotor speed and load torque.

Sensorless Digital Control of a Permanent Magnet Synchronous Motor

“…This structure is illustrated by the diagram in Figure 3. The pole placement algorithm is summarized as follows [12,18]:…”

“…We choose PT(q -1 ) in the form of a second order polynomial defined by its natural pulsation (0) and it's damping coefficient () while ensuring the following condition [12,18]:…”

“…After having chosen the polynomial PT(q -1 ), Eq. (5) allows obtaining the polynomials S and R. The polynomial T is given by [12,18]:…”

Adaptive super-twisting-based nonsingular fast terminal sliding mode control of permanent magnet linear synchronous motor

“…Due to the above reasons, extensive achievements have been achieved in the field of advanced motor drive methods, such as robust control (Sebaa et al, 2017; Yao et al, 2011), model predictive control (Kang et al, 2019; Yang et al, 2019), intelligent control (Hu et al, 2020; Lin, 2020) and sliding mode control (SMC) (Saghafinia et al, 2014; Zhang et al, 2012). As a nonlinear robust control method, SMC has the advantages of strong robustness and simple design method.…”