Performance Improvement of Reluctance Synchronous Motor Using Brain Emotional Learning Based Intelligent Controller

Abstract

In this paper, intelligent control of a reluctance synchronous motor by an emotional controller, considering the effect of magnetic saturation on implementation, is analyzed; the maximum torque per ampere (MTPA) strategy is provided. According to the application of the proposed control scheme, the structure adequately performs the control of speed and magnetic flux of the reluctance synchronous motor drive. Additionally, the application of intelligent control based on an emotional learning system has provided adequate results to create a proper control process. The control function of a SynRM drive based on vector control in a rotor machine was compared with another based on emotional controllers and a PI controller regulated by genetic algorithms. The result of this comparison was the improvement of control functions by the controller based on the emotional controller. In addition, the MTPA based on search algorithms was well implemented in different situations. Due to its simplicity and independence from system parameters, the emotional controller can be considered as a potential operational method in the industry.

Parameter Identification for Maximum Torque per Ampere Control of Permanent Magnet Synchronous Machines under Magnetic Saturation

“…The above partial derivatives are derived from the differentials of each term on the right side of Equation (17), respectively. The constant coefficients, such as a, b, c, d and e, have nothing to do with partial derivatives.…”

“…In machine parameter-independent methods, the extreme seeking methods based on signal injection have become mainstream [11][12][13][14][15][16][17]. This method can track MTPA points in real time by injecting specific signals into the IPMSM, such as high-frequency current [11,12] or voltage [13,14].…”

Improved performance and robustness of synchronous reluctance machine control using an advanced sliding mode and direct vector control

“…37 The field has also seen the adoption of intelligent control mechanisms, such as the use of a recurrent Legendre fuzzy neural network for MTPA tracking control of SynRM, 38 and the application of emotional controllers that consider magnetic saturation to optimize performance under various conditions. 39 Comparative studies form a cornerstone of this domain, with research contrasting adaptive backstepping (ABS) speed control systems with other methods, highlighting improvements in SynRM drive responsiveness. 40 Distinctions between SynRMs and switched reluctance motors (SRMs) have been drawn, noting the simplicity of control but also the challenge of high torque ripples in SRMs.…”

“…These insights pave the way for more effective current control methods 37 . The field has also seen the adoption of intelligent control mechanisms, such as the use of a recurrent Legendre fuzzy neural network for MTPA tracking control of SynRM, 38 and the application of emotional controllers that consider magnetic saturation to optimize performance under various conditions 39 …”