This paper proposes an enhanced brain emotional learning-based intelligent controller for synchronous reluctance motor (SynRM) drives. The controller is based on an emotional learning and decision making mechanism in the brain via emotional cues and sensory inputs. Furthermore, the enhanced controller improves learning process in the amygdala to avoid internal instability. In spite of the development for interior-stability, the proposed controller could keep its ability to deal with challenges related to SynRM drives. The proposed controller is also contributed with a speed deviation control. The new deviation controller is based on model but parameter-free. The updated system is implemented in real-time by a PC-based three-phase 370W laboratory SynRM. The proportional-integral (PI) controllers used in a standard rotor field-oriented control structure are replaced with those of the proposed method. The speed and d-axis stator current references are accurately tracked. The achieved performances by the proposed controllers are compared with those of optimized conventional PI controller in different situations. Considering the results, the enhanced system shows superiority over the traditional system in terms of fast dynamics, easy tuning, and robustness against disturbances and parameter variations.