Enhanced adaptive sliding mode control with termination parallelism cooperative optimization for torque ripple reduction in switched reluctance motor drives.

Switched reluctance motors (SRMs) are known for their sturdy construction, ability to run at high speeds, and fault tolerance. However, they still suffer from torque ripple, which limits their use in high‑performance drives. This project develops and tests an improved adaptive sliding‑mode control (SMC) scheme that works with a termination‑parallelism cooperative optimization algorithm to reduce torque ripple in SRM drives. The new control framework tackles the chattering that ordinary sliding‑mode controllers produce by adjusting the control gains in real time. A cooperative optimization strategy using parallel termination criteria is added to tune the control parameters online, giving fast convergence and reliable tracking even when the load changes. Detailed simulations are

used to examine the SRM drive’s dynamic response, torque‑ripple coefficient, and speed‑tracking accuracy. The work also provides step‑by‑step guidance for modeling the SRM’s nonlinear behavior and designing the adaptive control law to achieve better torque performance. This research lays the groundwork for applying advanced robust control methods in industrial motor drives.

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