Permanent magnet synchronous motor drives, or PMSM drives for short, use integrated nature‐dependent metaheuristic algorithms in this chapter to perform reduced order modeling and controller design in a unified domain. The firefly algorithm (FA) and the grey wolf optimizer (GWO) are two of the most important algorithms in computer science. Together, they form a new hybrid architecture called the hybrid grey wolf optimizer (HGWO). First, a lower‐order model of a permanent magnet synchronous motor drive, comprising of speed and current controllers, was obtained through a reduction using a signal‐processing‐based identification technique. The anonymous proportional‐integral (PI) controller gains can be roughly estimated by matching the reduced system developed in cascade with the controller to a desired system. The gains of the delta operator are nearly replicated by the gains of the continuous‐time controller. This allows for the development of a unified controller for the drive. Thus, the proposed algorithm is useful not only for order diminution but also for determining the control parameters of PMSM drives. In addition, many commonplace and industrial uses of ac motor drives of this type can benefit in future research from this unified approach study.
Hybrid Grey Wolf Optimizer for Modeling and Control of Electric Drives
Linear and Nonlinear System Modeling ; 159-172
08.10.2024
14 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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