AI Summary & Key Takeaways
AI InsightSimulation results showing the excellent performance of the proposed emulation strategy are presented
📌 3 Key Takeaways
Abstract
This paper proposes a neuro-fuzzy controller for a vector controlled load machine (dynamometer) which is mechanically coupled to a drive machine for the emulation of nonlinear loads. The main objective is to provide a system for testing of high performance electrical drives under nonlinear loads. The proposed emulation strategy is based on the model reference control approach using an on-line trained Neuro-Fuzzy Controller (NFC). The emulation is placed in the closed speed loop of the drive machine. Varieties of dynamic load models which are the nonlinear functions of the shaft speed are successfully emulated and the generalization capability of the trained NFC is shown. Simulation results showing the excellent performance of the proposed emulation strategy are presented
Özet
This paper proposes a neuro-fuzzy controller for a vector controlled load machine (dynamometer) which is mechanically coupled to a drive machine for the emulation of nonlinear loads. The main objective is to provide a system for testing of high performance electrical drives under nonlinear loads. The proposed emulation strategy is based on the model reference control approach using an on-line trained Neuro-Fuzzy Controller (NFC). The emulation is placed in the closed speed loop of the drive machine. Varieties of dynamic load models which are the nonlinear functions of the shaft speed are successfully emulated and the generalization capability of the trained NFC is shown. Simulation results showing the excellent performance of the proposed emulation strategy are presented.