High-Accuracy Dynamic Load Emulation Method for Electrical Drives
| Autor: | Carlos Matheus Rodrigues de Oliveira, Manoel Luis de Aguiar, Paulo Roberto Ubaldo Guazzelli, José Roberto Boffino de Almeida Monteiro, William Cesar de Andrade Pereira, Allan Gregori de Castro |
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| Rok vydání: | 2020 |
| Předmět: |
Coupling
Electronic speed control Emulation Mechanical load Computer science business.industry 020208 electrical & electronic engineering 02 engineering and technology Transfer function Dynamic load testing Renewable energy Mechanical system Nonlinear system Control and Systems Engineering Control theory 0202 electrical engineering electronic engineering information engineering Torque Electrical and Electronic Engineering business Induction motor Parametric statistics |
| Zdroj: | IEEE Transactions on Industrial Electronics. 67:7239-7249 |
| ISSN: | 1557-9948 0278-0046 |
| Popis: | This article addresses the problem of dynamic load emulation (DLE) with high accuracy of any mechanical load for which the mathematical model is known. The control strategy of a load machine is used to design tasks of control algorithms of variable speed and torque drives for educational purposes and several engineering applications, as transportation and renewable energy. The structure uses a set-point feed-forward compensator with speed-tracking controller, which provides robustness under parametric variation and nonmodeled dynamics. Nonlinear effects and constraints of the experimental setup shaft can be included in the compensator, which makes the strategy an alternative method for systems operating under different degrees of uncertainty. Moreover, different control approaches can be applied to both compensator and speed controller. The method can be applied with any rotary machines, where two induction motors (IMs) with directly coupling are adopted. The method was compared to two other DLE methods and was validated through nonlinear models whose inertia and friction are not constant. The simulated and experimental results are very similar, even when high uncertainty is assumed. |
| Databáze: | OpenAIRE |
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