Five phase multi-layer drive with fault tolerant neuro-fuzzy features for safety critical applications
| Autor: | Marco Tursini, Alessio Di Tullio, F. Parasiliti, Kan Akatsu |
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| Rok vydání: | 2017 |
| Předmět: |
Engineering
Control and Optimization Neuro-fuzzy Multi-layer motor Multiphase motor Energy Engineering and Power Technology PID controller 02 engineering and technology Fault (power engineering) Safety critical application 0203 mechanical engineering Control theory 0202 electrical engineering electronic engineering information engineering Torque Fault tolerant Electrical and Electronic Engineering Artificial neural network business.industry Mechanical Engineering 020208 electrical & electronic engineering 020302 automobile design & engineering Control engineering Fault tolerance Neuro-fuzzy control Cognitive network Neural network Motor drive business |
| Zdroj: | 2017 20th International Conference on Electrical Machines and Systems (ICEMS). |
| DOI: | 10.1109/icems.2017.8056487 |
| Popis: | This article presents a method for control of a multiphase motor drive based on the use of a cognitive network that is capable of modelling nonlinearities of the system in fault conditions. To obtain a faithful model of the drive, a neural network (trained with the results of simulated faults) is used in the control algorithm in order to predict the system performance and adapt the control. A new multiphase motor with variable characteristics, particularly suited to applications in which a very wide variability of the speed range is required, will be described and presented in its structure. The technique to remedy failure adopted for this drive will be presented and described in its characteristics. The effectiveness of the control technique lastly will be highlighted by simulations that put it in comparison with classical solutions that employ PID controllers. |
| Databáze: | OpenAIRE |
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