engleski

Neural Network Applications in Modern Induction Machine Control Systems

This chapter shows an overview of neural network applications in modern induction machine control systems. Induction motors have been used as the workhorse in industry for a long time due to their being easy to build, highly robust, and having generally satisfactory efficiency. In addition, induction generators play an important role in renewable energy systems such as energy systems with variable-speed wind turbines. The induction machine is a nonlinear multivariable dynamic system with parameters that vary with temperature, frequency, saturation and operating point. Considering that neural networks are capable of handling time varying nonlinearities due to their own nonlinear nature, they are suitable for application in induction machine systems. In this chapter, the use of artificial neural networks for identification and control of induction machine systems will be presented. An overview of neural network applications in induction machine control systems will be focused on: 1.Drive feedback signal estimation, 2.Inverter control, 3.Identification of machine parameters, 4.Neural network based approaches for the efficiency improvement in induction machine systems, 5.Neural network implementations by digital signal processors and ASIC chips.

Artificial Neural Network, Induction Machine, Control System

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