Neural networks application for mechanical parameters identification of asynchronous motor

Martin Lešo, Dušan Balara, Jaroslav Timko, Jaroslava Žilková


A method for identification of mechanical parameters of asynchronous motor is presented in this paper. The identification method is based on the use of our knowledge about the system. This paper clarifies the method using the example of identifying mechanical parameters of the three-phase squirrel-cage asynchronous motor. Model of mechanical subsystem of the motor is presented as well as results of simulation. The special neural network is used as identification model and its adaptation is based on the gradient descent method. Parameters of mechanical subsystem are derived from the values of synaptic weights of the neural identification model after its adaptation. Deviation of identified mechanical parameters in case moment of inertia was up to 0.03\% and in case of load torque was 1.45 \% of real values.


Neural network, identification, electric drive


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