Article

A HYBRID TECHNIQUE FOR FREQUENCY DOMAIN IDENTIFICATION OF SERVO SYSTEM WITH FRICTION FORCE

International Journal of Engineering Science and Technology 01/2011;
Source: DOAJ

ABSTRACT

The system identification process in servo system with frictional force seems to be a complex task becauseof its non-linear nature. For such non-linear systems, a good choice is system identification in frequencydomain. However, most of the techniques are manual and are inappropriate for determination of systemparameters. This makes system identification ineffective for servo systems with frictional force. Toovercome this issue, a hybrid technique is proposed in this paper. The proposed technique exploits neuralnetwork and genetic algorithm to determine the system parameters of servo systems with friction. In theproposed technique, the target parameters are determined from the transfer function derived for thesystem. Subsequently, the system parameters are identified by a process formed by blending the neuralnetwork and genetic algorithm techniques. Prior to performing the identification procedure, backpropagation training is given to the neural network using a pre-examined dataset. Then with thecombined operation of neural network and genetic algorithm, the system parameters that are closer tothe target parameters for the servo system with frictional force are determined. The technique isimplemented and compared with the existing frequency domain identification technique. From thecomparative results, it is evident that the proposed technique outperforms the existing technique.

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