Artificial Neural Network-Based Control of Switched Reluctance Motor for Torque Ripple Reduction

Table 21

Comparison of the proposed technique with existing techniques.

Parameters	Proposed technique	PI controller	Simplified model of SRM
MSE	MSE is very much reduced in ANN	MSE is higher as compared with ANN	MSE is of large value as compared with ANN and PI
Accuracy	Improved accuracy	Less accurate in comparison with ANN	Lack of accuracy
Conversions	Speedily conversions with reduction in torque ripple	Slow conversions as compared with ANN	Slow conversions as compared with ANN
Generalization	Good generalization when retrained improved performance with time	No generalization property has to be returned and no improvements with time	No generalization property
Simulation speed	Time taken for computation is less and fast in operation	Long computing time	Slow
Performance	Better performance for nonlinear characteristics of SRM	Performance is not up to the expected level	Poor performance
Regression	Regression is in the proximity of 1 which validate performance and fast change of parameters in ANN	No regression property, SRM demands a fast change of parameters, and the PI controller has a slow change of parameters	Nil
Complexity	Less complex because no mathematical model included	Complex because mathematical model included	Complex than ANN and PI controller
Stability	Good stability	Less stable than ANN	Less stable