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Polynomial Compensation of Odd Symmetric Nonlinear Actuators via Neural Network Modeling and Neural Network Describing Function

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Innovations and Advances in Computing, Informatics, Systems Sciences, Networking and Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 313))

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Abstract

Paper deals with polynomial compensation of odd symmetric nonlinear actuators. Most actuators are nonlinear sporting odd symmetric nonlinearities such as deadzone and saturation. One way of dealing with such actuators is to try to compensate for nonlinearities by polynomial representation of inverse nonlinearity. Compensated actuators can improve behavior of the system, but then arises the problem of stability analysis because compensated nonlinearity is now complex nonlinearity not described in common literature. One way of dealing with such problem is to perform stability analysis via describing function method. Paper describes the method for compensating nonlinearities, recording describing function and performing stability analysis.

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Acknowledgment

Research was partially supported by HZZZ grant 09/193 Fuzzy Logic Adaptive Elastic Controller.

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Correspondence to O. Kuljaca .

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Kuljaca, O., Horvat, K., Gadewadikar, J., Tare, B. (2015). Polynomial Compensation of Odd Symmetric Nonlinear Actuators via Neural Network Modeling and Neural Network Describing Function. In: Sobh, T., Elleithy, K. (eds) Innovations and Advances in Computing, Informatics, Systems Sciences, Networking and Engineering. Lecture Notes in Electrical Engineering, vol 313. Springer, Cham. https://doi.org/10.1007/978-3-319-06773-5_6

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  • DOI: https://doi.org/10.1007/978-3-319-06773-5_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06772-8

  • Online ISBN: 978-3-319-06773-5

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