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This book introduced an adaptive control algorithm to improve the response of the different systems. The self-tuning regulator used based on the radial basis function neural network (RBFNN) for minimum phase and non-minimum phase plants. The technique can estimate the plant parameters online and can be used to update the weights of the RBFNN/ coefficients of the PI. The weight/ coefficient update equations are derived based on the well-known least mean squares principle. Various systems have been involved, some of them minimum phase such as the Single-phase full-converter drive, the magnetic…mehr

Produktbeschreibung
This book introduced an adaptive control algorithm to improve the response of the different systems. The self-tuning regulator used based on the radial basis function neural network (RBFNN) for minimum phase and non-minimum phase plants. The technique can estimate the plant parameters online and can be used to update the weights of the RBFNN/ coefficients of the PI. The weight/ coefficient update equations are derived based on the well-known least mean squares principle. Various systems have been involved, some of them minimum phase such as the Single-phase full-converter drive, the magnetic levitation, one link manipulator and other non-minimum phase such as the flexible transmission.
Autorenporträt
Asmaa Fawzy recevied her B.Sc and M.Sc degrees in electrical engineering from Engineering Faculty, Aswan University and Assiut University, Egypt in 2002 and 2008, respectively. She joined to the Electrical Engineering Department of Energy Engineering Faculty, Aswan University as a Demonstrator in 2004. Currently, she is a Lecturer.