Advanced Control Techniques Based Controllers for Different Systems
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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 l...
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.
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