Hopfield Neural Network Based Identification and Control of Induction Motor Drive System -- Part I: Identification

摘要

The paper discusses a Hopfield-Neural-Network (HNN) based linear system parameters identification scheme in part I, under the assumption that HNN inputs are the detected system states delayed by sensors. Sufficient condition of correctidentification is derived. The scheme is used for identification of rotation inertia (J), speed damping coefficient (R{sub}Ω) and load torque (T{sub}i) of induction motor drive system. Simulation results show that even under bad working condition causedby incorrect setting to the controllers, the derived scheme guarantees correct identify results.