Анотація:
A feedforword neural network of multi-layer topologies for systems with hysteretic nonlinearity was constructed based on the Bouc-Wen differential model. The proposed model not only reflects the hysteresis force characteristics of the Bouc-Wen model, but can also determine the corresponding parameters. The simulation results demonstrate that the restoring force-displacement curve hysteresis loop closely represents real curves. The trained model can accurately predict the time response of the system. By comparing results obtained by the proposed model with real responses, the model was validated in the presence of noise and exhibits increased modeling precision, good generalizability and anti-interference capability.