Aiming at the dynamic hysteresis nonlinear problem of automotive electronic throttle system,a design method of fuzzy neural network PID controller was proposed.The controller combines the particle swarm optimization algorithm which adjusts the inertia weight dynamically with BP algorithm to optimize the parameters of fuzzy neural network,and corrects the shortcomings of slow convergence and easy to fall into the local minimum in the optimization process of fuzzy neural network.Using the self-learn-ing ability of fuzzy neural network,the PID controller parameters were adjusted.The simulation results show that the optimized fuzzy neural network PID controller has a significant improvement in response time,overshoot and oscillation times compared with the fuzzy PID controller.After the disturbance signal was applied to simulate the airflow disturbance condition,the controller shows good anti-interference performance.In the electronic throttle response experiment,the throttle response curve has a slight over-shoot,but the steady state error is small,which indicates that the electronic throttle has good dynamic response characteristics un-der this control method.
维普
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