Research and application of intelligent car based on BP neural network PID control

Abstract

This paper aims to study and apply the BP neural network-based PID control for intelligent cars. Although the traditional PID controller has been widely used in control systems, its difficulties in parameter tuning and poor adaptability limit its performance in complex environments. To address this, the BP neural network is introduced as an auxiliary component to enhance the control system's robustness and adaptability. The paper first introduces the principles of PID controllers and BP neural networks and then designs a control strategy based on BP neural network-based PID control, taking into account the characteristics of the intelligent car system. Subsequently, the effectiveness of the control strategy on intelligent cars is verified through experiments and simulations, analyzing its performance indicators. Finally, the potential applications and future directions of intelligent cars in different scenarios are discussed.