Intelligent Vehicle Control And Realization Based On Fuzzy Improved Adaptive PID

At present,there are many deficiencies in smart car control,such as insufficient robustness and precision,and the lack of stability in dynamic response.In this paper,the lack of intelligent vehicle control has been studied and improved.Because the driving of the smart car is a time-varying nonlinear system,there will be disturbances or mutations at any time,and it cannot be predicted in advance.The traditional PID algorithm cannot meet its control requirements well.In order to make the car more accurate,smooth angle,acceleration and deceleration,to optimize the precision of steering angle steering operation and to achieve the best speed control of the motor,this paper uses an efficient fuzzy improved adaptive PID algorithm,which combines fuzzy control theory with traditional PID algorithm,which can be better to overcome the shortcomings of the traditional PID algorithm of the smart car system that cannot adjust the parameters in real time,improve the adaptability of the smart car in sudden changes in external scenes and different road conditions,and increase the efficiency and robustness of speed control.In the description of this article,first of all,the research background of intelligent car is described,the significance and actual research progress of intelligent car are clarified,the necessity and urgency of intelligent car research is fully expounded,and the research objective and content of intelligent car in this paper are clarified.Next,it describes the PID algorithm,fuzzy control model and correlation technique of smart car control.Subsequently,it focuses on the specific application of the improved PID algorithm on the smart car.The transfer function is deduced according to the parameters of the smart car.The fuzzy control model is built through the Simulink si mulation module in MATLAB and the formulated fuzzy rules.The load motor speed disturbance and the step disturbance of electromagnetic torque are simulated by fuzzy rules.The traditional PID algorithm and the improved fuzzy adaptive PID algorithm are used to compare the control experiments of smart vehicles,and then the step response performance of the motor control system is tested.These experiments show that the system improves the performance of smart car real-time control and optimization speed,the improved fuzzy PID algorithm also has a better and stable dynamic response,robustness and accuracy compared with the traditional PID algorithm.Immediately afterwards,the algorithm was specifically applied to smart cars to verify the accuracy and effecti veness of the simulation results.The system built IAR development tools and Linux operating system.The hardware system of the smart car is designed and manufactured in a modular manner.It specifically analyzes and studies some problems and deficiencies of the car body control,and proposes solutions to practice.In terms of improving speed stability and controllability,the improved fuzzy self-adaptive PID application intelligent vehicle control system is used to carry out commissioning and comparative t ests,which greatly improves the accuracy requirements of intelligent search,obstacle avoidance and speed control of intelligent vehicles.Finally,the improved smart car system overcomes the shortcomings of traditional PID algorithms that cannot adjust parameters in real time,and greatly improves the efficiency,robustness,and dynamic stability of smart car control.