Simulation research on PID control of new trailing arm active suspension based on genetic algorithm optimization

A new type of trailing active arm suspension is proposed, which adopts additional power source control and actively adjusts the body height through the motor's output torque to adapt to different road conditions. The purpose is to solve the problem that wheeled robots have poor ability to overcome obstacles and cannot maintain high efficiency on complex roads. At the same time, a PID control strategy optimized by the genetic algorithm is proposed, which is compared with the fuzzy PID algorithm, and the optimization effect is verified by co-simulation research with AMESim and Simulink. Firstly, the main structure and control method of trailing arm suspension is introduced, and the theoretical model is established according to its body height adjustment system. Secondly, the advantages and feasibility of genetic algorithms are analyzed. Finally, the optimization effect curve is obtained through co-simulation. The research results show that the PID control strategy optimized by the genetic algorithm can obviously reduce the fluctuation of the body height adjustment, and the optimization effect is better than that of the fuzzy PID control.