Research on the PID control of the ESP system of tractor based on improved AFSA and improved SA

The paper uses the electronic stability program (ESP) on tractors in order to improve their trafficability and steering stability. The paper builds a full-tractor model with an ESP system, as well as a steering-by-wire system based on Matlab and Carsim with the aim to research and improve the ESP system's control performance. The paper investigated the optimization and the setting method of the PID control parameters. The paper applied the speed and the position update mode of the particle swarm optimization (PSO), the probability judgment Metropolis rule of simulated annealing algorithm (SA), the non-uniform mutation idea of genetic algorithm (GA), and the custom initial swarm implantation method into the artificial fish swarm algorithm (AFSA) in order to improve the AFSA. This paper proposes a new method based on the improved AFSA and the improved SA that would simulate the artificial setting of the PID parameters. This method alters the concurrent optimization process of the PID parameters into a process that is initially serial and then becomes concurrent. The new method is then compared with the parameter setting methods based standard AFSA and the improved AFSA. The comparison results showed that the improved AFSA had a faster rate of convergence and a better precision of optimization. The new setting method for the PID parameters improved the PID's control result more effectively and enabled a tractor with an ESP system to change directions at the expected yaw velocity.