基于粒子群优化与遗传算法融合的农业机器人PID转向控制方法

PID Steering Control Method of Agricultural Robot Based on Fusion of Particle Swarm Optimization and Genetic Algorithm

摘要:

为解决农业机器人在运动过程中出现的转向不稳定和滞后问题，提出了一种粒子群优化（PSO）与遗传算法（GA）融合的PID控制方法。该融合算法利用PSO的快速优化能力，对GA的种群筛选环节进行优化。Simulink仿真结果表明，融合算法的适应度函数收敛速度加快，系统响应调整时间缩短，超调量几乎为零。随后，该算法被应用于农业机器人在不同场景下的转向测试。在对农业机器人的转向系统进行建模后，无负载悬浮状态下的转向测试结果表明，与人工试错PID控制和基于GA的PID控制相比，基于融合算法的PID控制减少了系统的上升时间、响应调整时间和超调量，提高了系统的响应速度和稳定性。实际道路转向测试结果表明，基于融合算法的PID控制响应上升时间最短，约为4.43s。当目标脉冲数设为100时，稳态调节阶段实际均值约为102.9，在3种控制方法中最为接近目标值，同时超调量也有所减小。不同场景状态下的转向测试结果表明，本研究提出的基于融合算法的PID控制具有良好的抗干扰能力，能够适应环境和负载的变化，提高控制系统的性能。该方法在农业机器人的转向控制中效果显著，为其他机器人的精确转向控制提供了参考。

Abstract:

Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement, a fusion PID control method of particle swarm optimization (PSO) and genetic algorithm (GA) was proposed. The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA. The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated, the system response adjustment time was reduced, and the overshoot was almost zero. Then the algorithm was applied to the steering test of agricultural robot in various scenes. After modeling the steering system of agricultural robot, the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time, response adjustment time and overshoot of the system, and improved the response speed and stability of the system, compared with the artificial trial and error PID control and the PID control based on GA. The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest, about 4.43s. When the target pulse number was set to 100, the actual mean value in the steady-state regulation stage was about 102.9, which was the closest to the target value among the three control methods, and the overshoot was reduced at the same time. The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability, it can adapt to the changes of environment and load and improve the performance of the control system. It was effective in the steering control of agricultural robot. This method can provide a reference for the precise steering control of other robots.