【摘要】 液压挖掘机的控制系统具有非线性、时变性以及强耦合的特点，传统的比例积分微分(Proportion integral differential, PID)控制器参数整定方法不能满足对挖掘机工作装置精确的位置控制要求。因此提出一种遗传萤火虫算法(Genetic Firefly Algorithm, GFA)整定方法，通过对目标函数、选择算子、交叉算子等改进之后再引入人工萤火虫算法来提高遗传算法的全局寻优能力和收敛速度。利用MATLAB仿真软件进行仿真，并分别与标准PID控制和标准遗传算法进行比较。仿真结果表明，基于GFA的控制系统具有较快的响应速度、无超调量、更强的鲁棒性以及较小的铲斗关节轨迹跟踪误差。所提算法具有更好的参数整定能力，改善了系统性能，可用于提高液压挖掘机铲斗位置控制的效果。更多还原

【Abstract】 The control system of hydraulic excavator has the characteristics of non-linear, time-varying and strong coupling, and traditional Proportion integral differential(PID) controller parameter setting method cannot meet the requirement of precise position control of excavator working device. Therefore, a Genetic Firefly Algorithm(GFA) tuning method is proposed to improve the global optimization ability and convergence speed of the Genetic Algorithm by introducing artificial Firefly Algorithm after improving the objective function, selection operator and crossover operator. MATLAB simulation software was used to carry out simulation experiments, and compared with the standard PID control and the standard genetic algorithm. The simulation results show that the control system based on GFA has a faster response speed, no overshoot, stronger robustness, and smaller tracking error of the bucket joint. The proposed algorithm has better parameter setting ability, improves system performance, and can be used to improve the effect of bucket position control of hydraulic excavator.更多还原