用遗传算法优化机器人臂的PID参数，提升控制精度与响应速度。
Optimize the parameters of the PID Controller using Genetic Algorithm for Robot Manipulators
- 用遗传算法自动搜索最优PID参数，适应非线性系统。
- 仿真显示轨迹跟踪响应时间缩短，系统更稳定精确。
- 适合需要高精度控制的工业机器人等实际应用场景。
本文针对两自由度机器人臂设计了一种参数优化的比例-积分-微分（PID）控制器。提出一种遗传算法（GA）来优化控制器参数，解决传统方法在高度非线性系统如机器人臂中难以确定最佳参数的问题。仿真结果表明，基于遗传算法优化的PID控制器显著提升了控制精度与性能，系统运行具备高精度和稳定性。同时，轨迹跟踪响应时间明显缩短，增强了该控制算法在真实场景中的可行性。本研究不仅验证了PID-GA在机器人臂及类似系统中的适用性，也为该算法在真实物理系统中的应用开辟了新路径。
原文摘要 · Abstract (English)
This paper presents the design a Proportional-Integral-Derivative (PID) controller with optimized parameters for a two-degree-of-freedom robotic arm. A genetic algorithm (GA) is proposed to optimize the controller parameters, addressing the challenges in determining PID controller parameters for highly nonlinear systems like robotic arms compared to traditional methods. The GA-optimized PID controller significantly improves control accuracy and performance over traditional control methods. Simulation results demonstrate that the robotic arm system operates with high precision and stability. Additionally, the shortened trajectory tracking response time enhances the feasibility of applying this control algorithm in realworld scenarios. This research not only confirms the suitability of PID-GA for robotic arms and similar systems but also opens new avenues for applying this algorithm to real physical systems.
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