摘要
随着工业领域的不断发展,桥式起重机在物料搬运等方面发挥着至关重要的作用。然而,其负载运动轨迹的精确控制是当前研究的问题之一。对此,提出了桥式起重机负载运动轨迹反向传播比例积分微分(BP-PID)控制优化方法。构建出了桥式起重机平面模型,推导其运动学方程式。结合反向传播(BP)神经网络和比例积分微分(PID)控制技术,利用BP神经网络强大的非线性映射能力和自学习能力,并根据学习结果实时优化PID控制器的参数。采用人工蜂群算法和差分进化算法对BP-PID控制方法进行优化,从而快速地搜索到最优控制参数。运用Matlab软件对桥式起重机负载运动轨迹展开仿真操作,与优化前输出结果实施对比分析。结果表明:采用混合算法优化BP-PID控制方法,在减小轨迹跟踪误差方面表现出色,能使桥式起重机负载运动轨迹更加符合预期,提升了系统的控制精度和稳定性。
With the continuous development of the industrial field,bridge cranes play a crucial role in material handling and other aspects.However,precise control of its load motion trajectory is one of the current research issues.A BP-PID control optimization method for load motion trajectory of bridge cranes is proposed.Constructed a planar model of the overhead crane and derived its kinematic equations.The BP neural network and PID control technology are referenced,utilizing the powerful nonlinear mapping and self-learning capabilities of the BP neural network,and optimizing the parameters of the PID controller in real time based on the learning results.Using artificial bee colony algorithm and differential evolution algorithm to optimize the BP-PID control method,in order to quickly search for the optimal control parameters.Using Matlab software to simulate the load motion trajectory of an overhead crane,and conducting comparative analysis with the output results before optimization.The results show that using a hybrid algorithm to optimize the BP-PID control method performs well in reducing trajectory tracking errors,making the load motion trajectory of the overhead crane more in line with expectations,and improving the control accuracy and stability of the system.
作者
岑华
崔治
CEN Hua;CUI Zhi(School of Electromechanical Engineering,Guangxi Modern Polytechnic College,Hechi 547000,Guangxi,China;School of Electromechanical Engineering,Guilin Aerospace Institute of Technology,Guilin 541000,Guangxi,China)
出处
《中国工程机械学报》
北大核心
2025年第5期753-757,789,共6页
Chinese Journal of Construction Machinery
基金
国家自然科学基金资助项目(62241304)
广西高校中青年教师科研基础能力提升资助项目(2024KY1484)。
关键词
混合算法
桥式起重机
BP-PID控制
误差
仿真
hybrid algorithm
bridge crane
back propagation proportional integral derivative(BPPID)control
error
simulation
