基于路面辨识和改进PID控制的电缆收放车防滑处理技术

Anti-skid treatment of cable retracting vehicle based on road identification and improved PID control

为研究电缆收放车在复杂路面环境的防滑性能,基于路面附着系数与滑转率的关系,提出了基于模糊C均值聚类算法的路面辨识方法,通过聚类中心样本最佳滑转率与隶属度的加权得到实时路面的最佳滑转率,并且对实时运行数据进行存储和迭代聚类,形成历史经验知识库;然后,基于广泛应用的传统PID控制转矩方法,将实时滑转率与最佳滑转率的偏差作为控制变量,提出变速积分和前馈补偿结合的PID控制方法对电机输出转矩进行控制,提高控制系统的速度和跟踪性能。最后,基于电缆收放车防滑试验,验证本文方法的有效性和优势,结果表明,聚类算法的迭代存储形成的经验知识库对于路面辨识的工程实践更加适用,而改进的PID控制系统相较传统PID控制速度更快,跟踪性能更好。

In order to study the anti-skid performance of cable retracting vehicle in complex pavement environment,this paper proposed a pavement identification method based on fuzzy C-means clustering algorithm based on the relationship between pavement adhesion coefficient and slip rate.The optimal slip rate of real-time pavement was obtained by weighting the optimal slip rate and membership degree of clustering center samples,and the real-time running data were stored and iterably clustered.Forming a knowledge base of historical experience;Then,based on the widely used traditional PID torque control method,taking the deviation between real-time slip rate and optimal slip rate as the control variable,a PID control method combining variable speed integral and feedforward compensation was proposed to control the output torque of the motor,and improve the speed and tracking performance of the control system.Finally,based on the antiskid test of cable retracting vehicle,the effectiveness and advantages of the proposed method are verified.The results show that the experience knowledge base formed by the iterative storage of clustering algorithm is more applicable to the engineering practice of pavement identification,and the improved PID control system has higher speed and better tracking performance than the traditional PID control system.