嵌入式实时以太网运动控制器设计与性能测评
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摘要
针对标准以太网应用到运动控制领域存在的非确定网络延时问题,提出确定性调度配合延时补偿的方法提高系统性能。利用卡尔曼滤波算法提高时间同步精度,采用时隙划分调度策略保证数据交换的确定性,通过RBF (radial basis function)模糊神经网络PID算法对系统延时预测值进行补偿,使系统能跟随延时自适应调整,具有高精度多轴同步运动的能力。实验结果表明,卡尔曼滤波将时钟偏移标准差由11.6μs降至7.9μs,有效提高了同步精度,基于延时预测并补偿的控制算法比传统PID算法具有更短的响应时间,更高的稳态性能和同步跟随性能。
Aiming at the problem that Ethernet used in the field of motion control leads to non-deterministic network delay,a method combining deterministic scheduling with delay compensation was presented to improve system performance.The accuracy of time synchronization was improved using Kalman filter algorithm.The time-slot division scheduling strategy was used to guarantee the certainty of data exchange,and the PID algorithm based on radial basis function fuzzy neural network was proposed to compensate the delay prediction value of system,so that the system could implement adaptive adjustment following the delay,with the performance of high precision multi-axis synchronous motion.The results of experiments indicate that the Kalman filter algorithm can reduce the standard deviation of clock offset from 11.6μs to 7.9μs,and effectively improve the time synchronization accuracy.The control algorithm based on delay prediction and compensation has shorter response time,better steady-state performance and synchronous following performance than traditional PID algorithm.
Aiming at the problem that Ethernet used in the field of motion control leads to non-deterministic network delay,a method combining deterministic scheduling with delay compensation was presented to improve system performance.The accuracy of time synchronization was improved using Kalman filter algorithm.The time-slot division scheduling strategy was used to guarantee the certainty of data exchange,and the PID algorithm based on radial basis function fuzzy neural network was proposed to compensate the delay prediction value of system,so that the system could implement adaptive adjustment following the delay,with the performance of high precision multi-axis synchronous motion.The results of experiments indicate that the Kalman filter algorithm can reduce the standard deviation of clock offset from 11.6μs to 7.9μs,and effectively improve the time synchronization accuracy.The control algorithm based on delay prediction and compensation has shorter response time,better steady-state performance and synchronous following performance than traditional PID algorithm.
引文
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[6]Fan Z,Liu Y,Li H,et al.A servo design for slave clock in IEEE 1588synchronization networks[J].International Journal of Communication Systems,2015,28(4):615-624.
[7]ZUO Tao,MIN Huasong,ZHANG Xiongxi.Control system of robot based on bus of real-time Ethernet[J].Computer Engineering and Design,2016,37(5):1140-1144(in Chinese).[左韬,闵华松,张雄希.基于实时以太网的机器人通信总线控制系统[J].计算机工程与设计,2016,37(5):1140-1144.]
[8]YU Xiaoming,JIANG Jingping.Adaptive networked control system based on delay prediction using neural network[J].Journal of Zhejiang University(Engineering Science),2012,46(2):194-198(in Chinese).[于晓明,蒋静坪.基于神经网络延时预测的自适应网络控制系统[J].浙江大学学报(工学版),2012,46(2):194-198.]
[9]SHI Weiguo,SHAO Cheng,SUN Zhengyang.Improved GPC network-control algorithm based on AR model time-delay prediction[J].Control and Decision,2012,27(3):477-480(in Chinese).[时维国,邵诚,孙正阳.基于AR模型时延预测的改进GPC网络控制算法[J].控制与决策,2012,27(3):477-480.]
[10]CHEN Zaiping,WANG Xue.Predictive control of networked control systems random delay[J].Computer Simulation,2014,31(9):327-330(in Chinese).[陈在平,王雪.网络控制系统随机延迟的预测控制[J].计算机仿真,2014,31(9):327-330.]
[11]HAO Xiaoxing, WANG Xuping.Design of electro-hydraulic servo control system based on FPGA and fuzzy PID[J].Computer Engineering and Design,2014,35(7):2350-2355(in Chinese).[郝小星,王旭平.基于FPGA和模糊PID的电液伺服控制系统设计[J].计算机工程与设计,2014,35(7):2350-2355.]
[12]El-Sousy FFM.Adaptive hybrid control system using a recurrent RBFN-based self-evolving fuzzy-neural-network for PMSM servo drives[J].Applied Soft Computing,2014,21(2):509-532.
[13]Sang Y,Li F,Dai Y,et al.The practical control technology design for AC servo motor based on STM32 micro-controller[C]//Advanced Information Technology,Electronic and Automation Control Conference.IEEE,2016:1-5.