高速材料拉伸机模型预测控制系统设计
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摘要
高速材料拉伸机用于测试被试件在高速拉伸条件下材料特性,电液伺服系统具有高出力、速度快的特点,因此常被应用到高速材料拉伸机系统中。但是当拉伸阶段为毫秒级别时,电液伺服阀的响应延迟问题也变得无法避免。面对这个问题,普通PID控制显得力不从心。利用系统的近似数学模型,对未来一段时间系统的输出量进行预测的模型预测控制(MPC)方法则被应用于所设计的一种基于电液伺服控制系统的高速材料拉伸机,从而对系统输出提前进行控制,有效避免了系统延迟带来的问题,对整个系统实现了实际有效的控制。
High-speed material tensile machines are used to test high-speed tensile properties of specimens. Electro-hydraulic servo system has advantages of high power output and high speed,thus it is widely used in high-speed material tensile machines. However,when it comes to milliseconds' stretch,with a inevitable delay of reponse of valves,ordinary PID control would be useless. Model predictive control( MPC)predicts a period of output in the future based on the mathematical model of system,then it could control the output in advance to avoid problems caused by high delay in system. MPC method is able to control the whole system effectively.
High-speed material tensile machines are used to test high-speed tensile properties of specimens. Electro-hydraulic servo system has advantages of high power output and high speed,thus it is widely used in high-speed material tensile machines. However,when it comes to milliseconds' stretch,with a inevitable delay of reponse of valves,ordinary PID control would be useless. Model predictive control( MPC)predicts a period of output in the future based on the mathematical model of system,then it could control the output in advance to avoid problems caused by high delay in system. MPC method is able to control the whole system effectively.
引文
[1]Jay H.Lee.Model Predictive Control:Review o the Three Decades of Development[J].International Journal of Control,Automation,and Systems2011,9(3):415-424.
[2]卢明.间隙密封式伺服液压缸密封特性研究及仿真[D].武汉:武汉科技大学,2010.
[3]韩冰.基于延迟神经网络的非线性时滞系统控制研究[D].大连:大连理工大学,2009.
[4]丛爽,邓娟.MATLAB环境下的模型预测控制理论的应用[J].计算机工程与应用,2005(16):196.
[5]佚名.模型预测控制[EB/OL].[2017-12-05]https://wenku.baidu.com/view/8e4633d519e8b8f67c1cb9fa.html.
[2]卢明.间隙密封式伺服液压缸密封特性研究及仿真[D].武汉:武汉科技大学,2010.
[3]韩冰.基于延迟神经网络的非线性时滞系统控制研究[D].大连:大连理工大学,2009.
[4]丛爽,邓娟.MATLAB环境下的模型预测控制理论的应用[J].计算机工程与应用,2005(16):196.
[5]佚名.模型预测控制[EB/OL].[2017-12-05]https://wenku.baidu.com/view/8e4633d519e8b8f67c1cb9fa.html.