针对目前汽车装配监视生产线仍需人工作业、工作步骤繁琐以及效率不高的情况,设计了基于西门子S7-1200 PLC和西克射频识别(Radio Frequency Identification,RFID)技术的装配监视追溯系统。详细介绍了该系统的基本结构,系统实现了生产现...针对目前汽车装配监视生产线仍需人工作业、工作步骤繁琐以及效率不高的情况,设计了基于西门子S7-1200 PLC和西克射频识别(Radio Frequency Identification,RFID)技术的装配监视追溯系统。详细介绍了该系统的基本结构,系统实现了生产现场自动采集和写入仪表信息,上位机集中监视现场装配状况,同时将数据库中的仪表信息接入汽车厂制造企业生产过程执行管理系统(Manufacturing Process Execution Management System,MES),为汽车零/部件追溯和故障召回提供数据支持。该系统已在长春某汽车厂正式投入使用6个月,实践应用表明,该系统提高了工作效率,运行平稳,采集仪表底盘号成功率在99%以上,取得了良好的预期效果。展开更多
Two general approaches are adopted in solving dynamic optimization problems in chemical processes, namely, the analytical and numerical methods. The numerical method, which is based on heuristic algorithms, has been w...Two general approaches are adopted in solving dynamic optimization problems in chemical processes, namely, the analytical and numerical methods. The numerical method, which is based on heuristic algorithms, has been widely used. An approach that combines differential evolution （DE） algorithm and control vector parameteri- zation （CVP） is proposed in this paper. In the proposed CVP, control variables are approximated with polynomials based on state variables and time in the entire time interval. Region reduction strategy is used in DE to reduce the width of the search region, which improves the computing efficiency. The results of the case studies demonstrate the feasibility and efficiency of the oroposed methods.展开更多
An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong ...An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong disturbances to the continuous processes and traditional regulatory controllers are unable to eliminate these periodic disturbances. ILMPC integrates the feature of iterative learning control （ILC） handling repetitive signal and the flexibility of model predictive control （MPC）. By on-line monitoring the operation status of batch processes, an event-driven iterative learning algorithm for batch repetitive disturbances is initiated and the soft constraints are adjusted timely as the feasible region is away from the desired operating zone. The results of an industrial application show that the proposed ILMPC method is effective for a class of continuous/batch processes.展开更多
Many chemical processes can be modeled as Wiener models, which consist of a linear dynamic subsystem followed by a static nonlinear block. In this paper, an effective discrete-time adaptive control method is proposed ...Many chemical processes can be modeled as Wiener models, which consist of a linear dynamic subsystem followed by a static nonlinear block. In this paper, an effective discrete-time adaptive control method is proposed for Wiener nonlinear systems with uncertainties. The parameterization model is derived based on the inverse of the nonlinear function block. The adaptive control method is motivated by self-tuning control and is derived from a modified Clarke criterion function, which considers both tracking properties and control efforts. The uncertain parameters are updated by a recursive least squares algorithm and the control law exhibits an explicit form. The closed-loop system stability properties are discussed. To demonstrate the effectiveness of the obtained results, two groups of simulation examples including an application to composition control in a continuously stirred tank reactor(CSTR) system are studied.展开更多
To overcome the large time-delay in measuring the hardness of mixed rubber, rheological parameters were used to predict the hardness. A novel Q-based model updating strategy was proposed as a universal platform to tra...To overcome the large time-delay in measuring the hardness of mixed rubber, rheological parameters were used to predict the hardness. A novel Q-based model updating strategy was proposed as a universal platform to track time-varying properties. Using a few selected support samples to update the model, the strategy could dramat- ically save the storage cost and overcome the adverse influence of low signal-to-noise ratio samples. Moreover, it could be applied to any statistical process monitoring system without drastic changes to them, which is practical for industrial practices. As examples, the Q-based strategy was integrated with three popular algorithms （partial least squares （PIE）, recursive PIE （RPLS）, and kernel PIE （KPIE）） to form novel regression ones, QPLS, QRPIE and QKPLS, respectively. The applications for predicting mixed rubber hardness on a large-scale tire plant in east China prove the theoretical considerations.展开更多
文摘针对目前汽车装配监视生产线仍需人工作业、工作步骤繁琐以及效率不高的情况,设计了基于西门子S7-1200 PLC和西克射频识别(Radio Frequency Identification,RFID)技术的装配监视追溯系统。详细介绍了该系统的基本结构,系统实现了生产现场自动采集和写入仪表信息,上位机集中监视现场装配状况,同时将数据库中的仪表信息接入汽车厂制造企业生产过程执行管理系统(Manufacturing Process Execution Management System,MES),为汽车零/部件追溯和故障召回提供数据支持。该系统已在长春某汽车厂正式投入使用6个月,实践应用表明,该系统提高了工作效率,运行平稳,采集仪表底盘号成功率在99%以上,取得了良好的预期效果。
基金Supported by the Major State Basic Research Development Program of China(2012CB720500)the National Natural Science Foundation of China(Key Program:U1162202)+2 种基金the National Science Fund for Outstanding Young Scholars(61222303)the National Natural Science Foundation of China(61174118,21206037)Shanghai Leading Academic Discipline Project(B504)
文摘Two general approaches are adopted in solving dynamic optimization problems in chemical processes, namely, the analytical and numerical methods. The numerical method, which is based on heuristic algorithms, has been widely used. An approach that combines differential evolution （DE） algorithm and control vector parameteri- zation （CVP） is proposed in this paper. In the proposed CVP, control variables are approximated with polynomials based on state variables and time in the entire time interval. Region reduction strategy is used in DE to reduce the width of the search region, which improves the computing efficiency. The results of the case studies demonstrate the feasibility and efficiency of the oroposed methods.
基金Supported by the National Creative Research Groups Science Foundation of China （60721062） and the National High Technology Research and Development Program of China （2007AA04Z162）.
文摘An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong disturbances to the continuous processes and traditional regulatory controllers are unable to eliminate these periodic disturbances. ILMPC integrates the feature of iterative learning control （ILC） handling repetitive signal and the flexibility of model predictive control （MPC）. By on-line monitoring the operation status of batch processes, an event-driven iterative learning algorithm for batch repetitive disturbances is initiated and the soft constraints are adjusted timely as the feasible region is away from the desired operating zone. The results of an industrial application show that the proposed ILMPC method is effective for a class of continuous/batch processes.
基金Supported by the National Natural Science Foundation of China(61473072)
文摘Many chemical processes can be modeled as Wiener models, which consist of a linear dynamic subsystem followed by a static nonlinear block. In this paper, an effective discrete-time adaptive control method is proposed for Wiener nonlinear systems with uncertainties. The parameterization model is derived based on the inverse of the nonlinear function block. The adaptive control method is motivated by self-tuning control and is derived from a modified Clarke criterion function, which considers both tracking properties and control efforts. The uncertain parameters are updated by a recursive least squares algorithm and the control law exhibits an explicit form. The closed-loop system stability properties are discussed. To demonstrate the effectiveness of the obtained results, two groups of simulation examples including an application to composition control in a continuously stirred tank reactor(CSTR) system are studied.
文摘To overcome the large time-delay in measuring the hardness of mixed rubber, rheological parameters were used to predict the hardness. A novel Q-based model updating strategy was proposed as a universal platform to track time-varying properties. Using a few selected support samples to update the model, the strategy could dramat- ically save the storage cost and overcome the adverse influence of low signal-to-noise ratio samples. Moreover, it could be applied to any statistical process monitoring system without drastic changes to them, which is practical for industrial practices. As examples, the Q-based strategy was integrated with three popular algorithms （partial least squares （PIE）, recursive PIE （RPLS）, and kernel PIE （KPIE）） to form novel regression ones, QPLS, QRPIE and QKPLS, respectively. The applications for predicting mixed rubber hardness on a large-scale tire plant in east China prove the theoretical considerations.
