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| Filter-based iterative learning control for linear large-scale industrial processes | |
| 作者姓名： | Xiao' e RUAN Jianguo WANG Baiwu WAN |
| 作者单位： | [2]SchoolofScience,Xi＇anUniversityofArchitectureandTechnology,Xi＇anShaanxi710055,China [3]SysteMsEngineeringInstitute,Xi＇anJiaotongUniversity,Xi＇anShaanxi710049,China [4]FacultyofScience,Xi＇anJiaotongUniversity,Xi＇anShaanxi710049,China |
| 基金项目： | This work was supported by the National Natural Science Foundation of China (No. 60274055) |
| 摘 要： | In the procedure of the steady-state hierarchical optimization with feedback for large-scale industrial processes, a sequence of set-point changes with different magnitudes is carried out on the optimization layer. To improve the dynamic performance of transient response driven by the set-point changes, a filter-based iterative leaning control strategy is proposed. In the proposed updating law, a local-symmetric-integral operator is adopted for eliminating the measurement noise of output information, a set of desired trajectories are specified according to the set-point changes sequence, the current control input is iteratively achieved by utilizing smoothed output error to modify its control input at previous iteration, to which the amplified coefficients related to the different magnitudes of set-point changes are introduced. The convergence of the algorithm is conducted by incorporating frequency-domain technique into time-domain analysis. Numerical simulation demonstrates the effectiveness of the proposed strategy. |
| 关 键 词： | 迭代学习控制 大工业加工 线性系统 动态特性 |
| 收稿时间： | 31 August 2003 |
| 修稿时间： | 2004/3/26 0:00:00 |
Filter-based iterative learning control for linear large-scale industrial processes |
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| Xiao'' e RUAN,Jianguo WANG,Baiwu WAN.Filter-based iterative learning control for linear large-scale industrial processes[J].Journal of Control Theory and Applications,2004,2(2):149-154. | |
| Authors: | Xiao' e RUAN Jianguo WANG Baiwu WAN |
| Affiliation: | 1. Faculty of Science, Xi'an Jiaotong University, Xi' an Shaanxi 710049, China 2. School of Science, Xi'an University of Architecture and Technology, Xi'an Shaanxi 710055, China 3. Systems Engineering Institute,Xi'an Jiaotong University,Xi'an Shaanxi 710049,China |
| Abstract: | In the procedure of the steady-state hierarchical optimization with feedback for large-scale industrial processes, a sequence of set-point changes with different magnitudes is carried out on the optimization layer. To improve the dynamic performance of transient response driven by the set-point changes, a filter-based iterative learning control strategy is proposed. In the proposed updating law, a local-symmetric-integral operator is adopted for eliminating the measurement noise of output information,a set of desired trajectories are specified according to the set-point changes sequence, the current control input is iteratively achieved by utilizing smoothed output error to modify its control input at previous iteration, to which the amplified coefficients related to the different magnitudes of set-point changes are introduced. The convergence of the algorithm is conducted by incorporating frequency-domain technique into time-domain analysis. Numerical simulation demonstrates the effectiveness of the proposed strategy, |
| Keywords: | Iterative learning control Large-scale industrial processes Steady-state optimization Dynamic performance |
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