A new kind of volume control hydraulic press that combines the advantages of both hydraulic and SRM(switched reluctance motor) driving technology is developed.Considering that the serious dead zone and time-variant no...A new kind of volume control hydraulic press that combines the advantages of both hydraulic and SRM(switched reluctance motor) driving technology is developed.Considering that the serious dead zone and time-variant nonlinearity exist in the volume control electro-hydraulic servo system,the ILC(iterative learning control) method is applied to tracking the displacement curve of the hydraulic press slider.In order to improve the convergence speed and precision of ILC,a fuzzy ILC algorithm that utilizes the fuzzy strategy to adaptively adjust the iterative learning gains is put forward.The simulation and experimental researches are carried out to investigate the convergence speed and precision of the fuzzy ILC for hydraulic press slider position tracking.The results show that the fuzzy ILC can raise the iterative learning speed enormously,and realize the tracking control of slider displacement curve with rapid response speed and high control precision.In experiment,the maximum tracking error 0.02 V is achieved through 12 iterations only.展开更多
Mining operation, especially underground coal mining, always has the remarkable risks of ground control. Passive seismic velocity tomography based on simultaneous iterative reconstructive technique （SIRT） inversion ...Mining operation, especially underground coal mining, always has the remarkable risks of ground control. Passive seismic velocity tomography based on simultaneous iterative reconstructive technique （SIRT） inversion is used to deduce the stress redistribution around the longwall mining panel. The mining-induced microseismic events were recorded by mounting an array of receivers on the surface, above the active panel. After processing and filtering the seismic data, the three-dimensional tomography images of the p-wave velocity variations by SIRT passive seismic velocity tomography were provided. To display the velocity changes on coal seam level and subsequently to infer the stress redistribution, these three-dimensional tomograms into the coal seam level were sliced. In addition, the boundary element method （BEM） was used to simulate the stress redistribution. The results show that the inferred stresses from the passive seismic tomograms are conformed to numerical models and theoretical concept of the stress redistribution around the longwall panel. In velocity tomograms, the main zones of the stress redistribution arotmd the panel, including front and side abutment pressures, and gob stress are obvious and also the movement of stress zones along the face advancement is evident. Moreover, the effect of the advance rate of the face on the stress redistribution is demonstrated in tomography images. The research result proves that the SIRT passive seismic velocity tomography has an ultimate potential for monitoring the changes of stress redistribution around the longwall mining panel continuously and subsequently to improve safety of mining operations.展开更多
Abstract--This paper conducts a survey on iterative learn- ing control （ILC） with incomplete information and associated control system design, which is a frontier of the ILC field. The incomplete information, includ...Abstract--This paper conducts a survey on iterative learn- ing control （ILC） with incomplete information and associated control system design, which is a frontier of the ILC field. The incomplete information, including passive and active types, can cause data loss or fragment due to various factors. Passive incomplete information refers to incomplete data and information caused by practical system limitations during data collection, storage, transmission, and processing, such as data dropouts, delays, disordering, and limited transmission bandwidth. Active incomplete information refers to incomplete data and information caused by man-made reduction of data quantity and quality on the premise that the given objective is satisfied, such as sampling and quantization. This survey emphasizes two aspects： the first one is how to guarantee good learning performance and tracking performance with passive incomplete data, and the second is how to balance the control performance index and data demand by active means. The promising research directions along this topic are also addressed, where data robustness is highly emphasized. This survey is expected to improve understanding of the restrictive relationship and trade-off between incomplete data and tracking performance, quantitatively, and promote further developments of ILC theory. Index Terms--Data dropout, data robustness, incomplete in- formation, iterative learning controi（ILC）, quantized control, sampled control, varying lengths.展开更多
Based on an equivalent two-dimensional Fornasini-Marchsini model for a batch process in industry, a closed-loop robust iterative learning fault-tolerant guaranteed cost control scheme is proposed for batch processes w...Based on an equivalent two-dimensional Fornasini-Marchsini model for a batch process in industry, a closed-loop robust iterative learning fault-tolerant guaranteed cost control scheme is proposed for batch processes with actuator failures. This paper introduces relevant concepts of the fault-tolerant guaranteed cost control and formulates the robust iterative learning reliable guaranteed cost controller (ILRGCC). A significant advantage is that the proposed ILRGCC design method can be used for on-line optimization against batch-to-batch process uncertainties to realize robust tracking of set-point trajectory in time and batch-to-batch sequences. For the convenience of implementation, only measured output errors of current and previous cycles are used to design a synthetic controller for iterative learning control, consisting of dynamic output feedback plus feed-forward control. The proposed controller can not only guarantee the closed-loop convergency along time and cycle sequences but also satisfy the H∞performance level and a cost function with upper bounds for all admissible uncertainties and any actuator failures. Sufficient conditions for the controller solution are derived in terms of linear matrix inequalities (LMIs), and design procedures, which formulate a convex optimization problem with LMI constraints, are presented. An example of injection molding is given to illustrate the effectiveness and advantages of the ILRGCC design approach.展开更多
基金Project(2007AA04Z144) supported by the National High-Tech Research and Development Program of ChinaProject(2007421119) supported by the China Postdoctoral Science Foundation
文摘A new kind of volume control hydraulic press that combines the advantages of both hydraulic and SRM(switched reluctance motor) driving technology is developed.Considering that the serious dead zone and time-variant nonlinearity exist in the volume control electro-hydraulic servo system,the ILC(iterative learning control) method is applied to tracking the displacement curve of the hydraulic press slider.In order to improve the convergence speed and precision of ILC,a fuzzy ILC algorithm that utilizes the fuzzy strategy to adaptively adjust the iterative learning gains is put forward.The simulation and experimental researches are carried out to investigate the convergence speed and precision of the fuzzy ILC for hydraulic press slider position tracking.The results show that the fuzzy ILC can raise the iterative learning speed enormously,and realize the tracking control of slider displacement curve with rapid response speed and high control precision.In experiment,the maximum tracking error 0.02 V is achieved through 12 iterations only.
基金supported in part by National Natural Science Foundation of China(61533017,61273140,61304079,61374105,61379099,61233001)Fundamental Research Funds for the Central Universities(FRF-TP-15-056A3)the Open Research Project from SKLMCCS(20150104)
文摘Mining operation, especially underground coal mining, always has the remarkable risks of ground control. Passive seismic velocity tomography based on simultaneous iterative reconstructive technique （SIRT） inversion is used to deduce the stress redistribution around the longwall mining panel. The mining-induced microseismic events were recorded by mounting an array of receivers on the surface, above the active panel. After processing and filtering the seismic data, the three-dimensional tomography images of the p-wave velocity variations by SIRT passive seismic velocity tomography were provided. To display the velocity changes on coal seam level and subsequently to infer the stress redistribution, these three-dimensional tomograms into the coal seam level were sliced. In addition, the boundary element method （BEM） was used to simulate the stress redistribution. The results show that the inferred stresses from the passive seismic tomograms are conformed to numerical models and theoretical concept of the stress redistribution around the longwall panel. In velocity tomograms, the main zones of the stress redistribution arotmd the panel, including front and side abutment pressures, and gob stress are obvious and also the movement of stress zones along the face advancement is evident. Moreover, the effect of the advance rate of the face on the stress redistribution is demonstrated in tomography images. The research result proves that the SIRT passive seismic velocity tomography has an ultimate potential for monitoring the changes of stress redistribution around the longwall mining panel continuously and subsequently to improve safety of mining operations.
基金supported by the National Natural Science Foundation of China(61673045)Beijing Natural Science Foundation(4152040)
文摘Abstract--This paper conducts a survey on iterative learn- ing control （ILC） with incomplete information and associated control system design, which is a frontier of the ILC field. The incomplete information, including passive and active types, can cause data loss or fragment due to various factors. Passive incomplete information refers to incomplete data and information caused by practical system limitations during data collection, storage, transmission, and processing, such as data dropouts, delays, disordering, and limited transmission bandwidth. Active incomplete information refers to incomplete data and information caused by man-made reduction of data quantity and quality on the premise that the given objective is satisfied, such as sampling and quantization. This survey emphasizes two aspects： the first one is how to guarantee good learning performance and tracking performance with passive incomplete data, and the second is how to balance the control performance index and data demand by active means. The promising research directions along this topic are also addressed, where data robustness is highly emphasized. This survey is expected to improve understanding of the restrictive relationship and trade-off between incomplete data and tracking performance, quantitatively, and promote further developments of ILC theory. Index Terms--Data dropout, data robustness, incomplete in- formation, iterative learning controi（ILC）, quantized control, sampled control, varying lengths.
基金Supported in part by NSFC/RGC joint Research Scheme （N-HKUST639/09）, the National Natural Science Foundation of China （61104058, 61273101）, Guangzhou Scientific and Technological Project （2012J5100032）, Nansha district independent innovation project （201103003）, China Postdoctoral Science Foundation （2012M511367, 2012M511368）, and Doctor Scientific Research Foundation of Liaoning Province （20121046）.
文摘Based on an equivalent two-dimensional Fornasini-Marchsini model for a batch process in industry, a closed-loop robust iterative learning fault-tolerant guaranteed cost control scheme is proposed for batch processes with actuator failures. This paper introduces relevant concepts of the fault-tolerant guaranteed cost control and formulates the robust iterative learning reliable guaranteed cost controller (ILRGCC). A significant advantage is that the proposed ILRGCC design method can be used for on-line optimization against batch-to-batch process uncertainties to realize robust tracking of set-point trajectory in time and batch-to-batch sequences. For the convenience of implementation, only measured output errors of current and previous cycles are used to design a synthetic controller for iterative learning control, consisting of dynamic output feedback plus feed-forward control. The proposed controller can not only guarantee the closed-loop convergency along time and cycle sequences but also satisfy the H∞performance level and a cost function with upper bounds for all admissible uncertainties and any actuator failures. Sufficient conditions for the controller solution are derived in terms of linear matrix inequalities (LMIs), and design procedures, which formulate a convex optimization problem with LMI constraints, are presented. An example of injection molding is given to illustrate the effectiveness and advantages of the ILRGCC design approach.
