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作 者:Naser Alajmi Ali Alobaidly Mubarak Alhajri Salem Salamah Muhammad Alsubaie
机构地区:[1]Industrial Institute of Sabah Alsalem, PAAET, Kuwait, Kuwait [2]Vocational Training Institute, PAAET, Kuwait, Kuwait [3]Department of Electronics Engineering, College of Technological Studies, PAAET, Kuwait, Kuwait
出 处:《Intelligent Control and Automation》2017年第3期154-163,共10页智能控制与自动化(英文)
摘 要:Selecting a proper initial input for Iterative Learning Control (ILC) algorithms has been shown to offer faster learning speed compared to the same theories if a system starts from blind. Iterative Learning Control is a control technique that uses previous successive projections to update the following execution/trial input such that a reference is followed to a high precision. In ILC, convergence of the error is generally highly dependent on the initial choice of input applied to the plant, thus a good choice of initial start would make learning faster and as a consequence the error tends to zero faster as well. Here in this paper, an upper limit to the initial choice construction for the input signal for trial 1 is set such that the system would not tend to respond aggressively due to the uncertainty that lies in high frequencies. The provided limit is found in term of singular values and simulation results obtained illustrate the theory behind.Selecting a proper initial input for Iterative Learning Control (ILC) algorithms has been shown to offer faster learning speed compared to the same theories if a system starts from blind. Iterative Learning Control is a control technique that uses previous successive projections to update the following execution/trial input such that a reference is followed to a high precision. In ILC, convergence of the error is generally highly dependent on the initial choice of input applied to the plant, thus a good choice of initial start would make learning faster and as a consequence the error tends to zero faster as well. Here in this paper, an upper limit to the initial choice construction for the input signal for trial 1 is set such that the system would not tend to respond aggressively due to the uncertainty that lies in high frequencies. The provided limit is found in term of singular values and simulation results obtained illustrate the theory behind.
关 键 词:ITERATIVE Learning Control INITIAL INPUT Selection SINGULAR VALUES
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