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In this technical note, an additive-state-decomposition-based iterative learning control (ILC) method is proposed. Based on this method, the output feedback ILC problem is solved for a class of nonminimum phase (NMP) nonlinear systems with input saturation. This method is to “additively” decompose the output feedback ILC problem into two more tractable subproblems, namely an output feedback ILC problem...
In this paper, a new concept of iterative learning control (ILC), namely consolidated ILC (CILC), is introduced. An iterative learning control system is subject to data interrupt when the system output is restricted within a certain area. Data interrupt means that the system output is interrupted at a certain moment due to output restrictions. The output data from this moment to the end of the trail...
In order to remove the noise of the traction machine and the steel wire rope effectively and protect the details of the image better, the image denoising method based on an improved Contourlet are proposed, which considers the non-independence among Contourlet coefficients fully in denoising process. The traditional image denoising methods of Contourlet coefficients are obtained by Contourlet transform,...
This paper considers a multi-cell OFDMA downlink system with several decode-and-forward (DF) relay stations (RSs) aiding the base station (BS) transmissions. The opportunistic DF protocol proposed in [1] is applied. The problem considered is the maximization of the system sum rate with a total power constraint in each cell. An iterative low-complexity resource allocation (RA) algorithm is proposed...
This paper considers a multi-cell relay aided orthogonal frequency division multiple access (OFDMA) downlink system, in which all stations are coordinated by a central controller for resource allocation (RA). The decode-and-forward (DF) protocol with selection relaying (SR) is applied. The problem considered is the maximization of the weighted sum of per cell min-rate (WSMR) with a total power constraint...
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