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The purpose of this work is to improve the tracking performance of the iterative learning control (ILC) by designing a new learning law that has the ability to update the input along both the time and iterative axes. First, the reference is generated by a high-order internal model (HOIM) along the iterative axis and can be approximated by an HOIM along the time axis. Then, the HOIM-based repetitive...
In the technical note, consensus tracking is studied for multi-agents system (MAS) with state time-delays. Every agent of the MAS has homogeneous dynamic function, which is described by a nonlinearly parameterized functions with unknown state time-delays. Moreover, it is assumed that the virtual leader (regarded as the desired trajectory) can be accessible to at least one agent. Based on several necessary...
Based on combination of an optimal PI type iterative learning controller and projection like adjusting algorithm, an adaptive iterative learning control scheme is presented for repetitive control of uncertain systems. This adaptive iterative learning controller is designed without any priori knowledge of system parameters. The convergence of the presented scheme is analyzed and its convergence condition...
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