From Zhang neural network to Newton iteration for matrix inversion
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Neural Computing and Applications
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Recently, Zhang dynamics (ZD) and gradient dynamics (GD) have been used frequently to solve various kinds of online problems. In this paper, the output tracking of time-varying linear (TVL) systems is considered. Then, for such a problem, three different types of tracking controllers (i.e., Z0G0, Z1G0 and Z1G1 controllers) are designed by exploiting the ZD and GD methods. Simulation results on different TVL systems show that such three types of controllers can be feasible and effective for the output-tracking problem solving. Especially, the Z1G1 controller is capable of conquering the control-singularity of systems.