Based on the periodically forced dynamic qualities of the blood circulation system, this paper considered from network and hemodynamics, establishes plane structure diagram of the cerebral circulation. According to the electric circuit graph theory and blood dynamics equation, applies the averaging method to find an approximate solution of this equation. We apply this method in the cerebrovascular network that may help to explain the development processes of venous diseases. Simulation shows that computing result is consistent with blood flow change phenomenon of the clinical observation cerebral infarction.
In this paper, an adaptive iterative learning control is presented for robot manipulators with unknown parameters, performing repetitive tasks. In order to overcome the initial resetting errors, an auxiliary tracking error function is introduced. The adaptive algorithm is derived along the iteration axis to search for suitable parameter values. The technical analysis shows convergence of the tracking errors. Finally, simulation results are provided to illustrate the effectiveness of the proposed controller.
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