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The paper presents an approach to design a control of nonlinear dynamical systems based on the extended linearization technique of a mathematical model of an object such that a given quadratic cost function is minimized. In this case, the coefficients of the nonlinear controller are determined by solving Riccati matrix equation with state dependent parameters. A realizability problem of the controller of this sort is computational complexity of the realtime solution. The proposed approach solves the problem by controller coefficients searching at each control time subinterval of the whole control time interval. The presented methodology is illustrated by designing chemotherapy administration for the cancer treatment. The mathematical model of the cancer growth includes interaction between tumor cells, healthy normal cells and activated immune cells. Numerical results show effectiveness of the solutions obtained.