Abstract
The paper suggests a new approach to Model Reference Adaptive Control (MRAC) design for stabilization of a class of uncertain nonlinear systems. The proposed MRAC design methodology is based upon a stable nonlinear reference model which is produced by a state feedback controller using the so-called State Dependent Riccati Equation (SDRE) techniques. Based on states of the reference model, the designed stabilizer for the nonlinear reference model is then adapted for the nonlinear plant dynamics with a suitable adaptation mechanism, again by using the SDRE methodology. The proposed technique is illustrated to develop an optimal chemotherapy drug administration for cancer treatment using a tumor growth mathematical model. Simulation results show the effectiveness of the proposed SDRE-based MRAC method for the stabilization of nonlinear systems.
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