Modified Algorithms of Model Reference Adaptive Robust Control for Nonlinear Objects under Uncertainty and Unknown Disturbances

The article considers the problem of synthesizing model reference adaptive robust control systems for nonlinear objects under uncertainty and unknown disturbances. To solve this problem, two approaches are proposed that allow overcoming the limitations of traditional model reference adaptive control under external disturbances. The first approach, based on modified model reference adaptive robust control, is used to compensate for the influence of uncertainty and unknown matched disturbances. The second approach, based on model reference adaptive robust sliding mode control, is used to compensate for the influence of the above-mentioned factors and unknown unmatched disturbances. The Lyapunov function method is used to prove the robustness (robust stability) of control systems. The linear matrix inequalities (LMI) method is used to calculate the parameters of adaptive robust systems. The efficiency of the proposed approaches is demonstrated by modeling in the MatLab/Simulink software environment using a numerical example of control synthesis for a second-order nonlinear system.