Abstract. 

In modern control theory, one of the open problems is the construction of adaptive control  for nonlinear systems with parametric uncertainty and the analysis of the stability of the corresponding  closed system. One of the approaches that can take into account the nonlinearity and uncertainty of the  control object is fuzzy logic. Affine systems are a class of nonlinear systems whose representatives are  often found in various practical problems. For this class, there are a number of developed methods for  the synthesis of regulators, in particular, a method based on the Riccati equation with state-dependent  coefficients. In this paper, for a given class of nonlinear systems, the adaptation mechanism of a neuro  fuzzy controller approximating the control obtained using the SDRE approach is applied for the first  time. The main results of the work are the architecture of the neuro fuzzy network, as well as methods  of its initialization. The proposed approach is applied to the model of a two-link manipulator with  uncertain coefficients. Numerical experiments have shown the effectiveness of the obtained control  according to the totality of the quality criteria considered. 

Keywords: 

state-dependent riccati equation, adaptive control, fuzzy control, two-link robot. 

PP. 60-71.

DOI 10.14357/20718632220108 

 

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