Synthesis and Initialization of Adaptive Neuro-Fuzzy Control Based on the SDRE Technique for a Two-Link Manipulator

One of the open problems in modern control theory is synthesis of adaptive control for nonlinear systems with parametric uncertainty and analysis of stability of the corresponding closed-loop system. Fuzzy logic is one of the approaches that can take into account nonlinearity and uncertainty of the...

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Bibliographic Details
Published in:Programming and computer software 2023-12, Vol.49 (Suppl 2), p.S91-S98
Main Authors: Makarov, D. A., Puzach, V. A.
Format: Article
Language:English
Subjects:
Adaptation
Adaptive control
Approximation
Artificial Intelligence
Artificial neural networks
Closed loop systems
Closed loops
Computer Science
Control theory
Controllers
Feedback
Feedback control
Fuzzy control
Fuzzy logic
Fuzzy sets
Fuzzy systems
Manipulators
Nonlinear control
Nonlinear systems
Nonlinearity
Operating Systems
Riccati equation
Software Engineering
Software Engineering/Programming and Operating Systems
Stability analysis
Synthesis
Uncertainty
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Summary:One of the open problems in modern control theory is synthesis of adaptive control for nonlinear systems with parametric uncertainty and analysis of stability of the corresponding closed-loop system. Fuzzy logic is one of the approaches that can take into account nonlinearity and uncertainty of the plant. Affine systems constitute a class of nonlinear systems often used to solve various practical problems. For this class, there are a number of methods for synthesis of controllers, in particular, a method based on the matrix Riccati equation with state-dependent coefficients. In this paper, for a given class of nonlinear systems, an adaptation mechanism of a neuro-fuzzy controller that approximates the control synthesized by the SDRE method is used for the first time. The main contribution of this work is the architecture of the neuro-fuzzy network and methods for its initialization. The proposed approach is applied to the model of a two-link manipulator with uncertain coefficients. The conducted numerical experiments demonstrate the effectiveness of the synthesized control in terms of the selected quality criteria.
ISSN:0361-7688
1608-3261
DOI:10.1134/S0361768823100031