New feedback control techniques of quaternion fuzzy neural networks with time‐varying delay
Chaouki Aouiti, Hediene Jallouli
Abstract
Abstract This article addresses the problems of fixed‐time stabilization for a class of quaternion fuzzy neural networks (QFNNs) with time‐varying delay. The QFNNs are developed by dividing our system into four real‐valued parts based on the Hamilton rule. Then, based on fixed‐time stability theory, some inequality techniques, and selecting the appropriate controllers and Lyapunov function, a novel criterion guaranteeing the fixed‐time stabilization and the finite‐time stabilization of the addressed system is derived. Finally, three numerical examples are presented to show the effectiveness of our theoretical results.
Topics & Concepts
QuaternionControl theory (sociology)Lyapunov functionArtificial neural networkFuzzy logicClass (philosophy)Fuzzy control systemStability (learning theory)Computer scienceMathematicsControl (management)Nonlinear systemArtificial intelligenceMachine learningGeometryPhysicsQuantum mechanicsNeural Networks Stability and SynchronizationElasticity and Wave PropagationNeural Networks and Applications