Adaptive Neural Network Synchronization Control for Uncertain Fractional-Order Time-Delay Chaotic Systems
Wenhao Yan, Zijing Jiang, Xin Huang, Qun Ding
Abstract
We propose an adaptive radial basis (RBF) neural network controller based on Lyapunov stability theory for uncertain fractional-order time-delay chaotic systems (FOTDCSs) with different time delays. The controller does not depend on the system model and can achieve synchronous control under the condition that nonlinear uncertainties and external disturbances are completely unknown. Stability analysis showed that the error system asymptotically tended to zero in combination with the relevant lemma. Numerical simulation results show the effectiveness of the controller.
Topics & Concepts
Control theory (sociology)Controller (irrigation)Synchronization (alternating current)Lyapunov stabilityLemma (botany)Artificial neural networkComputer scienceNonlinear systemAdaptive controlStability theoryChaoticStability (learning theory)MathematicsControl (management)Artificial intelligencePoaceaeComputer networkChannel (broadcasting)EcologyQuantum mechanicsMachine learningPhysicsBiologyAgronomyChaos control and synchronizationNeural Networks Stability and SynchronizationNeural Networks and Applications