In this paper, a novel H∞-based adaptive fuzzy control is presented for the synchronization of fractional-order chaotic
systems. A self-evolving nonsingleton type-2 fuzzy neural network
(SE-NST2FNN) is proposed for the estimation of the unknown
functions in the dynamics of the system. The effects of the approximation error and the external disturbances are eliminated by
designing an adaptive compensator, such that the H∞ norm of the
synchronization error is minimized and asymptotically stability is
achieved. The consequent parameters of SE-NST2FNN are tuned
based on the adaptation laws that are derived from Lyapunov
stability analysis. The antecedent part and the rule database of
SE-NST2FNN are optimized based on a clustering method and the
modified invasive weed optimization algorithm, respectively. The
effectiveness of proposed control scheme is verified by simulation
examples.