Abstract
SummaryIn this article, a hybrid neural controller is designed in the form of a hybrid neural network (HNN) to deal with the problem of nonlinear continuous‐time systems with time delays and dead‐zone input. The designed HNN comprises of a neural network (NN) and firefly algorithm (FA). The approximation of unknown functions is carried out by using HNN and based on transformed systems, an adaption law, virtual control law and optimal control law are designed. By using the Lyapunov method, it is proved that the designed controller is stable in the sense of semiglobally uniformly ultimate boundedness (SGUUB) and the system output tracks the reference signal with tracking error converging into a small neighborhood of zero. Complexity analysis of the proposed controller is discussed and two numerical examples are presented to prove the efficiency and effectiveness of the proposed model.
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