Fractional Complex Dynamical Systems for Trajectory Tracking using Fractional Neural Network via Fractional Order PID Control Law
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In this paper the problem of trajectory tracking is studied. Based on the Lyapunov theory, a Fractional Order PID control law that achieves the global asymptotic stability of the tracking error between a fractional order recurrent neural network and a fractional order complex dynamical network is obtained. To illustrate the analytic results we present a tracking simulation of a dynamical network with each node being just one fractional order Lorenz%27s dynamical system and three identical fractional order Chen’s dynamical systems. © 2020 Instituto Politecnico Nacional. All rights reserved.
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In this paper the problem of trajectory tracking is studied. Based on the Lyapunov theory, a Fractional Order PID control law that achieves the global asymptotic stability of the tracking error between a fractional order recurrent neural network and a fractional order complex dynamical network is obtained. To illustrate the analytic results we present a tracking simulation of a dynamical network with each node being just one fractional order Lorenz's dynamical system and three identical fractional order Chen’s dynamical systems. © 2020 Instituto Politecnico Nacional. All rights reserved.
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Fractional complex dynamical systems; Fractional Lyapunov theory; Fractional order PID control law; Trajectory tracking
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