ROBUST DIRECT ADAPTIVE CONTROL BASED ON DYNAMICAL NEURAL NETWORK
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Graphical Abstract
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Abstract
The robust direct adaptive control for a class of unknown multivariable nonlinear system with unmodeled dynamics based on dynamical neural networks is presented. A stable weight learning algorithm, which doesn't require a priori knowledge of the norm for ideal weight matrices but can get stable controller, is determined using Lyapunov theory.Simulation results show the control algorithm is efficient.
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