Description: In this paper, an orthogonal functions neural network is used to
achieve the control of nonlinear systems. The adaptive controller is constructed
by using Chebyshev orthogonal polynomials neural network, which has advantages
such as simple structure and fast convergence speed. The adaptive learning
law of orthogonal neural network is derived to guarantee that the adaptive
weight errors and tracking errors are bound by using Lyapunov stability theory.
Simulation results are given for a two-link robot in the end of the paper, and the
control scheme is validated.
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Robo_PD.mdl
Robo_PD_sfun.mexw32
Robo_sfun.mexw32
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