ANNNAC – extension of adaptive backstepping algorithm with artificial neural networks

Adaptive Neural Network Control for Inverted Pendulum Using Backstepping with Uncertainties

“…The system being disturbed by sinusoid signals 3  and 4  respectively limited by h 3 =0.2 and h 4 =0.7. In this approach, the reference angle of the rod is equal to /6.…”

“…The main advantage of this method is to ensure system stability with adaptive control. It is also used to determine the control law and parameters updating laws ( [2][3][4]). …”

Dissipative-based adaptive neural control for nonlinear systems

“…For system (7) and the following L 2-supply rate 1 ~,2 [[ 2 (9) s(,,,y)--~t I1~o -Ity112t, where y > 0 is a prescribed constant. If system (7) is dissipative with respect to (9), then, it follows that fr II y(t)II 2dt ~ )'2fT~o II *' II 2dt + 2V(0).…”

“…By utilizing the Lyapunov synthesis approach, some stable adaptive neural control schemes have been developed in [2][3][4] and references therein. Recently, based on the ideas of adaptive backstepping, Polycarpou [ 5,6 ], Knohol et al [7], and Zhang et al [8] Consider a second-order nonlinear system are unknown smooth functions. The control objective is to force the output y ( t ) to track some desired reference signal Ya(t),yd.Yd, andyd are assumed to be uniformly bounded.…”

Fuzzy predictive functional control with adaptive fuzzy model

“…Some are based neural networks [1], [2], [3], [4], some on differential geometry [5], [6], some on fuzzy logic [4], [7], etc.…”