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In this paper, an integral barrier Lyapunov function combined with the RBF neural network are introduced for a class of MIMO nonlinear systems with unknown nonlinearities. Under the premise of the system output and its first derivative of the time being measurable, by applying the integral barrier Lyapunov function, we have designed a controller based on the adaptive RBF neural network which uses...
This paper proposes an adaptive neural network control scheme for uncertain nonlinearly multi-input-multi-output (MIMO) robotic systems with time-varying delay and unknown backlash-like hysteresis. The radial basis function neural network (RBFNN) is used to approximate the unknown nolinear function term of the uncertain MIMO robotic systems and the unknown backlash-like hysteresis nonlinearity. To...
In this technical note, high dimensional integral Lyapunov functions are introduced for a class of MIMO nonlinear systems with unknown nonlinearities. First, adaptive state feedback control is presented based on the integral Lyapunov function. When only the output is measurable, by using a high-gain observer to estimate the derivative of the system output, adaptive output feedback control is also...
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