Novel design of adaptive neural network controller for a class of non-affine nonlinear systems

The tracking control problem is studied for a class of uncertain non-affine systems. Based on the principle of sliding mode control (SMC), using the neural networks (NNs) and the property of the basis function, a novel adaptive design scheme is proposed. A novel Lyapunov function, which depends on both system states and control input variable, is used for the development of the control law and the adaptive law. The approach overcomes the drawback in the literature. In addition, the lumped disturbances are taken in account. By theoretical analysis, it is proved that tracking errors asymptotically converge to zero. Finally, simulation results demonstrate the effectiveness of the proposed approach.

► A novel adaptive design scheme is proposed for a class of uncertain non-affine systems.
► Using the property of the basis function of the Neural Networks, a novel adaptive sliding mode control scheme is proposed.
► A novel Lyaounov function is used for the development of the control law and the adaptive law.
► The approach overcomes the drawback in the literature. In addition, the lumped disturbances are taken in account.