Adaptive neural network control of unknown nonlinear affine systems with input deadzone and output constraint

作者：He, Wei; Dong, Yiting; Sun, Changyin^*

来源：ISA Transactions, 2015, 58: 96-104.

DOI：10.1016/j.isatra.2015.05.014

• Unknown nonlinear affine system
• Input deadzone
• Output constraint
• Radial Basis Function Neural Network (RBFNN)
• Barrier Lyapunov Function

In this paper, we aim to solve the control problem of nonlinear affine systems, under the condition of the input deadzone and output constraint with the external unknown disturbance. To eliminate the effects of the input deadzone, a Radial Basis Function Neural Network (RBFNN) is introduced to compensate for the negative impact of input deadzone. Meanwhile, we design a barrier Lyapunov function to ensure that the output parameters are restricted. In support of the barrier Lyapunov method, we build an adaptive neural network controller based on state feedback and output feedback methods. The stability of the closed-loop system is proven via the Lyapunov method and the performance of the expected effects is verified in simulation.

• 出版日期2015-9
• 单位北京科技大学; 电子科技大学