Adaptive NN finite-time tracking control of output constrained nonlinear system with input saturation

作者：Zhao, Shiyi; Liang, Hongjing^*; Du, Peihao; Qi, Suwen^*

来源：Nonlinear Dynamics, 2018, 92(4): 1845-1856.

DOI：10.1007/s11071-018-4167-4

• Finite-time control
• Barrier Lyapunov functions (BLFs)
• Output constraints
• Input saturation
• Neural networks (NNs)

This paper considers the finite-time tracking control problem for the strict-feedback nonlinear continuous systems involving input saturation and output constraints. A sequence of desired and auxiliary virtual control signals and real control input is designed to derive a representation of the system estimation errors and stabilize the system. The proposed approach is further developed via a finite-time stability theory, barrier Lyapunov function, and neural network approximation scheme to achieve an expected performance of the considered system. According to the proposed scheme, we solve the finite-time tracking control problem of the nonlinear systems with input saturation. Then, a theorem is provided to address that all the signals and system states are bounded, and the system output is driven to track the reference signal in a finite time to a small neighborhood of zero and remains in the predefined compact sets. The effectiveness of the proposed scheme is confirmed via two simulation examples.

• 出版日期2018-6
• 单位深圳大学; 渤海大学