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

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.