Adaptive neural network control of coordinated robotic manipulators with output constraint

In this study, the authors aim to solve the tracking control problem of coordinated robotic manipulators. In order to handle with the uncertainties and instability of coordinated robotic manipulators and improve the performance of the system with output constraint, they design a controller by using radial basis function neural network which has the ability to approximate any bounded and continuous functions effectively. A barrier Lyapunov function is also introduced to prevent the violation of output constraint. The stability analysis of the closed‐loop system is provided and the performance of the controller is verified through simulation.