Robust Fuzzy Neural Network for Concrete Delivery Manipulator with Nonsingleton Input

The control of the concrete manipulator is a challenge, considering its highly nonlinearity and coupling and the uncertainty from the internal and the external, which will effect the efficiency directly. In this paper, the kinemics and dynamics of the whole concrete delivery manipulator are analyzed firstly. An advanced control strategy, nonsingleton fuzzy neural network, is utilized on concrete delivery manipulator for the first time. Then the simulation study is conducted based the Simulink. It can be found that the establishment of dynamic model is appropriate and the proposed NSFNN controller can follow the target signal better. The result shows that the NSFNN controller can solve the uncertainty to some extent in the constrain of the frame of the type-1 logic fuzzy control.