The RBFNN Adaptive Variable Structure Temperature Control Algorithm for Extruder with Saturated Input

As an important industrial equipment, extruder has high requirements for temperature control accuracy, interference between temperature zones, limited control input, difficult parameter adjustment and complex controller design. Taking extruder temperature control system as the research object, this paper designs extruder temperature control algorithm under the condition of limited input. The algorithm adopts adaptive neural network to automatically identify the system model and suppress the disturbance through convenient structure control algorithm, at the same time, the neural network is used to compensate the saturated input signal. The simulation results show that the algorithm is reliable.