| Abstract: | An intelligent shearer height adjusting system is a key technology for mining at a man-less working face.A control strategy for a shearer height adjusting system based on a mathematical model of the height adjusting mechanism is proposed.It considers the non-linearity and time variations in the control process and uses Dynamic Fuzzy Neural Networks(D-FNN).The inverse characteristics of the system are studied.An adaptive on-line learning and error compensation mechanism guarantees system real-time performance and reliability.Parameters from a German Eickhoff SL500 shearer were used with Matlab/Simulink to simulate a height adjusting control system.Simulation shows that the trace error of a D-FNN controller is smaller than that of a PID controller.Also,the D-FNN control scheme has good generalization and tracking performance,which allow it to satisfy the needs of a shearer height adjusting system. |
