Advanced control of longitudinal motions for underground mining electric vehicles

This thesis aims to develop advanced control algorithms for underground mining electric vehicles (UMEVs). The specifications of UMEVs and the environments for underground mines are first introduced and studied. A new sliding mode controller (SMC) is first proposed in the presence of the bounded information of system uncertainties and external disturbances. Then fuzzy tuning technique is used to adjust SMC parameters to further improve the tracking error convergence with unexpected out-of-bound uncertainties and disturbances. Finally, the state of energy (SOE) is introduced as input to handle the slope changing for the roads in different underground mines.