A two-wheeled mobile robot(TWMR) is considered, and an interval type-2 fuzzy logic controller(IT2 FLC) is designed to control its balance and position, respectively. It is difficult to determine the parameters in interval two type fuzzy rules, thus, the improved quantum particle swarm optimization(LTQPSO) algorithm is utilized to optimize the parameters of interval type-2 fuzzy sets. The flowchart of the optimization algorithm is also presented. The control effect of the IT2 FLC and the type-1 fuzzy logic controller(T1 FLC) on balance and position is compared. The influence of mass uncertainty and position disturbance on the control effect of two controllers is considered. The simulation results show that the IT2 FLC designed can achieve the set control objectives effectively. Compared with the T1 FLC, the IT2 FLC has better ability to handle uncertainty and stronger anti-disturbance ability.