In this paper fully informed particle swarm optimization (FIPSO) is used as a tool to create an incremental method for design and optimization of Takagi-Sugeno-Kang (TSK) fuzzy controllers. The controller is refined as time goes on, starting from a single controlling rule and evolving as FIPSO leads it to optimize itself. The controller is adaptive and can adjust itself to changes in the parameters of the system as it updates its rule base and parameters. The proposed scheme was applied to the inverted wedge that is a planar robot with two degrees of freedom and a single control input. The inverted wedge is an under actuated system known to be a good test bed for the development of unconventional advanced control techniques. The adaptive fuzzy TSK controller achieved the control objective in a short period of time which shows the efficiency of the proposed method.