A new means for designating membership functions in a fuzzy logic controller (FLC) is presented. The method allows a novice to construct a set of membership functions, called shrinking-span membership functions (SSMFs), for a specific linguistic variable systematically by using only two parameters : number of elements of the term set and the shrinking factor for that linguistic variable. The SSMFs have different spans for various term set elements in the universe of discourse and this gives the FLC more power to deal with the nonlinearity of the control problems encountered in the real applications. When there is not enough domain knowledge about the process, the SSMFs make it possible for a designer to set up a reasonable and practical rule base for the FLC. According to the computational simulations presented, the satisfactory performance of such an FLC for several test problems can be acquired without laborious optimisation of the tuning parameters. Therefore the proposed approach narrows the gap between a theoretical FLC and a practical one and makes the FLC more down-to-earth.