Fuzzy logic provides a means for converting a linguistic control strategy, based on expert knowledge, into an automatic control strategy. Its performance depends on membership function and rule sets. In the traditional Fuzzy Logic Control (FLC) approach, the optimal membership is formed by trial-and-error method. In this paper, Genetic Algorithm (GA) is applied to generate the optimal membership function of FLC. The membership function thus obtained is utilized in the design of the Hybrid Intelligent Control (HIC) scheme. The investigation is carried out for an Air Heat System ( AHS) an important component of drying process. The knowledge of the optimum PID controller designed, is used to develop the traditional FLC scheme. The computational difficulties in finding optimal memebership function of traditional FLC is allieviated using GA in the design of HIC scheme. The qualitative performance indicies are evaluated for the three control strategies, namely, PID, FLC and HIC. The comparison reveals that the HIC schene designed based on the hybridisation of FLC with GA performs better. Moreover, GA is found to be an effective tool for designing the FLC, eliminating the human interface required to generate the membership functions.