A new long-range predictive control algorithm for non linear processes is proposed and is based on the popular Generalized Predictive Control (GPC) algorithm using the Takagi-Sugeno Kang (TSK) piece-wise fuzzy modelling approach. The proposed fuzzy modelling approach is integrated with the proposed control algorithm to form an adaptive control scheme based on a Controlled Auto-Regressive Integrated Moving Average (CARIMA) model structure. The performance of the adaptive control scheme is assessed using a series of experiments on the binary distillation column and on the Continuous Stirred Tank Reactor (CSTR) system.