An adaptive control algorithm for set-point tracking of bioreactor-scale microbial cultivation process parameters is presented, where adaptation of PI controller parameters is based on the controller input/output signals only and does not require additional measurements of process variables. A simple gain scheduling algorithm is developed using tendency model of the controlled process. Extreme operating conditions were selected and modeled to test the algorithms performance while controlling pH in fed-batch operating mode. The simulation results showed that the gain-scheduled controller demonstrated robust behavior and significantly improved the control performance compared to that of fixed-parameter controllers.