A key obstacle in the widespread application of microbial co-cultures in bioprocesses is their compositional instability, as faster-growing species outcompete and dominate the culture. While several synthetic biology approaches have demonstrated control over co-culture composition, there has been an increased interest in computer-based cybernetic control approaches that can offload burdensome genetic control circuitry to computers and enable dynamic control and real-time noise rejection. This work extends that approach, demonstrating a cybernetic control method that is not reliant on any genetic engineering, instead interfacing cells with computers by exploiting their natural characteristics to measure and actuate the composition. We apply this to aPseudomonas putida(P. putida) andEscherichia coli(E. coli) co-culture grown in Chi.Bio bioreactors, first showing how composition estimates calculated from different bioreactor measurements can be combined with a system model using an extended Kalman filter to generate accurate estimates of a noisy system. We also demonstrate that because the species have different optimal temperature niches, adjusting the temperature of the culture can drive the composition in either direction. By using a proportional-integral control algorithm to calculate the temperature that would bring the measured composition towards the desired composition, we are able to track dynamic references and stabilised the co-culture for 7 days (∼250 generations), with the experiment ending before the cells could adapt out of the control. This cybernetic framework is broadly applicable, with different microbes’ unique features and specific growth niches enabling robust control over diverse co-cultures.