Devices that interface with the nervous system are improving dramatically, but the complexity and variability of neuronal systems make it difficult to reliably control the activity of living neurons. In my research, I am developing a method for driving the rhythmic patterns generated by a neural circuit towards a target rhythm, providing a proof-of-principle that a living neural system can be reliably controlled. The method exploits novel adaptive filter designs from control theory that I have recently proposed to construct predictive models of neuronal dynamics in real-time. This approach is being tested experimentally in the Stomatogastric Ganglion central pattern generator of the crab, in collaboration with Prof Eve Marder's lab. We are using our engineering approach to exploit the applications of adaptive control for studying neuromodulation in living neural oscillators.