Fig. 6. Computational screening for optimal controller parameters and closed-loop control of co-culture composition.

a Schematic of closed-loop control experiment with a PID controller. b Computational screening for optimal PID gains. Sets of randomly sampled gains (K_p, K_i, K_d) are used to simulate the expected trajectory of the co-culture in a closed-loop setting with a defined target setpoint. Trajectories are scored according to their total deviation from the target strain ratio in the relevant time window. c–e Closed-loop control of co-cultures with the same initial strain ratio and different target setpoints. Both model predictions (Right) and experiments (Left) are shown. c Target photophilic fraction: ${\phi }_p^{\mathrm{set}}=0.7$. d Target photophilic fraction: ${\phi }_p^{\mathrm{set}}=0.3$. e The strain ratio is forced to track setpoints that change from a target photophilic fraction of ${\phi }_p^{\mathrm{set}}=0.2$ to ${\phi }_p^{\mathrm{set}}=0.8$ (t = 10 h) and to ${\phi }_p^{\mathrm{set}}=0.4$ (t = 30 h).

Source data.