Fig 1.
(a) Schematic of the bioelectronic ion pump. (b) Image of the ion pump in a 6-well plate with buffer solution. (c) Chemical structure of Fluoxetine (d) Graph showing the relationship between the Ipump and the amount of Fluoxetine delivered.
Fig 2.
Closed-loop control architecture for automated ion pump actuation to achieve prescribed current values and regulate the delivered concentration of Fluoxetine.
Fig 3.
Schematic of the experimental closed-loop setup.
The error is computed using the values of the current output read from the ion pump and the desired reference value. The sliding mode controller evaluates the next voltage value. This is sent to the external voltage controller with Raspberry Pi through a WiFi connection with the laptop running the control algorithm. The external voltage controller applies the value through a connected cable from the ion pump. After the voltage has been applied, the external voltage controller reads the current from the ion pump and sends it back to the laptop with the control algorithm through WiFi closing the loop.
Table 1.
Detailed control design parameters of the SMC used in in silico and in vitro experiments.
Fig 4.
In silico results for feedback control on fluorescence mean pixel value in the mathematical model of ion pump device using sliding mode control (SMC), machine learning (ML)–based control, and PID control.
The first row shows the ion pump response to step changes in the reference signal starting at 17.5 dropping by 0.5 each 400 seconds using SMC. The middle row shows the ion pump response to step changes in the reference signal starting at 17.5 dropping by 0.5 each 400 seconds using ML-based control. The last row shows the ion pump response to step changes in the reference signal starting at 17.5 dropping by 0.5 each 400 seconds using PID. The blue line in the first column indicates the desired fluorescence mean pixel value set as a reference for the feedback control algorithm. The red curve represents the output of the mathematical model (fluorescence mean pixel value). The second column shows the control output that is applied to the model in green. The third column shows the error between the desired and measured fluorescence mean pixel value referred to as tracking error in cyan.
Fig 5.
Experimental results for feedback control on current in the ion pump device using sliding mode control.
Row (a) shows the ion pump response to a constant reference signal at 1200nA. Row (c) shows the ion pump response to step changes in the reference signal starting at 1500nA dropping by 300nA each 400 seconds. Row (b) shows the ion pump response to a gradual decline reference signal beginning at 1500nA and ending at 900nA. The blue line in the first column indicates the desired current set as a reference for the feedback control algorithm. The red curve represents the measured current from the device in real-time. The second column shows the control output that is delivered to the device in green. The third column shows the error between the desired and measured current referred to as tracking error in cyan.
Table 2.
Quantitative measures of all the experiments.