## 4 Discussion
### Control Algorithm  
The model (Equation (3)) is stable, observable, and controllable because the rank of the controllability and observability matrix is equal to \(n\), where \(n=1\), and the system is a first-order system [22; 24; 25]. We considered a classical control algorithm for the Kv10.1 model. The controller is designed using the Sisotool in MATLAB. We chose an automated tuning method for a PID compensator in a feedback loop, the tuning method is a robust time response, and the controller type is PID. The controller is given by  
\[C(s)=316.85\Big{(}\frac{1+0.0026s}{s}\Big{)} \tag{6}\]  
Figure 6: Unit step response of the system \(G(s)\) with confidence region.  
The unit step response of the controlled Kv10.1 voltage-gated ion channel in a closed-loop, also called a feedback loop, is shown in Figure 8. The Kv10.1 in the feedback loop displays a rise time of 0.043 s, a peak amplitude of 1.06 nA, an overshoot of 6.08%, a transient time of 0.149 s, and a final value of 1 nA. The controlled model has a faster rise time and transient response, and the final value corresponds to the desired value.  
The feedback control system with the Kv10.1 model, \(G\)(s), and controller \(C\)(s) in a loop was implemented in Simulink (Figure 9a). A sine waveform with unit amplitude and frequency of 1 Hz was chosen as a simulation input. The simul  
Figure 8: Unit step response of the Kv10.1 model in a control loop.  
Figure 7: Measured and simulated output macroscopic current for the inactivation and deactivation input stimuli (grey lines). Input stimulus inactivation: measured output (**a**), simulated output (**b**); input stimulus deactivation: measured output (**c**), simulated output (**d**).  
Figure 9b. Nevertheless, using this approach of ion channel modeling, the ion channel could be simulated as a single system or a system in a control loop with any randomly chosen input, enabling the obtained output to be analyzed.  
Microelectromechanical (MEMS) devices and nanoelectromechanical (NEMS) devices can be designed as MEMS PID controllers and NEMS PID controllers. In a clinical context, nanorobots are already used for the mechanical opening of a cell membrane [32], microscopic surgical procedures, drug delivery, gene therapy, or selective destruction of cancer cells [4]. Therefore, our vision is that free-floating and guided nanorobots could have promising applications in cancer detection and therapy. Research has shown that the up-regulation of the selected channel Kv10.1 can promote cell proliferation and thus tumor development in different organs and human body systems [18], whereas the downregulation of Kv10.1 could potentially have the opposite effect, providing a potential oncological target. However, since the same ion channels are also expressed in normal, healthy cells, albeit to minor expression levels, one of the biggest challenges is to specifically block or manipulate them only in cancer cells. Nanorobots could be programmed to target certain cell clusters, tissues or organs (e.g., prostate, stomach, or breast) and specifically control the activity of selected ion channels in cancer cells without affecting the same channels expressed in surrounding healthy cells or other tissues and thus impairing their function. A controlled down-regulation of the ion channel current in specific cells only would also allow for a systemic application, such as the use of traveling nanorobots for the treatment of cancer in various regions of the body or targeted tissues and cell clusters, as shown in Figure 10, for example.