## 3 The Proposed Model and Methods
### ANN-Based Embedded Data-Driven Controller Design
#### 3.2.1 Preparing Data Set for Training  
An experimental setup, shown in Figure 6, was constructed for collecting ANN training data. Pressure control for data collection was achieved by regulating the PAM pressure using a proportional regulator, which generated compressed air output ranging from 0 to 6 bar in response to a 0-10 V analog input. Position feedback during the pressing operation, resulting from PAM contraction, was obtained using a linear potentiometer, producing a 0-10 V analog voltage signal. Additionally, a load cell-based force measurement device was utilized to measure the force resulting from PAM contraction.  
The data collection process, depicted in the schematic diagram in Figure 7, involved several steps. Initially, to adjust the inlet pressure of the PAM actuator, a FESTO VPPE-3-1/8-6-010 proportional pressure regulator was employed, converting the Siemens S7-1200 PLC's 0-10 V analog output into a compressed air supply ranging from 0 to 6 bar. The displacement resulting from the PAM actuator's contraction was measured using a linear displacement sensor connected to the analog input of the PLC. Simultaneously, the static force generated  
Figure 5: Pneumatic schematic and measurement system of the pressing unit.  
Figure 6: (**a**) Experimental setup used in discrete data acquisition; (**b**) static force measurement obtained from the contraction with applied pressure.  
by the actuator's contraction was quantified using a load cell-based static force measuring unit, with readings manually retrieved from a digital display and recorded accordingly.  
The experimental setup was used to measure and record the displacement and static force values corresponding to 25 different randomly selected pressure values. At the initial stage of data acquisition, the distance between the fixed base and the movable upper part of the Fluid Muscle Press module was measured as 40.4 mm, when no pressure was applied. In the non-pressured condition, the analog value read from the linear displacement sensor to be used for displacement measurement was recorded as an analog voltage signal of 2.27 V. In order to collect the subsequent 24 data, the compressed air controlled by the analog output signal of the PLC was gradually increased at randomly selected intervals, and the analog voltage signals obtained from the displacement sensor were collected. The displacement and the resulting contraction force at each inlet pressure change were read from the load cell-based measuring unit display and recorded manually. In this way, all of the training data shown in Table 1 were obtained.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Pressure Control** & **Distance Sensor** & **Pressure** & **Distance** & **Displacement** & **Force** \\
**Input Signal (V)** & **Output Signal (V)** & **(bar)** & **(mm)** & **(mm)** & **Measurement (N)** \\ \hline
0.000 & 2.270 & 0 & 40.4 & 0.0 & 0.0 \\
0.417 & 2.270 & 0.25 & 40.4 & 0  
Due to the stochastic collection of data and incremental pressure changes from the experimental setup, the force-displacement graph depicting the system's response to pressure variations was obtained and given in Figure 8. The graph illustrates that the system's response to the input signal applied to the actuator is not linearly characterized.