## 3 Results and Discussion
This process is rather complex and due to the lack of numeral parameters and the complexity of the process, a simpler transfer function model has been implemented in the simulator platform [41]. In the simulator library, the wet granulator contains sub-modules where the particle size specifications are explicitly used, as depicted in Figure 7.  
All process parameters are detailed in Table 1. \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Parameter** & **Symbol** & **Value** & **Unit** \\ \hline Number of axial & \(N_{a}\) & 10 & - \\ compartments & \(N_{r}\) & 7 & - \\ API forward flux & \(a_{API}\) & \(5\times 10^{3}\) & kg/(s rpm) \\ API forward flux & \(b_{API}\) & \(1\times 10^{-1}\) & kg/s \\ API backward flux & \(c_{API}\) & \(6\times 10^{-4}\) & kg/(s rpm) \\ API backward flux & \(d_{API}\) & 0 & kg/s \\ API radial flux & \(c_{API}\) & \(1.1\times 10^{-2}\) & kg/(s rpm) \\ parameter & \(a_{Exc}\) & \(2.5\times 10^{3}\) & kg/(s rpm) \\ MCC forward flux & \(b_{Exc}\) & \(9.8\times 10^{-2}\) & kg/s \\ parameter & MCC backward flux & \(c_{Exc}\) & \(1.3\times 10^{-3}\) & kg/(s rpm) \\ parameter & \(d_{Exc}\) & 0 & kg/s \\ MCC radial flux & \(e_{Exc}\) & \(6.4\times 10^{-3}\) & kg/(s rpm) \\ parameter & \(e_{Exc}\) & \(6.4\times 10^{-3}\) & kg/(s rpm) \\ \hline \hline \end{tabular}  
* API—Active pharmaceutical ingredient; MCC—Microcrystalline cellulose.  
\end{table} 
Table 1: Parameters for the blending process unit. Figure 7: Example of simulator library modules for specifying the grain size in granulator unit. These are part of the process start-up settings given by the operator. For two different species, the following impedance have been obtained, as illustrated in Figure 8 bottom. We compare the frequency response estimation against the parametric model estimation with one pole or two poles in the transfer function from (23). It turned out the result with one pole was sufficiently accurate. The methods for identification have been described in detail in [9]. The identified optimal parameters are listed in Table 2.  
If the grain particle size is decreasing, the number of particles per volume unit is increasing and viscosity is increasing to decrease flow. To maintain a constant flow of species in the blender, we need to adapt the ratio controller gains. An example of the relationship between the particle size and flow of species is given in Figure 9.  
Using mapping as that given in Figure 9, adaptation to context variations in terms of material properties can be done. Context-aware control is a major trend in current engineering applications, and the pharmaceutical industry offers a great opportunity to pick up emerging solutions from more established fields of control applications [16]. This very complex process of tablet manufacturing is described by several sub-processes (e.g., dispensing, blending, granulation, drying, tableting) as depicted in Figure 5. To ensure optimal production each unit needs to operate such that to assure the critical quality attributes. The development of advanced inline monitoring techniques (e.g., the sensing spectroscopy) tracks the product at each individual stage of manufacturing and eventually saves additional analysis time, thereby enabling the direct release of the continuously manufactured batch into the market without delay. The production thereof is a complex multivariable process and modifications to any of the mentioned components can have important implications on the efficiency of the production process (e.g., changes in powder stickiness or mixture viscosity). Therefore, \begin{table}
\begin{tabular}{l l l l l l} \hline  & \(\mathbf{K}\) & \(\boldsymbol{p}\) & \(\boldsymbol{\alpha}\) & \(\boldsymbol{\beta}\) & \(\mathbf{NMSE}\) \\ \hline Species 1 & \(1.11\times 10^{8}\) & \(1.46\times 10^{3}\) & 0.70 & 0.015 & \(4.32\times 10^{-5}\) \\ Species 2 & \(1.33\times 10^{8}\) & \(1.95\times 10^{3}\) & 0.75 & 0.019 & \(9.61\times 10^{-5}\) \\ \hline \end{tabular}
\end{table} 
Table 2: Reduced order model parameters (23) for two species of different viscosity.