# The Online Identification of the Behaviour of Pollutants inside the Tunnel Tube
## 6 Discussion  
Currently, in most cases of tunnel ventilation systems, conventional control algorithms are employed (such as PID controllers). This choice is due to their ease of implementation within control systems and compliance with ventilation requirements. However, when we aim to address the matter of optimal control concerning specific criteria, such as the minimization of electrical energy consumption (eliminating fan activations based on a one-time exceedance of harmful substance concentration limits), ensuring ventilation pre-emptively before approaching limit exceedances, accounting for significant time constants and dynamic system time delays, handling mutual interactions among various inputs and outputs, considering constraints on input and output variables and system parameters, and factoring in system disturbance, we must employ alternative forms of controllers capable of accommodating these aspects within their algorithms. Over the past few decades, significant progress has been made in this regard, and these approaches are currently implemented across various industrial and transportation applications. The term \"model predictive control\" does not denote a specific control strategy but rather a broad spectrum of control methods that explicitly utilize a process model for computing control signals by minimizing a cost function. This article primarily focuses on constructing a system model. Therefore, this work addresses the modelling of specific segments of the tunnel tube that characterize air pollution levels. The criteria for an appropriate recursive identification algorithm include stability, parameter convergence, resistance to disturbances, adaptability, efficiency, and real-time capability.  
Controlling the ventilation in the tunnel tube according to predicted traffic data assumes a close and logical connection between traffic intensity and pollutant concentrations. Predictions with the model eliminate a one-time increase in pollutant concentrations and eliminate short-term erroneous measurements of pollutant concentrations. The influence of the jet fan on the pollutants inside the tunnel is described in [31]. Jet fans are installed on the ceiling or side walls of the tunnel to create an air stream. The design of optimal ventilation control in the tunnel using a controller that will use a model of the controlled system (for example, a predictive MPC controller uses a model of jet fan influence on pollution, as well as pollution model as measured disturbances) when calculating control action must ensure that the required limits of pollutant concentrations are not exceeded. The limit values for concentrations of harmful substances for regular operation recommend that the air quality values in the tunnel tube not exceed 70 ppm for CO and 5 km\({}^{-1}\) for OP. If these limits are observed, it is not necessary to control NO\({}_{x}\) concentrations because it is assumed that the values of nitrous gases will not exceed the limits. In the standards, the limit for NO\({}_{2}\) ranges from 0.4 to 1 ppm, calculated as a 15 min moving average of variable across the entire tunnel [32]. From this point of view, it is sufficient to create two models, one for CO and the second for OP.