Control Theory Using in the Air Pollution Control System

In recent years, air pollution control has caused great concern. This paper focuses on the primary pollutant SO 2 in the atmosphere for analysis and control. Two indicators are introduced, which are the concentration of SO 2 in the emissions (PSO 2 ) and the concentration of SO 2 in the atmosphere (ASO 2 ). If the ASO 2 is higher than the certain threshold, then this shows that the air is polluted. According to the uncertainty of the air pollution control systems model, H ∞ control theory for the air pollution control systems is used in this paper, which can change the PSO 2 with the method of improving the level of pollution processing or decreasing the emissions, so that air pollution system can maintain robust stability and the indicators ASO 2 are always operated within the desired target.


Introduction
The main feature of the  ∞ control theory is based on the frequency design method of using the state-space model, and this theory presents an effective method to solve the uncertainty problem of external disturbance to the system.In order to overcome the drawbacks of the classical control theory and the modern control theory,  ∞ control theory established technology and method of the loop shaping in the frequency domain, which combines the classic frequency-domain and the modern state-space method.The design problem of the control system is converted to the  ∞ control problem, which made the system closer to the actual situation and meet the actual needs.So it gives the robust control system design method, which obtains  ∞ controller by solving two Riccati equations.This method fully considered the impact of system uncertainty, which not only can ensure the robust stability of the control system, but also can optimize some performance indices.It is the optimal control theory in frequency domain, and the parameters design of  ∞ controller is more effective than optimal regulator [1].
So the  ∞ control theory for the air pollution control systems can solve the uncertainty of the air pollution control systems model, which can get the control strategy to change the PSO 2 , so that air pollution system can maintain robust stability and the indicators ASO 2 are always operated within the desired target.1, which consists of  and . is a generalized control target which is a given part of the system. is  ∞ controller, and it needs to be designed.

Standard 𝐻
It is supposed that  and  are described as the transfer function matrix of the linear time invariant system [2].Then, () and () are proper rational matrices, Decomposing () as Its state-space realization is It is denoted as: where  ∈   is the state vector,  is the external input,  is the control input,  is the controlled output, and  is the measured output.They are all vector signals.To compare (1) and (3), we can obtain Obviously, the closed-loop transfer function matrix from  to  can be expressed as The problem of  ∞ optimal control theory is to find a proper rational controller  for closed-loop control system, and make the closed-loop control system internally stabile, and then minimize the  ∞ norm of closed-loop transfer function matrix   () [3] ,  21 and  22 are the corresponding dimension of the real matrix, and controller  is dynamic output feedback compensator [4].
Consider that  have a special form: which satisfies the following conditions: (1) (,  1 ) is stabilizable, and ( 1 , ) is detectable; (2) (,  2 ) is stabilizable; (3) ; that is, the state  of generalized control object and the external input signal  could be measured; then, it can be directly used to constitute control law.
As the result, we can obtain Theorem 1.

Analysis and Synthesis of Air Pollution Control System
Atmospheric quality management is essentially the process of the analysis and synthesis to the air pollution control system.So-called atmospheric system analysis is qualitative and quantitative research for an atmospheric area system or facilities system, which include that to evaluate the current situation, to find out the main environment problems, to put a series of optional target projects, and to establish the quantitative relation between emission and the quality of the permissive atmosphere [5].The systems synthesis means the plan and design of an air pollution control system on the basis of system analysis to determine the target and to determine a management method of a system, in other words, in order to achieve certain environmental goal to select the optimal planning scheme, to optimal design, to find the optimal management method, and so forth.So the process of the synthesis should include three main steps: determine the target, form better feasibility scheme of system, and optimization decision [6].Usually, the atmosphere has certain self-purification ability; namely, the atmospheric environment has a certain capacity.It refers to the permissible pollutant emissions within the natural purification capacity, which reach the limiting quantity in order not to destruct the nature material circulation [7].We can make the quantity of pollutant discharged that meets a certain environmental goal to be permissible total emission.Only when the pollutant emissions beyond atmospheric self-purification ability, namely, exceeds the environmental capacity, there may be air pollution [8].

Wind direction
The stirred reactor model of an ideal atmosphere section.
In this paper, the objective of applying the  ∞ control theory in air pollution control system is to find out regularity, to make full use of atmospheric environmental selfpurification ability; we cannot only develop production but also protect the environment.

𝐻 ∞ Control of Air Pollution
In recent years, air pollution control has caused great concern.This paper focuses on primary pollutant SO 2 in the atmosphere for analysis and control, which is mainly pollutant of the PM2.5.We introduced two indicators, which are the concentration of SO 2 in the emissions (PSO 2 ) and the concentration of SO 2 in the atmosphere (ASO 2 ).Meanwhile, we can change the content of SO 2 in the emissions (with the method of improving the methods of processing), with the aim of returning atmospheric quality back to the desired value.

The Mathematical Model of Air Pollution.
A certain volume of air mainly accepted the controlled pollutants which discharged from certain purification equipments.In addition, considering that the atmospheric self-purification ability is mainly affected by wind and other meteorological factors, a certain volume of air can be defined as atmospheric section.Thus, we can put forward a second order state-space equation; it describes the relationship between PSO 2 and ASO 2 on an average point of the atmospheric section [9].The basic idea of modeling is to consider each section as ideal stirred reactor, as shown in Figure 2. So, the parameters and variables of the whole section are consistent, and the output concentration of PSO 2 and ASO 2 is equal to the counterpart concentration in this section.Hence, from the point of view of the mass balance, we can get the following equation.
PSO 2 balance equation: ASO 2 balance equation: where   ,  −1 are the PSO 2 of Section  and Section  − 1 (mg/m 3 ), V  is the atmospheric capacity of Section  (m 3 );   is PSO 2 gas flow rate of Section  (m 3 /d),   ,  −1 are ASO 2 of Section  and Section  − 1 (mg/m 3 ),   , ℎ  are daily decay rate of PSO 2 of Section  and supply rate of ASO 2 of Section ,   ,  −1 are atmosphere gas flow rates of Section  and Section  − 1 (m 3 /d), and    is saturating capacity of SO 2 of Section  (mg/m 3 ).
From [5], we can conclude that it is advisable to take the following values as the coefficients in above equations:   = 0.32/day, ℎ  = 0.2/day,    = 0.36 mg/m 3 , Thus, the mathematical model of Section  air pollution is where  is control strategy.

Simulation of Air Pollution
problem of air pollution is basically how to control emissions of pollutants in the best way, in order to properly handle the cost of cleaning and the price we pay for too much atmospheric pollution.Using  ∞ control theory can better achieve this goal, which not only saves investment but also is easy to be realized [10].
In this paper, the simulation object is two sections of the  ∞ control of atmospheric pollution, the state-space equation is described as Using the MATLAB to simulate [11], we can conclude the step response curve of the air pollution control system.We have It could be seen from Figure 3, that the response time of the original system is 3.6 s, while the response time of closed loop system is 0.026 s by using  ∞ control strategy.It means that  ∞ control strategy makes the step response of the atmosphere system with an improvement; the response time is greatly reduced.Therefore,  ∞ control strategy is a practical control strategy, which can ensure that air pollution control system is operating steadily within the desired target [12].

Conclusion
In this paper, the  ∞ control theory and methods have a great application value on air pollution control system.It can help the environmental protection departments at various levels to analyze the air pollution system, which can ensure the atmosphere quality steady work within the desired target value.Of course, the analysis and control of a large-scale air pollution system that introduced other influencing factors will be very complicated, which will be the focus of the study in this field.

Figure 1 :
Figure 1: The diagram of the standard  ∞ control problem.
which is the transfer function and the state-space expression of robust  ∞ control strategy.