Study on the Elman Neural Network Operation Control Strategy of the Central Air Conditioning Chilled Water System

The stable operation of the central air conditioning water system always is a major difficulty for the control profession. Paper focus on the water system with multi variable, strong coupling, nonlinear, large time delay characteristics, presented use feed forward coupling compensation method, to eliminate the coupling effect between temperature and pressure. In this paper, the Elman neural network controller is designed for the first time, and the simulation results show that the response time of Elman neural network controller is shorter, the system is more stable and the overshoot is small.


Introduction
For the operation control of the central air conditioning water system, generally control the temperature difference and pressure difference. More scholars have done a lot of experimental research and engineering verification on the control method for temperature difference and pressure difference [1]. K. F. Fong optimization temperature setpoint of chilled water by EP genetic algorithm, water pump control strategy of air conditioning water system are analyzed and experimental by Brian J. Moore and Jamess B. [2] [3]. For the control strategy and control algorithm of the control circuit 2 input −2 output water system, the research is very few, so this paper design a Elman neural network controller for controlling the air conditioning water system stable operation by feed forward coupling compensation [4] [5] [6].

Chilled Water System Model
As Figure 1 show, for the operation control of the central air-conditioning water system, mainly through the control of chilled water supply and return water loop pressure and temperature to achieve. Chilled water supply and return water loop pressure is mainly through the bypass valve to achieve, the temperature difference is mainly through the control of chilled water flow to achieve. The specific control system diagram is shown in Figure 2 and Figure 3 [7].
As Fiure 2 show, for a given chilled water supply and return water loop pressure difference value, mainly through the opening of the regulating valve to achieve the loop of the chilled water supply and return water pressure control, when the chilled water supply and return water loop differential pressure differential pressure is lower than the setpoint, the bypass valve opening decreases. In order to increase the impedance of the pipeline, so as to achieve the stable pressure, and finally achieve the system running requirements.
As Figure 3 show, for a given temperature of chilled water supply and return water loop setpoints, mainly through adjusting the pump speed to change the operation flow of the chilled water system, to get the supply and return water temperature of chilled water loop control, when the temperature difference between chilled water supply and return water temperature is lower than the setpoint of the loop, by reducing the speed water pump. To reduce operation flow chilled water system, to achieve the temperature stability.
In fact, because of the strong direct coupling between the differential pressure regulating and the temperature regulating system, so it is very difficult to control    the system. As shown in Figure 4, when the different pressure regulating opening while changing the bypass valve, also changed the impedance of chilled water piping system, resulting in the chilled water system flow changes in the system under a certain load, the inevitable change of chilled water supply and return water temperature loop. Similarly, when the temperature difference is adjusted by changing the pump the rotational speed of the flow change at the same time, also cause the pressure difference on both sides of the chilled water bypass valve, and the impact of the water system pressure control.
In fact, to central air-conditioning chilled water control system, is a "2 input −2 output" control system. As show in Figure 5 Figure 4. Coupling relationship of chilled water pressure difference and temperature difference. Figure 5. Coupling relationship of air conditioning water system control.

Control Model Decoupling of Chilled Water System
For the decoupling method of the chilled water control model, the traditional decoupling method mainly has the modern frequency method and the feed forward compensation method. The modern frequency method also includes time domain method. The pre compensation method includes the invariance of the contact, the matrix inversion and the inverse decoupling. In this paper, the decoupling network is designed by using the invariance principle of feed forward decoupling compensation method, as shown in Figure 6: Order:    Figure 6 build the "2 input −2 output" decoupling network, although solved the problem of coupling between systems, but in order to ensure that the system output value satisfies the set value requirements, also need to set up the network controller based on feed forward compensation decoupling in Figure 6. In the control system, the PID controller is the most commonly used controller. Its principle block diagram is shown in Figure 7.

Elman Neural Network Controller
PID controller is based on the control deviation which on value ( ) Rin t and the Yout(t) : In the actual project cases, p k i k d k control parameter values have great influence on the output of the system, because of the central air conditioning system of "multi input and multi output, strong coupling between the system

Elman Neural Network Controller Program Simulation
According to the analysis of simulation program controller of central air conditioning water system, this paper uses MATLAB software as a simulation tool for research, program can be realized by MATLAB in Simulink, can be directly through the MATLAB program simulation directly.
As shown in Figure 10, for the Elman neural network PID control algorithm simulation diagram, procedures in accordance with the Elman neural network  Figure 11 shows the Elman neural network PID pressure control corresponding to the input-output simulation results, it can be seen from Figure 11, the Elman neural network PID control based on differential pressure, can be very good to achieve the central air conditioning water system pressure difference value of precision control, but the overshoot of Elman neural network PID differential pressure control based on the comparison, the output of the system in a short time quickly from the pressure difference of 0 m water column, up to 17.137 m water column, so the central air conditioning water system is bad, need to give enough attention in the subsequent engineering verification, but also need to see that the Elman neural network PID differential controllers based on the output of the system rise time is very short, the rise time is only 7S, the adjusting time is only 16S, and can be quickly to ensure the system output stable. Figure 12 shows the Elman PID neural network temperature control corresponding to the input-output simulation results, it can be seen from Figure 12, the PID temperature control based on Elman neural network, the output of the system can not only quickly change follow the preset temperature value changes, and the system is stable, small overshoot. Thus, based on the Elman neural network PID temperature control, can achieve very good operating results.

Simulation Results of Elman Neural Network Controller
In practical projects, for the regulation of central air conditioning water system operation, but also to adjust the temperature and pressure regulation by using the temperature difference, therefore, Elman neural network PID differential Figure 11. Elman neural network PID pressure control corresponding to the input-output simulation results. pressure control, can realize the central air conditioning water system operation good regulation.

Summary
In view of the central air conditioning water system control "2 input −2 output" characteristics, using the invariance principle of feed forward decoupling compensation method, realize the decoupling network structure of the central air conditioning water system "2 input −2 output", and the use of Elman neural network based on PID control algorithm, to achieve the precise control of the central air conditioning water system pressure difference the temperature difference, the simulation results show that Elman neural network control algorithm based on PID, not only can quickly respond to changes in input system, and the control precision is high, operation results are stable and have good application value.