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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.

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 [

As

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

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

In fact, to central air-conditioning chilled water control system, is a “2 input −2 output” control system. As show in

G ( s ) = [ G 11 ( s ) G 12 ( s ) G 21 ( s ) G 22 ( s ) ] = [ Y 1 ( s ) U 1 ( s ) Y 1 ( s ) U 2 ( s ) Y 2 ( s ) U 1 ( s ) Y 2 ( s ) U 2 ( s ) ] (1)

Y 1 ( s ) U 1 ( s ) = 0.0000274 s + 0.0002629 s 2 − 2.0043 s + 1.0054 e − 7.9 s

Y 2 ( s ) U 1 ( s ) = 0.0000025 s − 0.0000022 s 2 − 2.0043 s + 1.0054 e − 12.2 s

Y 1 ( s ) U 2 ( s ) = 0.1105 s + 0.5013 s 2 − 2.0043 s + 1.0054 e − 20.1 s

Y 2 ( s ) U 2 ( s ) = 0.0053 s − 0.0047 s 2 − 2.0043 s + 1.0054 e − 16.8 s

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

Order:

y 11 − y 12 = 0 ( m 2 ≠ 0 )

y 21 − y 22 = 0 ( m 1 ≠ 0 )

So:

G 12 ( s ) − D 12 ( s ) G 11 ( s ) = 0

G 21 ( s ) − D 21 ( s ) G 22 ( s ) = 0

So the mathematical model of the decoupling network:

D 12 ( s ) = − G 12 ( s ) G 11 ( s ) (2)

D 21 ( s ) = − G 21 ( s ) G 22 ( s ) (3)

Put expressions (1) input (2), (3):

D 12 ( s ) = 9.12 s − 8.03 s + 9.59 e − 4.3 s

D 21 ( s ) = 20.85 s − 94.59 s − 0.89 e − 3.3 s

PID controller is based on the control deviation which on value Rin ( t ) and the Yout ( t ) :

Error ( t ) = Rin ( t ) − Yout (t)

u ( t ) = k p ( e r r o r ( t ) + 1 k i ∫ 0 t e r r o r ( t ) d t + k d d e r r o r ( t ) d t )

G ( s ) = U ( s ) E ( s ) = k p ( 1 + 1 k i s + k d s )

where:

K_{p}: ratio coefficient;

K_{i}: integral time constant;

K_{d}: differential time constant.

In the actual project cases, k p k i k d 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

and other factors, resulting in the actual debugging of central air-conditioning system, control tuning parameters, k p k i k d has become very difficult. Therefore, the control loop of the water system of the central air conditioning system, the choice of the corresponding PID parameters becomes very important. If the parameter selection is not properly, it will not only lead to oscillation of the control loop, and even cause the instability of the control loop of the whole air conditioning system. The selection of control parameters k p k i k d in the actual air conditioning control case is also the difficulty of the project. In this paper, a new method of PID parameter k p k i k d is proposed, which uses the Elman neural network to adjust the parameters of the PID controller k p k i k d . As shown in

1) Initialization model: w j l w i j w k j θ l θ j ;

2) Input training values: x 1 , x 2 ⋅ ⋅ ⋅ x p the output value of the model: y 1 , y 2 ⋅ ⋅ ⋅ y p ;

3) estimate: | t p − y p | < ε ;

4) If the step (3) is satisfied, the weight and the threshold value of the model are corresponding to the model, or the following steps:

5) The following values are calculated

E p l = 1 2 ∑ l = 0 m − l ( t l p l − y l p l ) 2 ;

E a l l = 1 2 ∑ p l = 1 p ∑ l = 0 m − l ( t l p l − y l p l ) 2 ;

w j l ( n + 1 ) = w j l ( n ) − η ∂ E a l l ∂ w j l ;

θ l ( n + 1 ) = θ l ( n ) − η ∂ E a l l ∂ θ l ;

w i j ( n + 1 ) = w i j ( n ) − η ∂ E a l l ∂ w i j ;

w k j ( n + 1 ) = w k j ( n ) − η ∂ E a l l ∂ w k j ;

θ j ( n + 1 ) = θ j ( n ) − η ∂ E a l l ∂ θ j ;

6) calculated the model again: w j l w i j w k j θ l θ j

7) Return step (2)

If the step (3) satisfies the condition and stops the training (step 5), the measured value is input to the model, and the predicted value is obtained.

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

PID control structure based on given the formula (1), (12), (13) the corresponding coefficients corresponding simulation chart module. And the preparation of Elman PID1 and Elman PID2 corresponding to the Elman neural network PIDcontrol operation of the m file.

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

pressure control, can realize the central air conditioning water system operation good regulation.

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.

The authors declare no conflicts of interest regarding the publication of this paper.

Li, J.W., Ren, Q.C., Long, H. and Feng, Z.X. (2019) Study on the Elman Neural Network Operation Control Strategy of the Central Air Conditioning Chilled Water System. World Journal of Engineering and Technology, 7, 73-82. https://doi.org/10.4236/wjet.2019.72B009