Temperature reduction water spray valve control system for waste heat power generation control system

Abstract

The invention discloses a temperature reduction water spray valve control system for a waste heat power generation control system. The temperature reduction water spray valve control system comprises an SMC control module, a saturation amplitude limiting module, a rate limiting module and a compensator module. According to the system, on the basis that an SMC control module outputs sliding mode variable structure control with limited feedforward compensation, a rapid self-adaptive sliding mode variable structure scheme based on differential evolution is introduced, and rapid optimization is achieved through contraction of a feasible solution space to an optimal value by using an evolution module with limited population scale and iteration times so as to meet control requirements; the advantages that the sliding mode variable structure is high in control response speed and good in robustness are exerted, depth control is simulated, an indifference optimization control strategy is provided, and the calculated amount is reduced through the longitudinal depth, so that the control real-time performance is guaranteed, and rapid control over the temperature reduction water spray valve of the waste heat power generation control system under the set precision is achieved.

Description

Technical Field

[0001] The invention belongs to nonferrous metal smelting optimization control technology, and in particular relates to a temperature reduction water spray valve control system for a waste heat power generation control system. Background Art

[0002] In the process of non-ferrous metal smelting, a large amount of high-temperature flue gas is generated. The flue gas contains a large amount of waste heat. If it is completely discharged or used in small quantities, it will waste a huge amount of energy and cause environmental pollution. Therefore, before flue gas desulfurization and acid production, a large amount of waste heat is used to generate electricity. The generated electricity is used for smelting production, which has a significant effect on reducing production costs and improving the economic benefits of enterprises. It can also reduce the heat emission of the sulfuric acid system, reduce thermal pollution, and achieve the purpose of energy saving and emission reduction.

[0003] In the waste heat power generation control system, there are many factors that affect the temperature of superheated steam, and the factors interact with each other. At the same time, the control requirements of superheated steam are different for different influencing factors. Common influencing factors include: superheater inlet temperature, steam flow, cooling water volume, etc. In addition, due to the complex structure of the superheater, long pipelines, and large heating area, when disturbances exist, the system will have the characteristics of large time delay and large inertia. Therefore, it is difficult to achieve stable control of superheated steam temperature. Summary of the invention

[0004] The present invention provides a temperature reducing water spray valve control system for a waste heat power generation control system. The waste heat power generation control system adjusts the spray volume by controlling the opening of the temperature reducing water spray valve to achieve superheated steam temperature control. The temperature reducing water spray valve control system is optimized to improve the response speed and robustness, thereby achieving rapid and stable control of the waste heat power generation system.

[0005] The present invention provides a temperature reduction water spray valve control system for a waste heat power generation control system, comprising an SMC control module, a saturation limit module, a rate limit module and a compensator module;

[0006] The input of the desuperheating water spray valve control system is the preset superheated steam temperature expected value r and the temperature error feedback value e; the difference between the preset superheated steam temperature expected value r and the temperature error feedback value e is input into the SMC control module, and the SMC control module input also includes the output of the compensator module; the output w of the SMC control module is the theoretical control quantity, and the output w of the SMC control module is sequentially passed through the saturation limit module and the rate limit module connected in series to obtain the desuperheating water spray valve adjustment rate u as the output of the desuperheating water spray valve control system;

[0007] The difference ΔP1 between the output w of the SMC control module and the output v of the saturation limit module, and the difference ΔP2 between the output v of the saturation limit module and the adjustment rate u of the cooling water spray valve are weighted summed and the result is input into the compensator module.

[0008] Specifically, the input ΔP of the compensator module is expressed using the following formula:

[0009] ΔP=Q1ΔP1+Q2ΔP2

[0010] Among them, Q1 is the action threshold limit compensation coefficient; Q2 is the maximum action change rate limit compensation coefficient.

[0011] Specifically, the control process of the SMC control module is as follows:

[0012] T1 is the selection function sat(S) function threshold, T2 is the system steady-state threshold, S is the synovial surface penetration coefficient; the selection function sat(S) is expressed using the following formula:

[0013]

[0014] When |sat(S)|≤T1, the controlled system is controlled by adaptive sliding mode variable structure optimization control, and the cascade differential evolution control maintains the tracking state; when T1<|sat(S)|≤T2, the control output is completed by the cascade differential evolution control, and the adaptive sliding mode variable structure optimization control switches to tracking; when |sat(S)|>T2, the system again adopts adaptive sliding mode variable structure optimization control, and the cascade differential evolution control maintains the tracking state.

[0015] Furthermore, the adaptive sliding mode variable structure optimization control is specifically as follows:

[0016] Adopting the adaptive sliding mode variable structure method based on differential evolution algorithm, adaptive control is realized by optimizing the sliding mode coefficient according to state feedback and error value, so as to optimize the waste heat power generation control system; the number of optimization in the control process is obtained by designing a virtual sliding film surface to find the optimal threshold;

[0017] Specifically, for the number of optimization searches in the control process, 2×N virtual sliding surfaces with the sliding surface as the symmetry surface are designed, and the optimal threshold is updated only when the system state crosses the virtual sliding surface. The auxiliary sliding surface is expressed by the following formula:

[0018]

[0019] Among them, Z0 is the initial value of the controlled state; T4 is the setting accuracy; N is the number of auxiliary synovial surfaces; T1 is the threshold of the selection function sat(S); the distance between the initial value of the state and the threshold is divided into four equal sections, the optimal threshold is calculated once every 20 times the accuracy of the system state in the first interval, the optimal threshold is calculated once every 10 times the accuracy of the system state in the second interval, the optimal threshold is calculated once every 5 times the accuracy of the system state in the third interval, and the optimal threshold is calculated once every time the system state in the interval closest to the threshold undergoes a change in accuracy.

[0020] Furthermore, the cascade differential evolution control is specifically as follows:

[0021] For a single optimization process, the traditional differential evolution algorithm is used as the basic module unit, all module units point to the same fitness equation, each unit is used as an independent layer, and the two layers are connected sequentially;

[0022] The execution of the cascade differential evolution algorithm starts from the first layer. The preset population size of the differential evolution algorithm of the first layer is 20 to 100, and the preset number of iterations is 200 to 1000. The obtained optimization results are weighted and used as the feasible solution space of the differential evolution module of the second layer to realize the system's error-free optimization control.

[0023] Furthermore, the compensator module uses the following function for calculation:

[0024] f(x)=-bλ+a(Q1ΔP1+Q2ΔP2)

[0025] Among them, λ is the compensation factor; a is the control feedforward compensation coefficient; b is the error compensation coefficient.

[0026] The invention discloses a temperature-reducing water spray valve control system for a waste heat power generation control system, which improves response speed and robustness by optimizing a control method, thereby realizing rapid and stable control of the waste heat power generation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of the structure of the temperature reduction water spray valve control system used in the waste heat power generation control system of the present invention;

[0028] Figure 2 This is a simulation comparison diagram of the synovial variable structure optimization control of the present invention. DETAILED DESCRIPTION

[0029] The present invention provides a temperature reduction water spray valve control system for a waste heat power generation control system, comprising an SMC control module, a saturation limit module, a rate limit module and a compensator module;

[0030] The input of the desuperheating water spray valve control system is the preset superheated steam temperature expected value r and the temperature error feedback value e; the difference between the preset superheated steam temperature expected value r and the temperature error feedback value e is input into the SMC control module, and the SMC control module input also includes the output of the compensator module; the output w of the SMC control module is the theoretical control quantity, and the output w of the SMC control module is sequentially passed through the saturation limit module and the rate limit module connected in series to obtain the desuperheating water spray valve adjustment rate u as the output of the desuperheating water spray valve control system;

[0031] The difference ΔP1 between the output w of the SMC control module and the output v of the saturation limit module, and the difference ΔP2 between the output v of the saturation limit module and the adjustment rate u of the cooling water spray valve are weighted summed and the result is input into the compensator module.

[0032] Specifically, the input ΔP of the compensator module is expressed using the following formula:

[0033] ΔP=Q1ΔP1+Q2ΔP2

[0034] Among them, Q1 is the action threshold limit compensation coefficient; Q2 is the maximum action change rate limit compensation coefficient.

[0035] Specifically, the control process of the SMC control module is as follows:

[0036] T1 is the selection function sat(S) function threshold, T2 is the system steady-state threshold, S is the synovial surface penetration coefficient; the selection function sat(S) is expressed using the following formula:

[0037]

[0038] When |sat(S)|≤T1, the system state is far from the sliding surface, and the adaptive sliding mode variable structure optimization control is used to control the controlled system, and the cascade differential evolution control maintains the tracking state; when T1<|sat(S)|≤T2, the control output is completed by the cascade differential evolution control, and the adaptive sliding mode variable structure optimization control is switched to tracking to ensure the continuity of the control output and achieve disturbance-free switching; when |sat(S)|>T2, the cascade differential evolution control cannot stably implement control, and the system uses the adaptive sliding mode variable structure optimization control again to make the controlled system quickly return to the system steady-state threshold T2.

[0039] Furthermore, the adaptive sliding mode variable structure optimization control is specifically as follows:

[0040] Adopting the adaptive sliding mode variable structure method based on differential evolution algorithm, adaptive control is realized by optimizing the sliding mode coefficient according to state feedback and error value, so as to optimize the waste heat power generation control system; the number of optimization in the control process is obtained by designing a virtual sliding film surface to find the optimal threshold;

[0041] Specifically, for the number of optimization searches in the control process, 2×N virtual sliding surfaces with the sliding surface as the symmetry surface are designed, and the optimal threshold is updated only when the system state crosses the virtual sliding surface. The auxiliary sliding surface is expressed by the following formula:

[0042]

[0043] Among them, Z0 is the initial value of the controlled state; T4 is the setting accuracy; N is the number of auxiliary synovial surfaces; T1 is the threshold of the selection function sat(S); the distance between the initial value of the state and the threshold is divided into four equal sections, the optimal threshold is calculated once every 20 times the accuracy of the system state in the first interval, the optimal threshold is calculated once every 10 times the accuracy of the system state in the second interval, the optimal threshold is calculated once every 5 times the accuracy of the system state in the third interval, and the optimal threshold is calculated once every time the system state in the interval closest to the threshold undergoes a change in accuracy.

[0044] Furthermore, the cascade differential evolution control is specifically as follows:

[0045] For a single optimization process, the traditional differential evolution algorithm is used as the basic module unit, all module units point to the same fitness equation, each unit is used as an independent layer, and the two layers are connected sequentially;

[0046] The execution of the cascade differential evolution algorithm starts from the first layer. The preset population size of the differential evolution algorithm of the first layer is 20 to 100, and the preset number of iterations is 200 to 1000. The obtained optimization results are weighted and used as the feasible solution space of the differential evolution module of the second layer to realize the system's error-free optimization control.

[0047] Furthermore, the compensator module uses the following function for calculation:

[0048] f(x)=-bλ+a(Q1ΔP1+Q2ΔP2)

[0049] Among them, λ is the compensation factor; a is the control feedforward compensation coefficient; b is the error compensation coefficient.

[0050] The method of the present invention is further described below in conjunction with an embodiment:

[0051] After receiving the command, the speed of the regulating valve of the desuperheating spray valve of the waste heat power generation control system is usually uniform. Its characteristic curve is approximately regarded as a proportional relationship, and the change rate limit parameter is set to 1, that is, the rate of change of the control output is strictly limited to the interval [-1,1]. Under the restrictive conditions, after multiple simulations and debugging, the compensation weight coefficient Q1=Q2=1 is taken; the sat(s) function threshold is set to 0.3, the number of individuals for differential evolution optimization is set to 60, and the number of iterations is 600. The simulation curve finally obtained by using the desuperheating spray valve control system of the present invention is as follows: Figure 2 As shown in the DSMC curve.

[0052] The conventional control scheme PID control is used to simulate the waste heat power generation system. The simulation curve is as follows: Figure 2 As shown in the PID curve.

[0053] The waste heat power generation system is optimized and controlled only by using the adaptive sliding mode variable structure method in the temperature reduction spray valve control system of the present invention, without introducing the cascade differential evolution strategy to optimize the single optimization. The obtained simulation curve is as follows: Figure 2 As shown in the FSMC curve.

[0054] Figure 2 All three schemes achieved stable operation of the waste heat power generation control system, and all had small overshoots; FSMC belongs to differential control, and the static error of the simulation result is 0.0018, which fully meets the industrial operation demand standard. The traditional PID enters the steady state in about 140s, and the FSMC scheme enters the steady state in about 60s, which is better than conventional control. The DSMC scheme has the shortest rise time and adjustment time, which takes about 50s; and the overshoot of the control scheme that introduces the sliding mode variable structure algorithm is less than 1%, which has significant advantages over PID control.

Claims

1. A temperature-reducing water spray valve control system for a waste heat power generation control system, characterized in that: It includes SMC control module, saturation limit module, rate limit module and compensator module; The input of the desuperheating water spray valve control system is the preset superheated steam temperature expected value r and the temperature error feedback value e; the difference between the preset superheated steam temperature expected value r and the temperature error feedback value e is input into the SMC control module, and the SMC control module input also includes the output of the compensator module; the output w of the SMC control module is the theoretical control quantity, and the output w of the SMC control module is sequentially passed through the saturation limit module and the rate limit module connected in series to obtain the desuperheating water spray valve adjustment rate u as the output of the desuperheating water spray valve control system; The difference ΔP1 between the output w of the SMC control module and the output v of the saturation limit module, and the difference ΔP2 between the output v of the saturation limit module and the adjustment rate u of the cooling water spray valve are weighted summed and the result is input into the compensator module.

2. The temperature reduction water spray valve control system for waste heat power generation control system according to claim 1, characterized in that: The input ΔP of the compensator module is expressed using the following formula: ΔP=Q1ΔP1+Q2ΔP2 Among them, Q1 is the action threshold limit compensation coefficient; Q2 is the maximum action change rate limit compensation coefficient.

3. The temperature reduction water spray valve control system for waste heat power generation control system according to claim 1, characterized in that: The control process of the SMC control module is as follows: T1 is the selection function sat(S) function threshold, T2 is the system steady-state threshold, S is the synovial surface penetration coefficient; the selection function sat(S) is expressed using the following formula: When |sat(S)|≤T1, the controlled system is controlled by adaptive sliding mode variable structure optimization control, and the cascade differential evolution control maintains the tracking state; when T1<|sat(S)|≤T2, the control output is completed by the cascade differential evolution control, and the adaptive sliding mode variable structure optimization control switches to tracking; when |sat(S)|>T2, the system again adopts adaptive sliding mode variable structure optimization control, and the cascade differential evolution control maintains the tracking state.

4. The temperature reduction water spray valve control system for waste heat power generation control system according to claim 1, characterized in that: The adaptive sliding mode variable structure optimization control is specifically as follows: An adaptive sliding mode variable structure method based on differential evolution algorithm is adopted to realize adaptive control by optimizing sliding mode coefficient according to state feedback and error value. The number of optimization in the control process is obtained by designing virtual sliding membrane surface to obtain the optimal threshold value.

5. The temperature reduction water spray valve control system for waste heat power generation control system according to claim 4, characterized in that: For the number of optimization searches during the control process of the adaptive sliding mode variable structure optimization control, 2×N virtual sliding surfaces with the sliding surface as the symmetry surface are designed. The optimal threshold is updated only when the system state crosses the virtual sliding surface. The auxiliary sliding surface is expressed by the following formula: Among them, Z0 is the initial value of the controlled state; T4 is the setting accuracy; N is the number of auxiliary synovial surfaces; T1 is the threshold of the selection function sat(S); the distance between the initial value of the state and the threshold is divided into four equal sections, the optimal threshold is calculated once every 20 times the accuracy of the system state in the first interval, the optimal threshold is calculated once every 10 times the accuracy of the system state in the second interval, the optimal threshold is calculated once every 5 times the accuracy of the system state in the third interval, and the optimal threshold is calculated once every time the system state in the interval closest to the threshold undergoes a change in accuracy.

6. The temperature reduction water spray valve control system for waste heat power generation control system according to claim 1, characterized in that: The cascade differential evolution control is specifically as follows: For a single optimization process, the traditional differential evolution algorithm is used as the basic module unit, all module units point to the same fitness equation, each unit is used as an independent layer, and the two layers are connected sequentially; The execution of the cascade differential evolution algorithm starts from the first layer. The preset population size of the differential evolution algorithm of the first layer is 20 to 100, and the preset number of iterations is 200 to 1000. The obtained optimization results are weighted and used as the feasible solution space of the differential evolution module of the second layer to realize the system's error-free optimization control.

7. The temperature reduction water spray valve control system for waste heat power generation control system according to claim 1, characterized in that: The compensator module uses the following function for calculation: f(x)=-bλ+a(Q1ΔP1+Q2ΔP2) Among them, λ is the compensation factor; a is the control feedforward compensation coefficient; b is the error compensation coefficient.

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