CN103116278B - A kind of reactor three wastes control method based on multiple goal reverse optimization and system - Google Patents

A kind of reactor three wastes control method based on multiple goal reverse optimization and system Download PDF

Info

Publication number
CN103116278B
CN103116278B CN201310014456.9A CN201310014456A CN103116278B CN 103116278 B CN103116278 B CN 103116278B CN 201310014456 A CN201310014456 A CN 201310014456A CN 103116278 B CN103116278 B CN 103116278B
Authority
CN
China
Prior art keywords
control
module
multiple goal
wastes
objectives
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Expired - Fee Related
Application number
CN201310014456.9A
Other languages
Chinese (zh)
Other versions
CN103116278A (en
Inventor
李贵
党同强
潘玲阳
吴宜灿
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hefei Institutes of Physical Science of CAS
Original Assignee
Hefei Institutes of Physical Science of CAS
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hefei Institutes of Physical Science of CAS filed Critical Hefei Institutes of Physical Science of CAS
Priority to CN201310014456.9A priority Critical patent/CN103116278B/en
Publication of CN103116278A publication Critical patent/CN103116278A/en
Application granted granted Critical
Publication of CN103116278B publication Critical patent/CN103116278B/en
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Landscapes

  • Feedback Control In General (AREA)

Abstract

The invention provides a kind of reactor three wastes control method based on multiple goal reverse optimization and system, radioactive wastes process problem in reactor operation process, can be produced, comprise waste gas, waste liquid, give up admittedly.In order to carry out three-protection design to reactor safely and efficiently, the present invention proposes a kind of reactor three wastes control system based on multiple goal reverse optimization, is formed by upper layer software (applications) control module, lower circuit control module, machine control modules, and is connected successively.This three wastes control system gathers the signals such as radiation dose, concentration, pressure, liquid level, flow, temperature, the Controlling model of multiple goal reverse optimization method and extensibility is adopted to design and circuit interface design concept, pump, blower fan, electric check valve and enviromental monitoring equipment are controlled in real time, and Real time dynamic display control procedure, solve the problems such as control efficiency in current disposal of three wastes is low, power consumption is large, fallibility.

Description

A kind of reactor three wastes control method based on multiple goal reverse optimization and system
Technical field
The invention belongs to three wastes controlling party in the multi-crossed disciplines fields such as Nuclear Science And Engineering, radiation protection and environmental protection, Application of Nuclear Technology to, be specifically related to a kind of reactor three wastes control method based on multiple goal reverse optimization and system.
Background technology
Control in relevant device development at the existing reactor three wastes, what often adopt is simple instruction control method, is namely simply controlled by manual command's input, if discovery does not reach environmental emission requirement, then repeatable operation after controlling.This method often causes efficiency low, consumes energy high, the problem such as easily to make mistakes.Such as " China Experiment Fast Reactor three wastes control system " (Nuclear Science And Engineering, 30(3)) what adopt is exactly this kind of control method.In addition, prior art poor expandability, is not easy to according to different control overflow, carries out adjustment and controls.In order to overcome the above problems, the present invention develops a kind of reactor three wastes control method based on multiple goal reverse optimization and system.
Summary of the invention
The object of the invention is to provide a kind of reactor three wastes control method based on multiple goal reverse optimization and system, can according to the control objectives requirement of user's setting, utilize the Controlling model of multiple goal reverse optimization principle and extensibility to set up to design with circuit interface, realize the efficient reactor three wastes and control.
The technical solution adopted in the present invention realizes as follows: a kind of reactor three wastes control system based on multiple goal reverse optimization, and this system comprises: upper layer software (applications) control module, lower circuit control module, machine control modules, and connects successively;
Described upper layer software (applications) control module is formed by control objectives and pretreatment module, multiple goal reverse optimization module, Real time dynamic display module, and is connected successively; Control objectives has extensibility, control objectives number according to user need arrange, there is no particular/special requirement; The annexation of parts of Real time dynamic display module Real time dynamic display Controlling model, Controlling model and the process of control; Controlling model has extensibility, utilizes the pre-service of control objectives, can increase or reduce parts and the annexation of Controlling model;
Described lower circuit control module is formed by instruction translation module, instruction correction module, command output module, and is connected successively; The interface that the instruction of control circui exports has extensibility, according to control objectives pre-service, automatically generates;
Described machine control modules is made up of electric check valve, blower fan, pump, enviromental monitoring equipment, and is all connected with control circui; Wherein, the number of users of electric check valve, blower fan, pump, enviromental monitoring equipment is installed as required, and guarantees that the Controlling model given with control objectives pre-service is consistent.
Based on a reactor three wastes control method for multiple goal reverse optimization, realized by following operational process: (1) brings into operation; (2) top level control software: (2.1) control objectives and pre-service, (2.2) multiple goal reverse optimization, (2.3) Real time dynamic display; (3) whether result meets control objectives, if "Yes", turns (4) step, if "No", returns (2.1); (4) lower circuit controls: (4.1) instruction translation, (4.2) instruction correction, and (4.3) instruction exports; (5) Mechanical course: simultaneously control electric check valve, blower fan, pump, enviromental monitoring equipment; (6) return (2.3) Real time dynamic display, feed back and the result of display and control.
The present invention's advantage is compared with prior art: this three wastes control system gathers the signals such as radiation dose, concentration, pressure, liquid level, flow, temperature, the Controlling model of multiple goal reverse optimization method and extensibility is adopted to design and circuit interface design concept, pump, blower fan, electric check valve and enviromental monitoring equipment are controlled in real time, and Real time dynamic display control procedure, solve the problems such as control efficiency in current disposal of three wastes is low, power consumption is large, fallibility.
Accompanying drawing explanation
Fig. 1 is primary module structural drawing of the present invention;
Fig. 2 is operational flow diagram of the present invention.
Embodiment
The present invention is further illustrated below in conjunction with the drawings and specific embodiments.The technical solution adopted in the present invention realizes as follows:
As shown in Figure 1, a kind of reactor three wastes control system block diagram representation based on multiple goal reverse optimization.It is formed by upper layer software (applications) control module, lower circuit control module, machine control modules, and is connected successively;
A), described upper layer software (applications) control module is formed by control objectives and pretreatment module, multiple goal reverse optimization module, Real time dynamic display module, and is connected successively; Control objectives has extensibility, control objectives number according to user need arrange, there is no particular/special requirement; The annexation of parts of Real time dynamic display module Real time dynamic display Controlling model, Controlling model and the process of control; Controlling model has extensibility, utilizes the pre-service of control objectives, can increase or reduce parts and the annexation of Controlling model;
Multiple goal reverse optimization module: take control objectives as objective function, the optional power consumption of control objectives is minimum, the control time is target the soonest; Non-zero parameter is that constraint condition sets up multiple goal reverse optimization model, is then solved by optimized algorithm; The mathematic(al) representation of Optimized model is as follows:
Min σ j = | X j - X ′ j | ST X j = Σ i x ij ; x ij , X j , X ′ j > 0
Min is for minimizing;
σ jfor the least error of a jth target, the quantity that the size of j is corresponding according to working control target determines, the quantity of user's easily extensible control objectives, thus the size determining j value;
X ifor the control objectives that user is arranged; X ' ifor control objectives to be solved;
I=1,2,3,4 represent respectively: electric check valve, blower fan, pump, enviromental monitoring equipment, x ijfor the control objectives that these equipment are corresponding;
ST is constraint condition;
Optimized algorithm can adopt one such as comprising Newton method, method of conjugate gradient, gradient method, random approach, quasi-Newton method or combination, to which kind of optimized algorithm of selection does not specially require, whether to meet the foundation solving and require as employing algorithm; Conjugate gradient algorithm for based on " Matthew effect ": be only concerned about the feature that the key monitoring degree of control area is different according to general, develop " Matthew effect " strategy: be more that the weight that important area gives is larger, the lower weight given of importance degree is lower.Matthew effect (MatthewEffect): from the Holy Bible " New Testament Gospel According to Matthew " fable: " allly to have, also will add to him and make him unnecessary; Do not have, his all yet will dispossessing ".Mathematical formulae based on the conjugate gradient algorithm of " Matthew effect " strategy is described below:
x k + 1 = Mx k + t k p k p 0 = - ▿ f ( x 0 ) p k + 1 = - ▿ f ( x k + 1 ) + λ k p k λ k = | | ▿ f ( x k + 1 ) | | 2 ( λ k - 1 ) T [ f ( x k + 1 ) - f ( x k ) ] , k = 0,1 , · · · n - 2
M: " Matthew effect " tactful weight;
T k: Optimal Step Size;
P k+1: optimal anchor direction;
F (x k): take variable as x kfunction;
λ k: Optimal Parameters.
In formula, the 3rd formula adopts Dai and Yuan(D-Y) the non-linear conjugate gradient method of one that proposed in 1999.A key character of D-Y method be exactly it under Wolfe linear search, total energy produces descent direction, is therefore widely used.On D-Y method basis, this technology adds the M factor as " Matthew effect " tactful weight, to be applied to reactor three-protection design.The M factor is directly proportional to dosage size, provides with maximal value normalizing according to weight distribution;
Controlling model: with the structure of the electric check valve of working control, blower fan, pump, enviromental monitoring equipment and annexation for prototype, set up computer simulation emulation model;
B), described lower circuit control module is formed by instruction translation module, instruction correction module, command output module, and is connected successively; The interface that the instruction of control circui exports has extensibility, according to control objectives pre-service, automatically generates;
Whether upper strata is passed the optimum results of coming in and carries out translating into executable code by instruction translation module, then wrong by instruction correction module check instruction, and carries out instruction by command output module and output to machine control modules;
C), described machine control modules is made up of electric check valve, blower fan, pump, enviromental monitoring equipment, and is all connected with control circui; Wherein, the number of users of electric check valve, blower fan, pump, enviromental monitoring equipment is installed as required, and guarantees that the Controlling model given with control objectives pre-service is consistent.
As shown in Figure 2, a kind of reactor three wastes control method process flow diagram based on multiple goal reverse optimization, is realized by following operational process:
(1) bring into operation;
(2) upper layer software (applications) rate-determining steps: described upper layer software (applications) controls to be formed by control objectives and pre-treatment step, multiple goal reverse optimization step, Real time dynamic display step, and realized successively;
(2.1) control objectives and pre-treatment step; Control objectives has extensibility, control objectives number according to user need arrange, there is no particular/special requirement;
(2.2) multiple goal reverse optimization step;
Controlling model has extensibility, utilizes the pre-service of control objectives, can increase or reduce parts and the annexation of Controlling model;
Multiple goal reverse optimization: take control objectives as objective function, the optional power consumption of control objectives is minimum, the control time is target the soonest; Non-zero parameter is that constraint condition sets up multiple goal reverse optimization model, is then solved by optimized algorithm; The mathematic(al) representation of Optimized model is as follows:
Min σ j = | X j - X ′ j | ST X j = Σ i x ij ; x ij , X j , X ′ j > 0
Min is for minimizing;
σ jfor the least error of a jth target, the quantity that the size of j is corresponding according to working control target determines, the quantity of user's easily extensible control objectives, thus the size determining j value;
X ifor the control objectives that user is arranged; X ' ifor control objectives to be solved;
I=1,2,3,4 represent respectively: electric check valve, blower fan, pump, enviromental monitoring equipment, and xij is the control objectives that these equipment are corresponding;
ST is constraint condition;
Optimized algorithm can adopt one such as comprising Newton method, method of conjugate gradient, gradient method, random approach, quasi-Newton method or combination, to which kind of optimized algorithm of selection does not specially require, whether to meet the foundation solving and require as employing algorithm; Conjugate gradient algorithm for based on " Matthew effect ": according to general be only concerned about the key monitoring degree of control area different feature, develop " Matthew effect " strategy: be more that the weight that important area gives is larger, the lower weight given of importance degree is lower.Matthew effect (MatthewEffect): from the Holy Bible " New Testament Gospel According to Matthew " fable: " allly to have, also will add to him and make him unnecessary; Do not have, his all yet will dispossessing ".Mathematical formulae based on the conjugate gradient algorithm of " Matthew effect " strategy is described below:
x k + 1 = Mx k + t k p k p 0 = - ▿ f ( x 0 ) p k + 1 = - ▿ f ( x k + 1 ) + λ k p k λ k = | | ▿ f ( x k + 1 ) | | 2 ( λ k - 1 ) T [ f ( x k + 1 ) - f ( x k ) ] , k = 0,1 , · · · n - 2
M: " Matthew effect " tactful weight;
T k: Optimal Step Size;
P k+1: optimal anchor direction;
F (x k): take variable as x kfunction;
λ k: Optimal Parameters.
In formula, the 3rd formula adopts Dai and Yuan(D-Y) the non-linear conjugate gradient method of one that proposed in 1999.A key character of D-Y method be exactly it under Wolfe linear search, total energy produces descent direction, is therefore widely used.On D-Y method basis, this technology adds the M factor as " Matthew effect " tactful weight, to be applied to reactor three-protection design.The M factor is directly proportional to dosage size, provides with maximal value normalizing according to weight distribution;
Controlling model: with the structure of the electric check valve of working control, blower fan, pump, enviromental monitoring equipment and annexation for prototype, set up computer simulation emulation model;
(2.3) Real time dynamic display step; The annexation of parts of Real time dynamic display Controlling model, Controlling model and the process of control;
(3) whether result meets control objectives, if "Yes", turns (4) step, if "No", returns (2.1);
(4) lower circuit rate-determining steps: described lower circuit rate-determining steps is exported step and forms by instruction translation step, instruction correction step, instruction, and realized successively; The interface that the instruction of control circui exports has extensibility, according to control objectives pre-service, automatically generates;
Upper strata is passed the optimum results of coming in and carries out translating into executable code by instruction translation step, then checks that whether instruction is wrong by instruction correction step, and exports step by instruction and carry out instruction and output to machine control modules; And specific as follows:
(4.1) instruction translation step, upper strata is passed the optimum results of coming in and carries out translating into executable code by this instruction translation step;
(4.2) by instruction correction step, instruction correction step, checks that whether instruction is wrong;
(4.3) instruction exports step, carries out instruction and outputs to machine control modules;
(5) Mechanical course: simultaneously control electric check valve, blower fan, pump, enviromental monitoring equipment; Real time dynamic display: feed back and the result of display and control.
Described Mechanical course step is by control circui electric check valve, blower fan, pump, enviromental monitoring equipment; Wherein, the number of users of electric check valve, blower fan, pump, enviromental monitoring equipment is installed as required, and guarantees that the Controlling model given with control objectives pre-service is consistent.

Claims (2)

1. based on a reactor three wastes control system for multiple goal reverse optimization, it is characterized in that, this system comprises: upper layer software (applications) control module, lower circuit control module, machine control modules, and connects successively;
Described upper layer software (applications) control module is formed by control objectives and pretreatment module, multiple goal reverse optimization module, Real time dynamic display module, and is connected successively; Control objectives has extensibility, control objectives number according to user need arrange; The annexation of parts of Real time dynamic display module Real time dynamic display Controlling model, Controlling model and the process of control; Controlling model has extensibility, utilizes the pre-service of control objectives, can increase or reduce parts and the annexation of Controlling model; Described multiple goal reverse optimization module: take control objectives as objective function, control objectives choosing power consumption minimum, control time is target the soonest; Non-zero parameter is that constraint condition sets up multiple goal reverse optimization model, is then solved by optimized algorithm; The mathematic(al) representation of Optimized model is as follows:
M i n σ j = | X j - X j ′ | S T X j = Σ i x i j ; x i j , X j , X j ′ > 0
Min is for minimizing;
σ jfor the least error of a jth target, the quantity that the size of j is corresponding according to working control target determines, the quantity of user's easily extensible control objectives, thus the size determining j value;
X jfor the control objectives that user is arranged; X' jfor control objectives to be solved;
I=1,2,3,4 represent respectively: electric check valve, blower fan, pump, enviromental monitoring equipment, x ijfor the control objectives that these equipment are corresponding;
ST is constraint condition;
Optimized algorithm adopts conjugate gradient algorithm, and the mathematical formulae based on the conjugate gradient algorithm of " Matthew effect " strategy is described below:
x k + 1 = M x k + t k p k p 0 = - ▿ f ( x 0 ) p k + 1 = - ▿ f ( x k + 1 ) + λ k p k λ k = | | ▿ f ( x k + 1 ) | | 2 ( λ k - 1 ) T [ f ( x k + 1 ) - f ( x k ) ] , k = 0 , 1 , ... , n - 2
M: " Matthew effect " tactful weight; The M factor is directly proportional to dosage size, provides with maximal value normalizing according to weight distribution;
T k: Optimal Step Size;
P k+1: optimal anchor direction;
F (x k): take variable as x kfunction;
λ k: Optimal Parameters;
Described lower circuit control module is formed by instruction translation module, instruction correction module, command output module, and is connected successively; The interface that the instruction of control circui exports has extensibility, according to control objectives pre-service, automatically generates;
Described machine control modules is made up of electric check valve, blower fan, pump, enviromental monitoring equipment, and is all connected with control circui; Wherein, the number of users of electric check valve, blower fan, pump, enviromental monitoring equipment is installed as required, and guarantees that the Controlling model given with control objectives pre-service is consistent;
This three wastes control system gathers radiation dose, concentration, pressure, liquid level, flow, temperature signal, the Controlling model of multiple goal reverse optimization method and extensibility is adopted to design and circuit interface design concept, pump, blower fan, electric check valve and enviromental monitoring equipment are controlled in real time, and Real time dynamic display control procedure.
2., based on a reactor three wastes control method for multiple goal reverse optimization, this control method utilizes the reactor three wastes control system based on multiple goal reverse optimization described in claim 1, it is characterized in that, is realized by following operational process:
Step (1), to bring into operation;
Step (2), top level control software:
Step (2.1), control objectives and pre-service,
Step (2.2), multiple goal reverse optimization,
Step (2.3), Real time dynamic display;
Whether step (3), result meet control objectives, if "Yes", turn (4) step, if "No", return (2.1);
Step (4) lower circuit controls:
Step (4.1), instruction translation,
Step (4.2), instruction correction,
Step (4.3), instruction export;
Step (5), Mechanical course: control electric check valve, blower fan, pump, enviromental monitoring equipment simultaneously; Then return (2.3) Real time dynamic display, feed back and the result of display and control.
CN201310014456.9A 2013-01-13 2013-01-13 A kind of reactor three wastes control method based on multiple goal reverse optimization and system Expired - Fee Related CN103116278B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201310014456.9A CN103116278B (en) 2013-01-13 2013-01-13 A kind of reactor three wastes control method based on multiple goal reverse optimization and system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201310014456.9A CN103116278B (en) 2013-01-13 2013-01-13 A kind of reactor three wastes control method based on multiple goal reverse optimization and system

Publications (2)

Publication Number Publication Date
CN103116278A CN103116278A (en) 2013-05-22
CN103116278B true CN103116278B (en) 2015-12-09

Family

ID=48414692

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201310014456.9A Expired - Fee Related CN103116278B (en) 2013-01-13 2013-01-13 A kind of reactor three wastes control method based on multiple goal reverse optimization and system

Country Status (1)

Country Link
CN (1) CN103116278B (en)

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102096406A (en) * 2011-01-13 2011-06-15 北京工业大学 Simulation control system and control system for unsteady change of water inflow during biological waste water treatment

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7826909B2 (en) * 2006-12-11 2010-11-02 Fakhruddin T Attarwala Dynamic model predictive control

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102096406A (en) * 2011-01-13 2011-06-15 北京工业大学 Simulation control system and control system for unsteady change of water inflow during biological waste water treatment

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
中子学计算多目标优化程序开发及其初步应用;胡杨林等;《核科学与工程》;20100930;第30卷(第3期);277-282，288 *

Also Published As

Publication number Publication date
CN103116278A (en) 2013-05-22

Similar Documents

Publication Publication Date Title
Mangal et al. Capability of the RELAP5 code to simulate natural circulation behavior in test facilities
CN103853052A (en) Design method for nuclear power station reactor control system
Zhang et al. The comparison between nonlinear and linear preconditioning JFNK method for transient neutronics/thermal-hydraulics coupling problem
Sánchez-Cervera et al. DE-TOP: A new IAEA tool for the thermodynamic evaluation of nuclear desalination
Batet et al. Modelling of a supercritical CO2 power cycle for nuclear fusion reactors using RELAP5–3D
KR101467221B1 (en) A Method for Determining Optimal design capacity for Integrated Hybrid New and Renewable Energy System
He et al. Towards to the development of virtual testbed for net zero energy communities
Xu et al. ATHLET Simulation of PKL I2. 2 IB-LOCA Benchmark Test and Quantitative Assessment
CN103116278B (en) A kind of reactor three wastes control method based on multiple goal reverse optimization and system
Sun et al. Control system design and validation platform development for small pressurized water reactors (SPWR) by coupling an engineering simulator and MATLAB/Simulink
Garofalo et al. Mission and overview of a Fusion Development Facility
Maitri et al. Computational fluid dynamic assisted control system design methodology using system identification technique for CANDU supercritical water cooled reactor (SCWR)
CN103714212B (en) A kind of distribution system model abbreviation error control method towards transient emulation
Wang et al. Numerical study of integral inherently safe light water reactor in case of inadvertent DHR operation based on the multiscale method
Balestra et al. Modular high temperature gas reactor core modeling with RELAP5-3D/PHISICS–Optimization schemes for load following
Miglierini et al. Investigation of VVER-1000 rod ejection accident according to the phenomenon identification and ranking tables for PWR
Mahmoud et al. Analyzing APR1400 system response under load follow operation using a multiphysics approach
Yu et al. Numerical investigation on the influence of the type of PI controller combined with MAAP code on the steady-state performance of a nuclear power plant
Chiasson et al. Simulation of hybrid solar-geothermal heat pump systems
Ye et al. Development of system code of CFETR design
Tang et al. Development and Application of an Engineering Simulator for HTR-PM Using THERMIX/BLAST and vPower
Lu et al. Coupling Methods for HTR-PM Multicircuit Problem
Jennings Development and application of a computerised design tool for remote area power supply systems
CN104037775A (en) Short-term-voltage stability control method for electric power system
Yildiz et al. Numerical analysis of 1/28 scaled NGNP HTGR reactor building test facility response to depressurization event using GOTHIC

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20151209

Termination date: 20170113

CF01 Termination of patent right due to non-payment of annual fee