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Research on Multi-objective Optimization Decision Method and Its Applications to Copper Electrolysis Process

Author: LiMingJie
Tutor: WangXiaoGang
School: Northeastern University
Course: Control Theory and Control Engineering
Keywords: Copper electrolysis Steady-state optimization Multi-objective optimization Particle Swarm Optimization Multiple Attribute Decision Making
CLC: TF811
Type: Master's thesis
Year: 2008
Downloads: 96
Quote: 1
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Abstract


Metal copper is an important basic raw materials and strategic materials, the the copper electrolytic production process is the main way to obtain high-purity refined copper products. However, due to the electrolytic copper industrial process nonlinear, time-varying, strong coupling and complex reaction mechanism, an important indicator of the relationship between product quality parameters difficult online measurement to establish the model of the relationship between the steady-state production goals and operating parameters very difficult, thus affecting the the copper electrolytic industrial production process optimization control implementations. With the changes in market demand and improve product quality requirements, the urgent need for copper electrolytic industrial process using high-tech to accelerate development. In the case of copper electrolytic production process matures, the basis and process control system equipment has improved continuously, copper electrolytic process parameters soft measurement and steady-state optimization techniques to further improve the economic efficiency of enterprises are two important research topics closely . This article is based on the actual copper electrolytic industrial production process of multi-objective optimization and its decision-making method. Research based on the optimization of the the copper electrolytic production process energy consumption and quality control analysis, combined with widespread industrial process with multi-objective constrained optimization problem, and propose a new multi-objective optimization method consists of two main parts, the first part of and optimize the use of the proposed method for solving the steady state of the copper electrolysis process optimization problems. The second part of the study of decision-making methods, improved decision-making on the basis of the theory of multi-attribute decision-making utility function to fit the needs of the steady-state optimization. The paper is organized as follows: (1) Based on the of copper electrolytic production principle, the industrial production process in-depth analysis to determine the basic structure of the copper acid composition soft sensor model and auxiliary variables; From the best quality and reduce costs establish a radical ion concentration to the concentration of copper ions, and the cost of electricity consumption of the three objectives of the optimization index function. (2) A new multi-objective optimization particle swarm algorithm to solve this multi-objective optimization problem. This method using variable external set strategy and quick sort method to reduce the amount of computation adopted congestion operators and strong dominate the distribution of relationship to ensure good results. Verified through simulation comparative analysis of the test functions as well as the steady-state optimization of copper electrolysis process, the method has good quality in terms of convergence and distribution of solutions and computational efficiency, especially in solving the three-objective optimization problem outstanding performance, and show that the algorithm has broader applicability in the field of multi-objective optimization. (3) proposed a method suitable for multi-objective decision-making method of multi-attribute utility function of the steady-state optimization of the process control system, designed to solve the problem of the choice of the optimal solution in the process of multi-objective optimization of process industry. Due to the adjustment of the magnitude of the decision variables (controller setting), the transition from one steady state to another steady state will allow the controlled process, during which accompanied the dynamic response of the process (or object). According to the original decision-making function of the relationship between strike decision variables, you can make the controller setpoint adjustment is too large, resulting in the process large fluctuations of the accused, and even affect the stability of the system. In this regard, improved decision-making function combines the preferences of decision-makers, and the impact of the decision variables change, the application of the results of the numerical simulation analysis and electrolytic copper production process that improved decision-making method is able to take into account the decision-makers expect goals and decision variables The moderate change two aspects, not only because of the decision variables can be avoided adjustment is too large to affect the system stability problems, and can maintain an appropriate optimization process. Finally, in the summary of the full text of the work on the basis of decision theory research and engineering application development trend of industrial process optimization their point of view, and pointed out that the issue needs further study of the theory and applications.

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CLC: > Industrial Technology > Metallurgical Industry > Nonferrous metal smelting > Heavy metals smelting > Copper
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