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Three-phase automatic submerged arc furnace electrode lifting control system research and applicatio

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Tutor: HeJianJun
School: Central South University
Course: Control Science and Engineering
Keywords: Three-phase electrode lifting system,Position - Current Model,PSD Algorithm,Sing
CLC: TP273
Type: Master's thesis
Year:  2010
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Abstract:
Submerged arc furnace is the production of manganese alloy core equipment introduced into the furnace through a three-phase current electrode , arc resistance heat , the raw material at a certain temperature, chemical reduction reaction manganese alloys. Phase submerged arc furnace electrode lifting system control performance directly affects the furnace temperature and the power balance of the pool phase extent , determine the manganese alloy smelting efficiency and quality. Taking a large sealed submerged arc furnace ferroalloy plant automation transformation topics as research background , to achieve the manganese alloy production process optimization , to improve productivity, reduce energy consumption , to build a three-phase electrode lifting the automatic control system's hardware platform, and from the submerged arc furnace system characterization, system modeling and control strategy three aspects of the study . The diversity of the furnace inner conductive manner , the reaction furnace smelting furnace phase current complexity and mutual coupling , decided submerged arc furnace with time-varying , strong coupling , multi -variable nonlinear system characteristics. According to the characteristics of submerged arc furnace system , established a position as the input variables to the electrode , the electrode current position of the output variables - current model, using least squares parameter identification algorithm for submerged arc furnace model parameters identification. The model is a true reflection of the submerged arc furnace as a function of position and current mapping relationship , the study of control strategies of great significance . For submerged arc furnace system characteristics, the design of a neuron adaptive PSD ( ratio , sum, differential ) decoupling control algorithm , the control algorithm than the traditional PID control algorithm, with the following characteristics: does not depend on the object mathematical model ; structure is simple and clear physical significance ; functionality with online learning can overcome object parameter varying impact on the control system ; learning time is short, rapid convergence parameters , adaptive ability, good decoupling effect . Simulation results show that the control algorithm has good dynamic characteristics, can greatly improve the control effect of electrode lifting system , improve production efficiency.
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