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分时供电条件下锌电解过程电解液酸锌比优化控制

Optimal control for acid-zinc ratio of zinc electrolysis process under condition of time-sharing power supply
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摘要 针对分时供电生产所带来的锌电解过程中酸锌比难以控制问题,研究面向电流切换过程中能耗最小的酸锌比最优控制策略。在分析锌电解过程动态反应机理的基础上,通过优化求解新液流量及酸锌比预调节时间,得到酸锌比最优切换轨迹。针对外界扰动造成实际电解液酸锌比偏离最优轨迹的问题,提出一种酸锌比轨迹偏差预测控制方法。研究结果表明:所提出的控制策略能使电解液实际酸锌比快速、准确地跟踪优化设定值,保证锌电解过程稳定、低耗运行。 To solve the control problem caused by frequent adjustments of acid-zinc ratio under the condition of time sharing power supply, an optimal control strategy was established to reduce the energy consumption during the current switching period. Based on the material balance and electrochemical equations, the optimal trajectory of acid-zinc ratio was determined by calculating the flow rate of leaching solution and pre-regulating time. A deviation predictive control method was proposed to deal with the deviation of actual acid-zinc ratio from the optimal trajectory. The results show that the acid-zinc ratio is stabilized around the target, which ensures the stability of zinc electrolysis process and the low energy consumption.
出处 《中南大学学报(自然科学版)》 EI CAS CSCD 北大核心 2017年第6期1538-1544,共7页 Journal of Central South University:Science and Technology
基金 国家自然科学基金资助项目(61673400) 中南大学创新驱动计划项目(2015cx007) 中南大学中央高校基本科研业务费专项资金资助项目(502200771) 湖南省自然科学联合基金资助项目(13JJ8003)~~
关键词 锌电解 能耗优化 最优控制 偏差预测控制 zinc electrolysis energy optimization optimal control deviation predictive control
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  • 1张春峰,邹新杰,余张国.预测控制在过程控制中的应用综述[J].可编程控制器与工厂自动化(PLC FA),2006(7):12-14. 被引量:5
  • 2孙强 桂卫华 王雅琳.锌电解过程电流效率的模糊神经网络模型设计.系统仿真学报,2001,13(18):105-107.
  • 3Yang C H,Deconinck G, Li Y G. An optimal power - dispatching system using neural networks for the electrochemical process of zinc depending on varying prices of electricity [ J]. IEEE Transactions on Neural Networks,2002,13 ( 1 ) :229-236.
  • 4Kennedy J, Eberhart R. Particle swarm optimization [ C ]. Perth: Proceedings of IEEE International Conference on Neural Networks, 1995.
  • 5Gaing Z L. A particle swarm optimization approach for optimum design of PID cont roller in AVR system[J]. IEEE Transactions on Energy Conversion ,2004,19 ( 2 ) :384-391.
  • 6Scott A C,Pitblado R M,Barton G W. Experimental determination of the factors affecting zinc electrowinning efficiency[ J]. Journal of Applied Electrochemistry, 1988,18 : 120-127.
  • 7Barton G W,Scotl A C. A validated mathematical model for a zinc electrowinning cell[ J]. Journal of Applied Electrochemistry, 1992, 22 : 104-115.
  • 8Camacho E F. Constrained generalized predictive control [J]. IEEETransactions on Automatic Control, 1993, 38(2): 327-332.
  • 9Deshpande P B, Bhalodia M A, Caldwell J A,et al. Should you useconstrained model predictive control [J]. Chemical EngineeringProgress, 1995, 91(3): 65-72.
  • 10Yu Yang(于洋), Xu Jun(许鋆), Luo Xionglin(罗雄麟). Constraintsboundary effect in model predictive control and correspondingsolutions [J]. 自动化学报.http://www.cnki.net/kcms/detail/ 11.2109.TP. 20131220. 0431. 031.html.

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