了基于性能指標切換的多模型預測控制算法，這種方法通過(guò)在多個(gè)操作點(diǎn)附近獲取的多個(gè)線(xiàn)性模型來(lái)設計多個(gè)線(xiàn)性控制器，同時(shí)根據所提的控制器選擇方法來(lái)達到非線(xiàn)性控制。將所提基于性能指標切換的多模型預測控制算法施加到仿真系統中，分別進(jìn)行了設定點(diǎn)跟蹤和有干擾兩種不同情況的仿真。結果表明，所提算法多模型非線(xiàn)性預測控制算法與普通的DMC相比具有更加良好的穩定性和收斂性，并能做到無(wú)偏跟蹤。 參考文獻 [1] QIN S J, BADGWELL T A. An overview of nonlinear model predictive control applications. In: Algower F, Zheng A, eds. Proceedings of Nonlinear model predictive control workshop—assessment and future directions.Ascona, Switzerland, 1998. [2] QIN S J, BADGWELL T A. A survey of industrial model predictive control technology[J]. Control Engineering Practice,2003,11(7):733-764. [3] JOHANSEN T S. Operating regime based process modeling and identification[D]. Norway: University of Trondheim, 1994. [4] Zhou Chaojun, Jiang Weisun. Two methods of multiple models control for nonlinear process[J]. Signal and Control (China), 1994，23(6):356-330. [5] BALAKRISHNAN J. Control system design using multiple models, switching, and tuning [D].American: Yale University, 1996. [6] PISHVAIE M R, SHAHROKHI M. pH control using the nonlinear multiple models, switching, and tunning approach [J]. Ind. Eng. Chem. Res., 2000,39(5):1311-1319. [7] GALAN O, ROMAGNOLI J A, PALAZOGLU A. Real-time implementation of multi-linear model-based control strategies—an application to a bench-scale pH neutralization reactor[J]. Journal of Process Control,2004,14(5):571-579. [8] AUFDERHEIDE B, BEQUETTE B W. Extension of dynamic matrix control to multiple models[J]. Computers and Chemical Engineering, 2003,27(8-9):1079-1096. [9] PORFIRIO C R, NETO E A, ODLOAK D, Multi-model predictive control of an industrial C3/C4 Splitter[J]. Control Engineering Practice, 2003,11(7):765-779.本文引用地址：http://dyxdggzs.com/article/161632.htm
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