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《中国化学工程学报(英文版)》 2012-06
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An Improved Control Vector Iteration Approach for Nonlinear Dynamic Optimization (Ⅰ) Problems Without Path Constraints

HU Yunqing1 , LIU Xinggao1, ** and XUE Anke2 1 State Key Laboratory of Industry Control Technology, Zhejiang University, Hangzhou 310027, China 2 Institute of Information and Control, Hangzhou Dianzi University, Hangzhou 310018, China  
This study proposes an efficient indirect approach for general nonlinear dynamic optimization problems without path constraints. The approach incorporates the virtues both from indirect and direct methods: it solves the optimality conditions like the traditional indirect methods do, but uses a discretization technique inspired from direct methods. Compared with other indirect approaches, the proposed approach has two main advantages: (1) the discretized optimization problem only employs unconstrained nonlinear programming (NLP) algorithms such as BFGS (Broyden-Fletcher-Goldfarb-Shanno), rather than constrained NLP algorithms, therefore the computational efficiency is increased; (2) the relationship between the number of the discretized time intervals and the integration error of the four-step Adams predictor-corrector algorithm is established, thus the minimal number of time intervals that under desired integration tolerance can be estimated. The classic batch reactor problem is tested and compared in detail with literature reports, and the results reveal the effectiveness of the proposed approach. Dealing with path constraints requires extra techniques, and will be studied in the second paper.
【Fund】: Supported by the National Natural Science Foundation of China (U1162130);; the National High Technology Research and Development Program of China (2006AA05Z226);; the Outstanding Youth Science Foundation Zhejiang Province (R4100133)
【CateGory Index】: TP13
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