Discrete modeling of uncertain continuous systems having an interval structure using genetic algorithms

Chen Chien Hsu, Shih Chi Chang, Hsin Yen Kuo

研究成果: 書貢獻/報告類型會議論文篇章

摘要

In this paper, an evolutionary approach is proposed to obtain the discrete-time transfer function for uncertain continuous-time systems having interval uncertainties. Based on a worst-case analysis, the problem to derive the discrete-time model is first formulated as multiple mono-objective optimization problems for coefficients in the discrete model, and subsequently minimized and maximized via a proposed genetic algorithm to obtain the lower and upper bounds of the coefficient functions. The problem of non-linearly coupled coefficients with exponential nature occurred in the exact discrete-time transfer function is therefore circumvented while preserving the interval structure in the resulting discrete model by using this approach. Because of the time-consuming process that genetic algorithms generally exhibit, particularly the problem nature which requires undertaking a large number of evolution processes, parallel computation for the proposed evolutionary approach in a MATLAB-based working environment is therefore proposed to accelerate the derivation process.

原文英語
主出版物標題Proceedings of the IASTED International Conference on Computational Intelligence
頁面310-315
頁數6
出版狀態已發佈 - 2005 十二月 1
事件IASTED International Conference on Computational Intelligence - Calgary, AB, 加拿大
持續時間: 2005 七月 42005 七月 6

出版系列

名字Proceedings of the IASTED International Conference on Computational Intelligence
2005

其他

其他IASTED International Conference on Computational Intelligence
國家加拿大
城市Calgary, AB
期間2005/07/042005/07/06

ASJC Scopus subject areas

  • Engineering(all)

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