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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Mehrjerdi, M.Z. Amoabediny, G. Moshiri, B. Ashktorab, A. Araabi, B.N. |
| Copyright Year | 2013 |
| Description | Author affiliation: Dept. of Life Sci. Eng., Univ. of Tehran, Tehran, Iran (Amoabediny, G.) || Control & Intell. Process. Center of Excellence, Univ. of Tehran, Tehran, Iran (Mehrjerdi, M.Z.; Moshiri, B.; Ashktorab, A.; Araabi, B.N.) |
| Abstract | Today the importance of life science and its related processes are undeniable. Modeling and control of these kind of processes are too complicate because of existence of delay in growth and also nonlinear behavior of micro-organisms. Model predictive control is one of the most popular advanced controlling strategies in this industry, however its dependence on accurate model for predicting future input and output values is limitating. If there is a way that could predict the future values of the process properly, it is possible to overcome to the existing challenges. In this paper we design a model free predictive controller by using a trained recurrent neural network as a predictor for prediction stage at MPC and using GA for solving the associated optimization problem that result the optimal control signal sequence. |
| Sponsorship | IEEE Control Syst. Soc. |
| Starting Page | 2288 |
| Ending Page | 2293 |
| File Size | 387407 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467355339 |
| e-ISBN | 9781467355346 |
| DOI | 10.1109/CCDC.2013.6561318 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-05-25 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Aerated Flask Artificial neural networks Predictive models Biological System GA Trajectory Biological cells Predictive control NNMPC |
| Content Type | Text |
| Resource Type | Article |
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