Volume 3 Number 1
January 2006
Article Contents
Modelling and Multi-Objective Optimal Control of Batch Processes Using Recurrent Neuro-fuzzy Networks. International Journal of Automation and Computing, vol. 3, no. 1, pp. 1-7, 2006. doi: 10.1007/s11633-006-0001-4
Cite as: Modelling and Multi-Objective Optimal Control of Batch Processes Using Recurrent Neuro-fuzzy Networks. International Journal of Automation and Computing, vol. 3, no. 1, pp. 1-7, 2006. doi: 10.1007/s11633-006-0001-4

Modelling and Multi-Objective Optimal Control of Batch Processes Using Recurrent Neuro-fuzzy Networks

  • Received: 2005-03-03
Fund Project:

This work was supported by the UK EPSRC (GR/N13319, GR/R10875).

通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

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Modelling and Multi-Objective Optimal Control of Batch Processes Using Recurrent Neuro-fuzzy Networks

Fund Project:

This work was supported by the UK EPSRC (GR/N13319, GR/R10875).

Abstract: In this paper, the modelling and multi-objective optimal control of batch processes, using a recurrent neuro-fuzzy network, are presented. The recurrent neuro-fuzzy network, forms a global nonlinear long-range prediction model through the fuzzy conjunction of a number of local linear dynamic models. Network output is fed back to network input through one or more time delay units, which ensure that predictions from the recurrent neuro-fuzzy network are long-range. In building a recurrent neural network model, process knowledge is used initially to partition the processes non-linear characteristics into several local operating regions, and to aid in the initialisation of corresponding network weights. Process operational data is then used to train the network. Membership functions of the local regimes are identified, and local models are discovered via network training. Based on a recurrent neuro-fuzzy network model, a multi-objective optimal control policy can be obtained. The proposed technique is applied to a fed-batch reactor.

Modelling and Multi-Objective Optimal Control of Batch Processes Using Recurrent Neuro-fuzzy Networks. International Journal of Automation and Computing, vol. 3, no. 1, pp. 1-7, 2006. doi: 10.1007/s11633-006-0001-4
Citation: Modelling and Multi-Objective Optimal Control of Batch Processes Using Recurrent Neuro-fuzzy Networks. International Journal of Automation and Computing, vol. 3, no. 1, pp. 1-7, 2006. doi: 10.1007/s11633-006-0001-4
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