Predictive control based on local linear fuzzy models
β Scribed by FISCHER, MARTIN; NELLES, OLIVER; ISERMANN, ROLF
- Book ID
- 126515861
- Publisher
- Taylor and Francis Group
- Year
- 1998
- Tongue
- English
- Weight
- 945 KB
- Volume
- 29
- Category
- Article
- ISSN
- 0020-7721
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
the Complexity And Sensitivity Of Modern Industrial Processes And Systems Increasingly Require Adaptable Advanced Control Protocols. These Controllers Have To Be Able To Deal With Circumstances Demanding Judgement Rather Than Simple Yes/no, On/off Responses, Circumstances Where An Imprecise Linguist
Nonlinear model-based predictive control (MBPC) in multi-input multi-output (MIMO) process control is attractive for industry. However, two main problems need to be considered: (i) obtaining a good nonlinear model of the process, and (ii) applying the model for control purposes. In this paper, recen