Abstract
This paper presents the application of a special technique which combines neural networks and sliding modes for solving the robust tracking problem in a nuclear reactor when only the input and the output are available. Due to the appropriate sensor absence, the design is based on a differential neural network observer. The highly nonlinear structure provided by this neural network is linearized using sliding mode. Finally, this linear model is employed for determining a sliding mode control for tracking a reference model. The efficiency of this technique with a guaranteed bound for the averaged tracking error is illustrated by simulation.
Original language | English |
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Pages (from-to) | 171-176 |
Number of pages | 6 |
Journal | IFAC Proceedings Volumes (IFAC-PapersOnline) |
Volume | 40 |
Issue number | 5 |
DOIs | |
State | Published - 2007 |
Externally published | Yes |
Event | 8th IFAC Symposium on Dynamics and Control of Process Systems, 2007 - Cancun, Mexico Duration: 6 Jun 2016 → 8 Jun 2016 |
Keywords
- Differential neural network
- Nuclear reactor
- Sliding mode controller