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Paper   IPM / Cognitive Sciences / 7526
School of Cognitive Sciences
  Title:   Applying BELBIC (Brain Emotion Learning Based Intelligent Controller) to an Auto landing System
  Author(s): 
1.  C. Lucas
2.  S. Moghimi
  Status:   In Proceedings
  Proceeding: WSEAS AIKED'03
  Year:  2003
  Supported by:  IPM
  Abstract:
During landing, aircrafts have to face low-altitude wind shear that can be fatal. Most commercial aircrafts currently have optimal automatic landing systems, but they are activated only if well-specified wind speed limitation are met. The reason is that these autolanding systems are not designed to work in the presence of strong with gusts. In this paper, we apply a modified version of brain emotional learning based intelligent controller (BELBIC) to the autolanding system whose multivariable and non-minimum phase nature make the task difficult. By comparing the results with the results derived from using a high gain controller, we show that our proposed solution can achieve robust and satisfactory performance.


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