“School of Cognitive”
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| Paper IPM / Cognitive / 7526 |
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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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