Design of a Neural Network Controller to Enhance the Control of Flights in Bad Weather Conditions

Adaptive control is a control method used by a controller which must be adaptable to the controlled system in relation to the parameters which may vary, or are initially uncertain. This is concerned with the control laws changing themselves. The foundation of adaptive control is parameter estimation, which is a branch of system identification. An Artificial Neural Network is used in adaptive control. It is an information processing paradigm inspired by the way the biological nervous systems, such as the brain, process information. This is why its adaptability in flight control processes has continued to attract increasing attention. It is able to answer “what if” questions as required and expected. This has been aptly demonstrated such that to the question, “what if weather is bad?” the answer becomes, “do not land,” automatically. Neural Networks as used here demonstrated adaptability in enhancing flight control in bad weather conditions.