Intelligent Reconfigurable Control System for Aircraft Flight Control

This research investigation looks at an intelligent reconfigurable control methodology that is used for the design and implementation of control system for commercial aircrafts operating under known and unknown flight conditions. The intelligent reconfigurable methodology is based upon adaptive neuro fuzzy inference system (ANFIS) and is used to integrate the actions of multiple adaptive controllers designed and implemented following the model reference control strategy and architecture. A transport control model (TCM) of commercial aircrafts is used to generate linearized models of its flight dynamics and then the models are utilized in the development and determining the effectiveness of the developed intelligent reconfigurable control system. This methodology attempts to provide a solution for the problems in using an indicator function as presented in previous works. The proposed intelligent reconfigurable control system is developed in two phases: first, a set of flight reference models are established and associate set of adaptive controllers are designed. Second, the ANFIS system is developed for the elevator flight surfaces and trained based on the performance of two designed adaptive controllers using two specific operating conditions to maintain and adjust the angle of attack (AOA) of commercial aircrafts. The testing of the ANFIS system used aircraft dynamic operating under condition that wasn't used in the design of the adaptive controllers. The results showed the intelligent reconfigurable ANFIS control system was able to achieve the desired result of combining the actions of two adaptive controllers for aircraft operating under an unknown operating condition.