22 research outputs found
Performance in different failure conditions of the predictor-corrector neural controller within the NASA IFCS F-15 WVU simulator
Performance in different failure conditions of the predictor-corrector neural controller within the NASA IFCS F-15 WVU simulator
A simulation environment for design and testing of aircraft adaptive faultātolerant control systems
Nonlinear Aircraft Model Identification and Validation for a Fault-Tolerant Flight Control System
A stochastically optimal feedforward and feedback technique for flight control systems of high performance aircrafts
This paper focuses on a detailed description of a control technique, which has been successfully used in several advanced flight control systems research projects over the past decade. The technique, called Stochastically Optimal Feedforward and Feedback Technique (SOFFT), directly descends from optimal control, and in particular from Explicit Model Following Control (EMFC). Unlike the most used model following techniques, in SOFFT the feedforward and feedback control laws are designed independently of one another. Moreover, this technique relies on different levels of plant models, specifically, a simple plant model is used for the synthesis of the feedback control law, and another plant model, together with a "command" model, are used in the synthesis of the feedforward control laws. It is important to notice that the controller in its final form is nonlinear in nature. This is because the matrices that compose the plant and command models are constantly updated as the aircraft moves throughout the flight envelope, and at least two Algebraic Riccati Equations (ARE) are solved in real time to compute the feedback and feedforward gains