A Model Matching STR Controller for High Performance Aircraft

This paper presents a development, as well as an investigation of a Model Matching Controller (MMC) design based on the Self-Tuning Regulator (STR) framework for high performance aircraft with direct application to an F-16 aircraft flight control system. In combination with the Recursive Least Squares (RLS) identification, the MMC is developed and investigated for effectiveness on a detailed model of the aircraft. The popular robust Quantitative Feedback Theory (QFT) controller is also outlined and used to represent a baseline controller, for performance comparison during four simulated test flight maneuvers. In each of the four maneuvers, the proposed MMC provided consistently stable and satisfactory performance, including the challenging pull-up and pushover maneuvers. The baseline stationary controller has been found to become unstable in two of the four maneuvers tested. It also performs satisfactorily-to-arguably poorly in the remaining two as compared to the MMC. Simulation results presented in this investigation support a clear argument that the proposed MMC provides superior performance in the realm of automatic flight control. 1. Introduction Challenges in automatic flight control are predominant over those in many systems due to the uncertainties that are involved in the aircraft itself, as well as its surroundings [1–5]. Nonlinearities are found in the dynamics of the plane and the actuators that control it. In addition, atmospheric conditions can always be given credit to the uncertainties in flight control. An aircraft’s velocity, altitude, and orientation are all factors that decide how the plane will perform. Differences in these factors along with varying atmospheric conditions throughout the flight envelope can result in a less than optimum, or even unstable system. For the purpose of stability and control, the ability to cope with these different conditions cannot be compromised. Current methods of flight control include dynamic inversion, gain scheduling, and QFT, among others [6–12]. These are stationary controllers, in which they incorporate a design that does not adapt to the many changes that an aircraft can encounter. Beyond the design phase, their behavior is fixed. For these reasons, the focus of most designs is robustness. This can prove successful, but maneuverability of the aircraft is usually sacrificed to some extent. The flight envelope may even be bounded by the restrictions of the controller itself. Additionally, the aircraft and its surroundings are modeled only in the design phase. The drawback to a design whose