Adaptive LFT control of a civil aircraft with online frequency‐domain parameter estimation

Abstract

Summary This paper describes the application of an indirect linear fractional transformation (LFT)–based state‐space adaptive control scheme to a transport aircraft, within the context of the European project REconfiguration of CONtrol in Flight for Integral Global Upset REcovery. The principle of the scheme is to design and validate off‐line a gain‐scheduled controller, depending on the plant parameters to be estimated, and to combine it online with a model estimator, so as to minimize the onboard computational time and complexity. A modal approach, very classical for the design of a flight control law, is used to directly synthesize the static output feedback LFT controller, depending on the control and stability derivatives, ie, the parameters of the linearized aerodynamic state‐space model to be estimated. Since the gain‐scheduled LFT controller online depends on the parameter estimates instead of the true values, its robustness to transient and asymptotic estimation errors needs to be assessed using μ and integral quadratic constraint analysis techniques. A primary concern being an online implementation, a fully recursive frequency‐domain estimation technique is proposed, with a low online computational burden and the capability to track time‐varying parameters. Full nonlinear simulations along a trajectory validate the good performance properties of the combined estimator and gain‐scheduled flight controller. To some extent, minimal guaranteed stability and performance properties of the adaptive scheme can be ensured by switching to a robust controller when the parameter estimates are not reliable enough, thus bypassing the Certainty Equivalence Principle.

On-line parameter estimation for indirect adaptive flight control: a practical evaluation of several techniques

“…Though the design of the controller is out of the scope of this paper (please report to [6,12]), before displaying test results, it is useful to stress that the architecture of the flight control law is of C*-type [18], a standard choice for longitudinal control laws (e.g., for Airbus aircraft), and that relies on load factor commands:…”

“…The aircraft is supposed to fly about a steady flight condition, and a constant engine thrust is assumed. To feed the gain scheduled controller [6,12], only some lines of (21) need to be estimated in practice, i.e. those corresponding to the fast longitudinal states α & , q & and Nz .…”

“…When these key parameters are no more available or reliable enough, it is still possible to schedule the control laws according to estimated parameters instead of measured ones to keep the same level of performances. Two possible alternatives are: 1/ to replace the faulty measurement by an estimated value (virtual sensing) and to keep going with a scheduling strategy using this estimate [9]; 2/ to schedule the laws with another type of parameters, namely some aerodynamic coefficients [6]. This paper is related to a design belonging to the second category.…”

“…In 2017-2018, a number of ground and flight tests were achieved to implement and to evaluate this adaptive control strategy aboard the MuPAL-α aircraft of JAXA. During these works, a Frequency Domain (FD) technique was used to perform the estimation task (see [6,11] for a description of the techniques and [12] for results). In 2019, additional Time Domain (TD) estimation methods were also developed and implemented: 1/ to be compared to the FD approach in the same experimental conditions since they are much simpler and less demanding; 2/ because such techniques were required for estimating the controller gains of a direct adaptive approach (also tested during VISION).…”

A Novel IGC Scheme for RHV with the Capabilities of Online Aerodynamic Coefficient Estimation and Trajectory Generation

“…The proposed methods are tested with real ordinary flight data sets but the re-entry scenario is not discussed. Additionally, Ferreres et al conducted research on the adaptive Linear Fractional Transformation (LFT) control of a civil aircraft with online frequency-domain parameter estimation [21] and Subrahmanyam et al also developed an online identification system in the frequency domain for mini cropped delta Unmanned Aerial Vehicles (UAVs) [22]. Chowdhary et al compare the performance of three online parameter estimation algorithms with real flight data from two aircrafts-a fixed-wing aircraft (HFB-320) and a rotary wing UAV (ARTIS).…”