Analysis of Nonlinear Control Systems

Active flutter suppression, which is a part of the group of flight vehicle technologies known as active controls, is an important contributor to the effective solution of aeroelastic instability pr...

https://arc.aiaa.org/doi/pdf/10.2514/1.C034442

Aircraft Active Flutter Suppression: State of the Art and Technology Maturation Needs

The challenges in designing human-machine interaction have been around for decades: how to combine the intelligence and creativity of humans with the precision and strength of machines? It is well known that manual control tasks are prone to human errors. The conventional engineering solution is to either fully automate a (sub)task or to support the human with alerting systems. Both approaches have inherent limitations, widely described in literature (e.g., Pritchett, 2001; Sheridan, 2002). Recently, an alternative solution is receiving increased attention: that of shared control. In the shared control paradigm, an intelligent system continually shares the control authority with the human controller. The idea behind shared control is to keep the human operator in the direct manual control loop, while providing continuous support. Shared control has been investigated for a wide range of applications, for example during the direct control of automobiles (e.g., Griffiths & Gillespie, 2005; Mulder et al., 2008a&b) and aircraft (e.g., Goodrich et al., 2008), or during tele-operated control to support gripping (Griffin et al., 2005), surgery (e.g, Kragic et al., 2005), micro-assembly (e.g, Basdogan et al., 2007) or the steering of unmanned aerial vehicles (e.g., Mung et al., 2009).

/pdf/neuromuscular-analysis-as-a-guideline-in-designing-shared-4gixuv4egq.pdf

Neuromuscular Analysis as a Guideline in designing Shared Control

Robust linear control, combined with model-reduction methodologies, is investigated for gust rejection on large, very flexible aircraft using trailing-edge control surfaces. Controllers are designed on linearizations of the nonlinear aeroelastic equations, and the closed-loop response of both the linearized and nonlinear system to discrete gust distributions is compared to the open-loop dynamics. Results show that an ℋ∞ controller performs well on a relatively large linearized system, with 9% load alleviation in root bending moments for the critical gust length. When applied to the nonlinear model of the same vehicle, the robust controller gives a good performance in response to short gusts, including the critical length, with even better load reductions than the linear case. However, this performance gap decreases as the gust length is increased. It is also shown how standard model-reduction techniques can provide metrics for the selection of a minimum size of the aeroelastic system. Finally, it is shown...

Robust Gust Alleviation and Stabilization of Very Flexible Aircraft

This paper describes a practical system identification procedure for small, low-cost, fixed-wing unmanned aircraft. Physical size and cost restrictions limit the sensing capabilities of these vehicles. The procedure is demonstrated on an Ultra Stick 25e, therefore emphasizing a minimum complexity approach compatible with a low-cost inertial sensor. A linear model, obtained from the generic nonlinear equations of motion for aircraft, is used as a basis for system identification. This model is populated with results from a first principles analysis to form a baseline model. Flight experiments are designed using the baseline model and operational constraints to collect informative data. Parameters of the linear model are identified by fitting the model to frequency responses extracted from the data. The parameters are integrated into the nonlinear equations of motion, and both linear and nonlinear models are validated in the time domain. Verification of model accuracy is extended with a sensitivity and resid...

System Identification for Small, Low-Cost, Fixed-Wing Unmanned Aircraft

Flight testing for aeroservoelastic clearance is an expensive and time consuming process. Large degree-of-freedom high-fidelity nonlinear aircraft models using computational fluid dynamics coupled with finite element models can be used for accurately predicting aeroelastic phenomena in all flight regimes including subsonic, supersonic, and transonic. With the incorporation of an active feedback control system, these high-fidelity models can be used to reduce the flight-test time needed for aeroservoelastic clearance. Accurate computational fluid dynamics/finite element models are computationally complex, rendering their runtime ill suited for adequate flight control system design. In this work, a complex, large-degree-of-freedom, transonic, inviscid computational fluid dynamics/finite element model of a fighter aircraft is fitted with a flight control system for aeroelastic oscillation reduction. A linear reduced-order model of the complete aeroelastic aircraft dynamic system is produced directly from the high-order nonlinear computational fluid dynamics/finite element model. This rapid runtime reduced-order model is used for the design of the flight control system, which includes models of the actuators and common nonlinearities in the form of rate limiting and saturation. The oscillation reduction controller is successfully demonstrated via a simulated flight test using the high-fidelity nonlinear computational fluid dynamics/finite element/flight control system model.

Incorporation of Feedback Control into a High-Fidelity Aeroservoelastic Fighter Aircraft Model

Wavelet-based time-varying human operator models.

Development of Wavelet-Based Techniques for Detecting Loss of Control

Adverse aeroservoelastic interaction is a problem on aircraft of all types causing repeated loading, enhanced fatigue, undesirable oscillations and catastrophic flutter. This adverse response is traditionally suppressed using notch and/or roll off filters in the primary flight control system architecture. This solution has pitfalls; rigid body performance is degraded due to resulting phase penalty and the filter may not be robust to off nominal behavior. An adaptive approach has been developed that determines optimal blends of both multiple outputs and multiple inputs which effectively isolate and suppress problematic lightly damped modes via negative feedback while minimizing adverse effects on the remaining modal response. Additional emphasis is given towards minimizing adverse effects on aircraft rigid body modes so that low frequency behavior is unchanged with minimal phase penalty. A subspace system identification solution has been incorporated to rapidly identify a large order model of the aircraft from multiple measurement sensors. This identified model is used to synthesize the controller, demonstrating the solution to be completely adaptive. Due to successful isolation of problematic modes, this solution can be applied independent of any primary flight control solution. Algorithm validation was performed via real-time piloted simulation of large order aeroelastic F/A-18C aircraft models.

https://info.aiaa.org/Regions/Western/Orange_County/ASAT%20Conference%202014%20Presentations/Danowsky_AIAA-2013-4743.pdf

Peter M. Thompson

Papers

Incorporation of Feedback Control into a High-Fidelity Aeroservoelastic Fighter Aircraft Model

Wavelet-based time-varying human operator models.

Development of Wavelet-Based Techniques for Detecting Loss of Control

Modal Isolation and Damping for Adaptive Aeroservoelastic Suppression

Evaluation of Wavelet-Based Techniques for Detecting Loss of Control