Fly-by-Feel Control of an Aeroelastic Aircraft Using Distributed Multirate Kalman Filtering

Armanious, George J.; Lind, Rick

doi:10.2514/1.g002799

Cited by 12 publications

(8 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thapa Magar et al have used artificial hairs based on trichoid sensilla in a feedforward network to predict aerodynamic characteristics on wings in unsteady conditions [83]. Armanious and Lind have proposed a control architecture for mechanosensory-based systems [84]. The benefits of so-called fly-by-feel systems are that they are fast, lightweight, robust and computationally inexpensive.…”

Section: Discussionmentioning

confidence: 99%

Insect and insect-inspired aerodynamics: unsteadiness, structural mechanics and flight control

Bomphrey

Godoy-Diana

2018

Current Opinion in Insect Science

View full text Add to dashboard Cite

Flying insects impress by their versatility and have been a recurrent source of inspiration for engineering devices. A large body of literature has focused on various aspects of insect flight, with an essential part dedicated to the dynamics of flapping wings and their intrinsically unsteady aerodynamic mechanisms. Insect wings flex during flight and a better understanding of structural mechanics and aeroelasticity is emerging. Most recently, insights from solid and fluid mechanics have been integrated with physiological measurements from visual and mechanosensors in the context of flight control in steady airs and through turbulent conditions. We review the key recent advances concerning flight in unsteady environments and how the multi-body mechanics of the insect structure—wings and body—are at the core of the flight control question. The issues herein should be considered when applying bio-informed design principles to robotic flapping wings.

show abstract

Section: Discussionmentioning

confidence: 99%

Insect and insect-inspired aerodynamics: unsteadiness, structural mechanics and flight control

Bomphrey

Godoy-Diana

2018

Current Opinion in Insect Science

View full text Add to dashboard Cite

show abstract

“…The second step is to filter the observed signal. The standard discrete Kalman filter algorithm is summarized as follows [22,23]…”

Section: Dynamic Filtering Algorithmmentioning

confidence: 99%

Research on Dynamic Inertial Estimation Technology for Deck Deformation of Large Ships

Ren

2019

Sensors

View full text Add to dashboard Cite

Many kinds of weapon systems and launching equipment on the deck of large ships are easily affected by deck deformation. In order to ensure the accuracy of weapon systems and the safety of taking off and landing of carrier aircraft, a dynamic estimation method combining the main inertial navigation systems (INS) and the sub-inertial navigation systems (SINS) is designed to estimate the curvature and torsion of any trajectory on the deck. Our contributions start from the fact that the area of concern extends from the fixed points to any trajectory on the deck. The dynamic filter algorithm of wavelet combined with Kalman filter is used to process the acquired data. The wavelet method is used to remove the outliers in the acquired data, and the Kalman filter effectively reduces the influence of white noise, so that the estimation accuracy is guaranteed. The simulation results clearly show that the deck deformation of large ships can be obtained accurately in real-time over the observed area which proved that this dynamic inertial measurement method is feasible in practical engineering application.

show abstract

“…To solve this problem, the flexible states that are difficult to be measured directly need to be provided for feedback. 9 Besides the flexible states, the natural frequencies of flexible modes 10 also have great influences on the dynamic response characteristics. With an inaccurate value of this parameter, the state estimation error could become large.…”

Section: Introductionmentioning

confidence: 99%

Sensor placement and moving horizon state/parameter estimation for flexible hypersonic vehicles

Chen

Jing

Gao

2019

Proceedings of the Institution of Mechanical Engineers, Part G:

View full text Add to dashboard Cite

Considering the nonlinearity, uncertainty, and rigid/elastic coupling, a state/parameter joint estimation method is essential for control system design or fault diagnosis of flexible hypersonic vehicles. With the goal of improving state/parameter estimation accuracy, this paper proposes a sensor placement strategy and a moving horizon estimation algorithm with a QR-decomposition-based arrival cost update strategy (MHE-QR). To enhance observability, a novel double sensor placement strategy, in which the sensor positions are obtained via solving a constrained nonlinear optimization problem, is developed. The MHE-QR algorithm transforms the arrival cost update problem into a least square problem and solves it utilizing QR decomposition. With this QR-decomposition-based arrival update strategy, the state/parameter estimation problem is solved as a nonlinear programming problem in the framework of moving horizon estimation. Finally, the performance of sensor placement strategy and MHE-QR is evaluated by Monte Carlo simulations in 10 different scenarios. Simulation results demonstrate that the sensor placement strategy and MHE-QR algorithm can effectively improve the estimation accuracy, convergence speed and computation rate. Additionally, the CPU time of MHE-QR validates its real-time applicability.

show abstract

Fly-by-Feel Control of an Aeroelastic Aircraft Using Distributed Multirate Kalman Filtering

Cited by 12 publications

References 16 publications

Insect and insect-inspired aerodynamics: unsteadiness, structural mechanics and flight control

Insect and insect-inspired aerodynamics: unsteadiness, structural mechanics and flight control

Research on Dynamic Inertial Estimation Technology for Deck Deformation of Large Ships

Sensor placement and moving horizon state/parameter estimation for flexible hypersonic vehicles

Contact Info

Product

Resources

About