The effects of icing on the longitudinal dynamics of an icing research aircraft

Miller, Robert H.; Ribbens, William B.

doi:10.2514/6.1999-636

Cited by 43 publications

(17 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Discretization of the model is achieved by applying the 4 order Runge-Kutta method and the sample time is 0.01 second. More details about the model are available in [16].…”

Section: A Longitudinal Aircraft Model Applicationmentioning

confidence: 99%

See 1 more Smart Citation

A nonlinear version of the generalized likelihood ratio test

Liu

Zhong

2014

Proceedings of the 33rd Chinese Control Conference

View full text Add to dashboard Cite

In this paper, a new version of the generalized likelihood ratio (GLR) test is proposed to deal with the fault diagnosis problem in nonlinear systems. The unscented Kalman filter (UKF) is utilized for state estimation and innovation generation. The fault signatures used in the hypotheses test are pre-computed by running the fault model and the nominal model simultaneously based on the state estimations. In such a way the intolerable computational problem, which arise from applying a bank of nonlinear filters, is solved. Further more, the fault isolation problem as well as the fault estimation problem of the non-abrupt fault is discussed based on the nonlinear GLR approach. The simulation study of a longitudinal aircraft model is utilized to show the effectiveness of the proposed method.

show abstract

“…Discretization of the model is achieved by applying the 4 order Runge-Kutta method and the sample time is 0.01 second. More details about the model are available in [16].…”

Section: A Longitudinal Aircraft Model Applicationmentioning

confidence: 99%

“…A Longitudinal aircraft model presented in [16] is applied to validate the nonlinear GLR approach proposed in section 3. The model is as follows:…”

Section: A Longitudinal Aircraft Model Applicationmentioning

confidence: 99%

A nonlinear version of the generalized likelihood ratio test

Liu

Zhong

2014

Proceedings of the 33rd Chinese Control Conference

View full text Add to dashboard Cite

show abstract

“…The longitudinal motion dynamics of the Twin Otter aircraft is discussed in detail in Miller and Ribbens (1999) and Tang, Tao, and Joshi (2007). In particular, in Tang et al (2007), the nonlinear affine model introduces the aeroplane velocity V , the angle of attack α, the pitch angle θ and the pitch rate q as the state vector…”

Section: Aircraft Longitudinal Modelmentioning

confidence: 99%

Dynamic gain-scheduled control and extended linearisation: extensions, explicit formulae and stability

Yang¹,

Hammoudi

Herrmann

et al. 2014

International Journal of Control

View full text Add to dashboard Cite

A controller designed for linearisations at various trim/operating points of a nonlinear system using linear approaches is not necessarily performing well or stable once scheduled with a state under dynamic conditions; the key idea of using this scheduled control law design is to retain states close to the current, usually dynamically varying, operating point. Dynamic gain scheduling (DGS) is a technique aimed to resolve this controller scheduling issue for rapidly changing dynamics and states. It entails scheduling the control law gains with a fast-varying state variable rather than with a slowly varying state. It has been successfully applied to the aircraft system models, allowing also for nested loops. The aim of this paper is to extend DGS to a more general setting allowing for more complex multi-input dynamics incorporating the more simple static scheduling within the same controller. Hence, given a linear design, suitable transformations are provided which allow fast scheduling of multi-variable controllers. Important parallels to the approach of extended linearisation are drawn. Theoretical results are shown, providing explicit formulae related to nonlinear dynamic inversion control. Several examples of varying nonlinear complexity are presented in order to emphasise the characteristics of the approach.

show abstract

“…The nonlinear longitudinal dynamics of the twin otter aircraft [23] is used for our actuator failure compensation study. Choosing the velocity, angle of attack, pitch angle, and pitch rate as the states x 1 , x 2 , x 3 and x 4 , and the elevator angles of an augmented two-piece elevator as the inputs u 1 and u 2 , we write the nonlinear aircraft into the state-space form:…”

Section: An Application To Aircraft Controlmentioning

confidence: 99%

An adaptive nonlinear output feedback controller using dynamic bounding with an aircraft control application

Tang¹,

Tao

2008

Adaptive Control & Signal

View full text Add to dashboard Cite

An adaptive output feedback control scheme is developed for a class of nonlinear systems with uncertain nonlinearities, which are bounded by both static and dynamic functions of the system output, and with actuator failures whose failure time instants, patterns and values are unknown, as motivated from an aircraft flight control application. An adaptive backstepping control law using dynamic bounding is constructed to deal with unknown actuator failures as well as system parameter and dynamics uncertainties to guarantee desired system performance. Complete stability and performance analysis and illustrative simulation results of an application to aircraft flight control are presented.

show abstract

The effects of icing on the longitudinal dynamics of an icing research aircraft

Cited by 43 publications

References 3 publications

A nonlinear version of the generalized likelihood ratio test

A nonlinear version of the generalized likelihood ratio test

Dynamic gain-scheduled control and extended linearisation: extensions, explicit formulae and stability

An adaptive nonlinear output feedback controller using dynamic bounding with an aircraft control application

Contact Info

Product

Resources

About