Robust Stabilization of Uncertain Aircraft Active Systems

Ibrir, Salim; Botez, Ruxandra Mihaela

doi:10.1177/1077546305041366

Cited by 6 publications

(6 citation statements)

References 10 publications

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“…Thus, it is easy to move from a normalized basis to a non-normalized basis and vice versa by inverting coefficients matrix in eq. (14). We note…”

Section: Normalizationmentioning

confidence: 86%

“…LFT is based primarily on the number of different types of uncertainties that are incorporated in the aircraft dynamic model. For example, a multiplicative parametric uncertainty was considered for a robust Gust Load Alleviation of B-52 aircraft, and analyzed using mu -synthesis [14]. One of the two forms of uncertainties: "unknown (or unstructured) uncertainty" structure, and well-defined, known as "structured uncertainties" could be chosen.…”

Section: Introductionmentioning

confidence: 99%

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Cessna Citation X Business Aircraft Eigenvalue Stability– Part 1: a New GUI for the LFRs Generation

Boughari¹,

Mihaela²,

Theel³

et al. 2017

INCAS BULLETIN

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The aim of "Robustness Analysis" is to assess aircraft stability in the presence of all admissible uncertainties. Models that are able to describe the aircraft dynamics by taking into account all uncertainties over a region inside the flight envelope have therefore been developed, using Linear Fractional Representation (LFR). In this paper Part 1 a friendly Graphical User Interface is developed to facilitate the generation of Linear Fractional Representation uncertainty models for the

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“…Thus, it is easy to move from a normalized basis to a non-normalized basis and vice versa by inverting coefficients matrix in eq. (14). We note…”

Section: Normalizationmentioning

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Cessna Citation X Business Aircraft Eigenvalue Stability– Part 1: a New GUI for the LFRs Generation

Boughari¹,

Mihaela²,

Theel³

et al. 2017

INCAS BULLETIN

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“…It is well-known that the presence of time-delay and uncertainty may induce instability or bad performance of dynamic systems. There have been considerable research efforts on the stability analysis and design of uncertain timedelay systems in the last two decades [1][2][3][4][5][6][7][8][9]. However, as stated in [10,11], many existing approaches for the stability of uncertain systems are often over-conservative when dealing with uncertainties, especially for the problems of parametric uncertain systems, such as that in flight control, structural control, and so forth.…”

Section: Introductionmentioning

confidence: 99%

Stability analysis and design of time-delay uncertain systems using robust reliability method

Guo¹

2011

J. of Syst. Eng. Electron.

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A robust reliability method for stability analysis and reliability-based stabilization of time-delay dynamic systems with uncertain but bounded parameters is presented by treating the uncertain parameters as interval variables. The performance function used for robust reliability analysis is defined by a delayindependent stability criterion. The design of robust controllers is carried out by solving a reliability-based optimization problem in which the control cost satisfying design requirements is minimized. This kind of treatment makes it possible to achieve a balance between the reliability and control cost in the design of controller when uncertainties must be taken into account. By the method, a robust reliability measure of the degree of stability of a time-delay uncertain system can be provided, and the maximum robustness bounds of uncertain parameters such that the time-delay system to be stable can be obtained. All the procedures are based on the linear matrix inequality approach and therefore can be carried out conveniently. The effectiveness and feasibility of the proposed method are demonstrated with two practical examples. It is shown by numerical simulations and comparison that it is meaningful to take the robust reliability into account in the control design of uncertain systems.

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“…Due to its complexity in the aerospace industry, the determination of the robust FCS is usually carried out using linear methods applied on linear models, and it is further validated using nonlinear models. In the literature, many linear control methods were used to obtain an FCS such as the linear matrix inequality (LMI) approach, which has been used to achieve a robust control design of an uncertain aircraft system, 6 adaptive controls have been used for disturbance rejection, 7–9 other optimal algorithms were investigated for gust load alleviation and further tested on different aircrafts. 10–13 Then, online parameter estimations and identifications methods were used to improve the flight control capabilities 14–16 by its recovering in the presence of disturbances.…”

Section: Introductionmentioning

confidence: 99%

Flight control clearance of the Cessna Citation X using evolutionary algorithms

Boughari¹,

Botez²,

Ghazi³

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part G:

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In this paper, an Aircraft Research Flight Simulator equipped with Flight Dynamics Level D (highest level) was used to collect flight test data and develop new controller methodologies. The changes in the aircraft's mass and center of gravity position are affected by the fuel burn, leading to uncertainties in the aircraft dynamics. A robust controller was designed and optimized using the H 1 method and two different metaheuristic algorithms; in order to ensure acceptable flying qualities within the specified flight envelope despite the presence of uncertainties. The H 1 weighting functions were optimized by using both the genetic algorithm, and the differential evolution algorithm. The differential evolution algorithm revealed high efficiency and gave excellent results in a short time with respect to the genetic algorithm. Good dynamic characteristics for the longitudinal and lateral stability control augmentation systems with a good level of flying qualities were achieved. The optimal controller was used on the Cessna Citation X aircraft linear model for several flight conditions that covered the whole aircraft's flight envelope. The novelty of the new objective function used in this research is that it combined both time-domain performance criteria and frequency-domain robustness criterion, which led to good level aircraft flying qualities specifications. The use of this new objective function helps to reduce considerably the calculation time of both algorithms, and avoided the use of other computationally more complicated methods. The same fitness function was used in both evolutionary algorithms (differential evolution and genetic algorithm), then their results for the validation of the linear model in the flight points were compared. Finally, robustness analysis was performed to the nonlinear model by varying mass and gravity center position. New tools were developed to validate the results obtained for both linear and nonlinear aircraft models. It was concluded that very good performance of the business Cessna Citation X aircraft was achieved in this research.

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Robust Stabilization of Uncertain Aircraft Active Systems

Cited by 6 publications

References 10 publications

Cessna Citation X Business Aircraft Eigenvalue Stability– Part 1: a New GUI for the LFRs Generation

Cessna Citation X Business Aircraft Eigenvalue Stability– Part 1: a New GUI for the LFRs Generation

Stability analysis and design of time-delay uncertain systems using robust reliability method

Flight control clearance of the Cessna Citation X using evolutionary algorithms

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