New Analysis Techniques for Clearance of Flight Control Laws

Selier, Michiel; Fielding, Christopher G.; Korte, Udo; Luckner, Robert

doi:10.2514/6.2003-5476

Cited by 8 publications

(4 citation statements)

References 3 publications

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“…This means that the angle of attack criteria is within the limit (−10 ∘ -26 ∘ ) specified by the clearance process [3]. This result also agrees with that obtained by other investigators using other optimization methods [1][2][3][4][5].…”

supporting

confidence: 89%

“…Military aircrafts are usually, due to performance reasons, naturally unstable, and therefore a flight control system which provides a required artificial stability is essential for their operation. Because the performance of the aircraft is dependent on the controller, and this performance affects the safety of the pilot and reliability of the aircraft structure and components, it must be proven to the aviation authorities that a controller performance will be correctly acceptable throughout a specified flight envelope in all possible failure conditions and in the presence of all possible system parameter variations [1,2]. ideas of natural selection and genetics [9].…”

Section: Introductionmentioning

confidence: 99%

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Flight Control Laws Verification Using Continuous Genetic Algorithms

2013

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This work is concerned with the application of a continuous genetic algorithm (CGA) to solve the nonlinear optimization problem that results from the clearance process of nonlinear flight control laws. The CGA is used to generate a pilot command signal that governs the aircraft performance around certain points in the flight envelope about which the aircraft dynamics were trimmed. The performance of the aircraft model due to pitch and roll pilot commands is analyzed to find the worst combination that leads to a nonallowable load factor. The motivations for using the CGA to solve this type of optimization problem are due to the fact that the pilot command signals are smooth and correlated, which are difficult to generate using the conventional genetic algorithm (GA). Also the CGA has the advantage over the conventional GA method in being able to generate smooth solutions without the loss of significant information in the presence of a rate limiter in the controller design and the time delay in response to the actuators. Simulation results are presented which show superior convergence performance using the CGA compared with conventional genetic algorithms.

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supporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Flight Control Laws Verification Using Continuous Genetic Algorithms

2013

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“…Clearance methods split neatly into two types based on the different clearance principle. One is the so-called analytical-model-based method (AMBM) [1] and another is simulation-data-based method (SDBM) [2,3]. AMBM analyses stable margin, robust stability and some other criteria based on advanced control theories which include (1) structural singular value ( ) analysis [4,5]; (2) polynomial-based clearance [6]; (3) v-gap analysis; (4) bifurcation and continuation method [7]; and (5) optimizationbased clearance [8].…”

Section: Introductionmentioning

confidence: 99%

Robust Stability Clearance of Flight Control Law Based on Global Sensitivity Analysis

Liu

Dong

et al. 2014

Journal of Applied Mathematics

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To validate the robust stability of the flight control system of hypersonic flight vehicle, which suffers from a large number of parametrical uncertainties, a new clearance framework based on structural singular value (μ) theory and global uncertainty sensitivity analysis (SA) is proposed. In this framework, SA serves as the preprocess of uncertain model to be analysed to help engineers to determine which uncertainties affect the stability of the closed loop system more slightly. By ignoring these unimportant uncertainties, the calculation ofμcan be simplified. Instead of analysing the effect of uncertainties onμwhich involves solving optimal problems repeatedly, a simpler stability analysis function which represents the effect of uncertainties on closed loop poles is proposed. Based on this stability analysis function, Sobol’s method, the most widely used global SA method, is extended and applied to the new clearance framework due to its suitability for system with strong nonlinearity and input factors varying in large interval, as well as input factors subjecting to random distributions. In this method, the sensitive indices can be estimated via Monte Carlo simulation conveniently. An example is given to illustrate the efficiency of the proposed method.

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“…From the Airbus team point of view the clearance criteria are considered as robustness criteria, and were applied in linear and nonlinear analysis of the HIRM+ generic model and HWEM aircraft as shown in [7]. Five (5) new analysis techniques highlighted the importance of the clearance task presented in [9], and [10].…”

Section: Incas Bulletin Volume 9 Issue 2/ 2017mentioning

confidence: 99%