Design of Fuzzy Logic Controller to Drive Autopilot Altitude in Landing Phase

Rawea, Adel; Urooj, Shabana

doi:10.1007/978-3-319-13731-5_13

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…Fuzzy logic has been introduced in many engineering-related fields in aviation. Aircraft conflict resolution (Sathyan et al , 2017), unmanned aerial vehicle swarm routing (Sathyan et al , 2016), aerodynamic modeling (Chang, 2013), fuzzy logic controller to drive autopilot altitude in landing phase (Rawea and Urooj, 2015) and harmonic distortion reduction (Radmanesh and Gharehpetian, 2021) are only a few examples of fuzzy logic implementation in the aerospace industry. In addition to engineering applications, fuzzy logic is also widely used in risk assessment applications in aviation.…”

Section: Fuzzy Risk Matricesmentioning

confidence: 99%

Fuzzy Bayesian based bow-tie risk assessment of runway overrun: a method for airline flight operations

Acarbay

Kiyak

2022

AEAT

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Purpose The purpose of this paper is to improve risk assessment processes in airline flight operations by introducing a dynamic risk assessment method. Design/methodology/approach Fuzzy logic and Bayesian network are used together to form a dynamic structure in the analysis. One of the most challenging factors of the analyses in aviation is to get quantitative data. In this study, the fuzzy data quantification technique is used to perform dynamic risk assessment. Dynamic structure in the analysis is obtained by transforming the bow-tie model into a Bayesian network equivalent. Findings In this study, the probability of top-event from fault tree analysis is calculated as 1.51 × 10−6. Effectiveness of the model is measured by comparing the analysis with the safety performance indicator data that reflects past performance of the airlines. If two data are compared with each other, they are at the same order of value, with small difference (0.6 × 10−7). Originality/value This study proposes a dynamic model to be used in risk assessment processes in airline flight operations. A dynamic model for safety analysis provides real-time, autonomous and faster risk assessment. Moreover, it can help in the decision-making process and reduce airline response time to undesired states, which means that the proposed model can contribute to the efficiency of the risk management process in airline flight operations.

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Section: Fuzzy Risk Matricesmentioning

confidence: 99%

Fuzzy Bayesian based bow-tie risk assessment of runway overrun: a method for airline flight operations

Acarbay

Kiyak

2022

AEAT

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“…For that, some advanced control approaches and improved schemes have been proposed such as: fuzzy logic control [4], neural network [5], adaptive control strategy [6]. The advantage of these approaches is that for a wide range of nonlinear systems, only one algorithm can be applied to solve many problems [7]- [9]. This feature makes advanced control approaches operate in a new atmosphere without any trouble.…”

Section: Introductionmentioning

confidence: 99%

Generalized predictive control based on fuzzy sliding-mode control strategy and fuzzy PI controller for synchronization of uncertain chaotic systems

Driss

Mansouri

2015

2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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In this paper, we consider the synchronization of uncertain chaotic systems using a generalized predictive control (GPC) algorithm based on fuzzy sliding-mode control (FSMC) strategy and fuzzy PI controller respectively. Optimization per formance and synchronization error are the criteria used to distinguish between the two approaches. The control chattering problem affects negatively on the accuracy of FSMC which needs improvements to avoid this problem. The improvements make FSMC more complex to use. Nonetheless, fuzzy PI controller performs better without any improvement, which makes it easier to use. The performances of the two methods are tested considering the synchronization of two uncertain Duffing systems.To illustrate the effectiveness of the described approaches, some numerical results are given.

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Handling Uncertain Environment Using OWA Operators: An Overview

Gupta

Agrawal

2023

Lecture Notes in Networks and Systems

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Design of Fuzzy Logic Controller to Drive Autopilot Altitude in Landing Phase

Cited by 4 publications

References 7 publications

Fuzzy Bayesian based bow-tie risk assessment of runway overrun: a method for airline flight operations

Fuzzy Bayesian based bow-tie risk assessment of runway overrun: a method for airline flight operations

Generalized predictive control based on fuzzy sliding-mode control strategy and fuzzy PI controller for synchronization of uncertain chaotic systems

Handling Uncertain Environment Using OWA Operators: An Overview

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