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An Intelligent Air Traffic Control System using Fuzzy Logic Model

Ngozi Idika, Barilee B. Baridam in Fuzzy Systems

International Journal of Applied Information Systems
Year of Publication: 2018
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors:Ngozi Idika, Barilee B. Baridam
10.5120/ijais2018451716
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  1. Ngozi Idika and Barilee B Baridam. An Intelligent Air Traffic Control System using Fuzzy Logic Model. International Journal of Applied Information Systems 12(11):1-9, February 2018. URL, DOI BibTeX

    @article{10.5120/ijais2018451716,
    	author = "Ngozi Idika and Barilee B. Baridam",
    	title = "An Intelligent Air Traffic Control System using Fuzzy Logic Model",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "February 2018",
    	volume = 12,
    	number = 11,
    	month = "Feb",
    	year = 2018,
    	issn = "2249-0868",
    	pages = "1-9",
    	url = "http://www.ijais.org/archives/volume12/number11/1019-2018451716",
    	doi = "10.5120/ijais2018451716",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"
    }
    

Abstract

The application of fuzzy logic in solving flight schedule and air traffic control problems. Fuzzy set theory is appropriate in dealing with this problem because of its ability to deal with control operations and the development of knowledge-based systems using approximate reasoning. The objective is to solve the problem inherent with poor traffic control using an intelligent (knowledgebased) system based on learnt procedures and processes over a set period of time. A fuzzy logic model for air traffic control system is developed that will enhance the performance of air traffic controller and reduce the rate of aircraft accident. The Object- Oriented Analysis and Design Methodology (OOADM) is used in designing the intelligent air traffic control system proposed in this paper. A fuzzification block is designed to convert the fuzzy logic controller. The fuzzy logic input values used are Pathway, Velocity, Climate, Airplane, Height and D-term - which allows the controller to respond faster to permission for clearance. Eleven rules were constructed based on the assigning of linguistic values defined by relatively small number of membership function to variable. The computation block runs the inference engine through all the rules, evaluating the firing strength of each rule whose result is proportional to the truth-value of the preconditions. MATLAB was used to simulate the outcome. The Nigeria airspace is used in the study. From simulated results, safety rules projected were observed by all aircrafts with absolute control irrespective of the number of aircrafts demanding service at a particular time interval. Air accidents were perfectly avoided.

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Keywords

Fuzzy logic, Intelligent system, Air-traffic control, Knowledgebased systems, OOADM