A Review on Drone Technology and Control System by IRJET Journal

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 13 Issue: 02 | Feb 2026 www.irjet.net p-ISSN: 2395-0072

A Review on Drone Technology and Control Systems

Honmore Pooja D.1 , Peerzade Needa S, 2 , Shaikh Md. Sameer S.3 Harage Shrikrant A.4

2,3

Diploma Student, Electronics & Computer Engg. Sanjay Bhokare Group of Institutes, Miraj, Maharashtra, India. 1 Professor, Electronics & Computer Engg. Sanjay Bhokare Group of Institutes, Sangli, Maharashtra, India

⁴HOD, Electronics & Computer Engg, Sanjay Bhokare Group of Institutes, Miraj, Maharashtra, India

Abstract - Drone technology, also known as Unmanned Aerial Vehicle (UAV) technology, has shown rapid growth in recent years due to its wide range of applications in both civilianandindustrialdomains.Initiallydevelopedformilitary operations, drones are now extensively used in agriculture, surveillance, logistics, healthcare, construction, and disaster management. This systematic literature review presents a structured analysis of recent research related to drone technology and control systems. The review focuses on drone architectures, control mechanisms, sensor integration, artificial intelligence-based autonomy, and emerging trends suchasswarmintelligence.Variousresearchpaperspublished in reputed journals and conferences are analyzed to identify technological advancements, application areas, challenges, and research gaps. The study highlights how modern control systems, combined with machine learning and artificial intelligence, have improved flight stability, navigation accuracy, obstacle avoidance, and decision-making capabilities of drones. However, issues related to battery life, security, regulation, and reliable autonomous control still remain open challenges. This review aims to provide a clear understanding of the current state of drone control systems and offers direction for future research in autonomous and intelligent UAV systems.

Key Words: Drone Technology, UAV, Control Systems, Autonomous Navigation, Artificial Intelligence, Machine Learning, Swarm Intelligence

1. INTRODUCTION

DronescommonlyreferredtoasUnmannedAerialVehicles (UAVs), are aircraft systems that operate without an onboard human pilot. Initially developed for military surveillanceanddefencemissions,dronesarenowwidely used in civilian sectors such as agriculture, logistics, healthcare,construction,andenvironmentalmonitoring[1], [3],[4].Therapidgrowthofdroneapplicationsisdrivenby advancementsinlightweightmaterials,sensortechnology, embedded systems, and intelligent control algorithms [5], [6].

Moderndronesarenolongerlimitedtomanualorremote operation.Theintegrationofartificialintelligence(AI)and machinelearning(ML)hasenabledautonomousnavigation, obstacleavoidance,andintelligentdecision-making[2],[13], [14].Control systems playa critical rolein ensuring flight stability, trajectory tracking, and safe operation under

dynamic environmental conditions [17], [20]. This review systematically examines existing literature to understand theevolutionofdronetechnologyandcontrolmechanisms.

2. DRONE ARCHITECTURE AND CLASSIFICATION

Drone systems consist of multiple hardware and software components that work together to achieve stable and controlledflight.Thebasicarchitectureincludestheairframe, propulsionsystem,sensors,flightcontroller,communication modules,andpayload[5],[6].

Dronesarecommonlyclassifiedbasedontheirdesignand operation:

 Fixed-wingdrones,suitableforlong-rangemissions withhigherendurance.

 Rotary-wingdrones(multirotor/copters),preferred for vertical take-off, hovering, and precise maneuvering[17].

 Hybrid drones, combining features of both fixedwingandrotary-wingplatforms[19].

Eachconfigurationrequiresdifferentcontrolstrategiesto managelift,thrust,andstabilityeffectively.

3. DRONE CONTROL SYSTEMS

3.1 Flight Control Mechanisms

Flight control systems are responsible for stabilizing the drone and executing pilot or autonomous commands. Traditional control approaches include Proportional–Integral–Derivative(PID)controllers,whicharewidelyused duetotheirsimplicityandeffectiveness[17].However,PID controllers struggle in highly dynamic or uncertain environments.

Recentresearchfocusesonadaptiveandintelligentcontrol algorithms that can handle communication delays, sensor noise, and incomplete information [20]. These methods improverobustnessandsafetyduringautonomousflight.

3.2 Artificial Intelligence in Drone Control

AI-based control systems allow drones to perceive their environment and make decisions without human intervention.Machinelearninganddeeplearningtechniques are used for path planning, object detection, and collision

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 13 Issue: 02 | Feb 2026 www.irjet.net p-ISSN: 2395-0072

avoidance[2],[10],and[12].Advancedvision-basedsystems using convolutional neural networks (CNNs) and YOLObasedmodelsimprovelocalizationandmappingaccuracy, especiallyincomplexindoorenvironments[24].AI-driven controlsignificantlyenhancesdroneautonomyandmission reliability[14],[22]

3.3Autonomous Navigation and SwarmIntelligence

Autonomous drones rely onsimultaneous localization and mapping (SLAM), sensor fusion, and real-time decisionmaking[13].Swarmintelligenceenablesmultipledronesto coordinateandperformcollectivetasksusingdecentralized control strategies inspired by biological systems [28].Such swarm-based control improves scalability, fault tolerance, andoperationalefficiency,especiallyinsurveillance,searchand-rescue,andlogisticsapplications[7],[15].

4. APPLICATIONS OF DRONE TECHNOLOGY.

4.1 Agriculture

Drones play a major role in precision agriculture by monitoring crop health, detecting pests, and optimizing irrigation[18],[25].Multispectralandthermalsensorshelp farmers make data-driven decisions, increasing yield and reducingresourcewaste[3].

4.2 Logistics and Delivery

Drone-baseddeliverysystemsaregainingattentionforlastmilelogistics.Optimizedroutingandcoordinationbetween drones and trucks improve efficiency and reduce delivery time [7], [15]. These systems require reliable control and communicationframeworkstoensuresafety.

4.3 Surveillance and Monitoring

Drones are extensively used for surveillance, disaster management, and environmental monitoring due to their flexibilityandcost-effectiveness[8],[9].AI-baseddetection systems enhance situational awareness and real-time response[10].

4.4 Healthcare and Emergency Services

Inhealthcare, dronesareusedto deliver medical supplies suchasblood,vaccines,andemergencykitstoremoteareas [4].Autonomousnavigationandreliablecontrolarecrucial forsafeoperationincriticalscenarios.

5. CHALLENGES AND RESEARCH GAPS

Despite significant advancements, several challenges remain:

 Limitedbatterylifeandendurance

 Communicationdelaysandsecurityvulnerabilities

 Regulatoryandprivacyconcerns

 ReliabilityofAImodelsunderdynamicconditions [16],[19],[20]

There is a need for lightweight security frameworks, adaptivelearningmodels,andstandardizedregulationsto ensuresafedroneintegrationintosharedairspace[21].

6. FUTURE DIRECTIONS

Future research in drone technology is expected to move towardsthedevelopmentoffullyautonomousdronesthat can operate with minimal human intervention. Advanced artificial intelligence techniques will play a key role in designingadaptiveflightcontrolsystemscapableofhandling dynamicenvironments,uncertaincommunicationconditions, and unexpected obstacles. Another important research direction is the development of secure Internet-of-Drones (IoD) frameworks to ensure reliable communication, data integrity,andprotectionagainstcyberthreatsinlarge-scale dronenetworks[21],[22].Inaddition,energy-efficientdrone designs and coordinated swarm operations are gaining increasing attention to improve mission endurance, scalability, and operational efficiency [26]. The combined integration of artificial intelligence, edge computing, and advanced sensing technologies is expected to significantly enhancedroneintelligence,real-timedecision-making,and overall system performance, enabling drones to support morecomplexandcriticalapplicationsinthefuture.

7. CONCLUSION

Thissystematicliteraturereviewpresentsacomprehensive overview of drone technology and control systems. The analysis highlights the critical role of AI and advanced controlalgorithmsinenablingautonomousandintelligent droneoperations.Whiledroneshavetransformedmultiple industries,challengesrelatedtoenergyefficiency,security, andregulationstillpersist.Addressingtheseissueswill be essentialforthelarge-scaledeploymentofsafeandreliable dronesystemsinthefuture.

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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 13 Issue: 02 | Feb 2026 www.irjet.net p-ISSN: 2395-0072

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