Research on the Attitude Control of Civil Quad-Rotor UAV Based on Fuzzy PID Control

Sheng, Guangrun; Gao, Guowei

doi:10.1109/ccdc.2019.8832855

Cited by 10 publications

(5 citation statements)

References 6 publications

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“…So, in recent years, there has been a notable shift towards the implementation of intelligent control systems for the automation of UAVs, and among these, systems founded on fuzzy logic have emerged as particularly promising [39][40][41]. Fuzzy logic control leverages a flexible and adaptive approach to decision-making, allowing for nuanced responses to complex and uncertain environments [42][43][44].…”

Section: Brief Literature Reviewmentioning

confidence: 99%

“…Fuzzy controllers excel at capturing the nuances of imprecise and non-linear relationships within dynamic environments. By utilizing linguistic variables and intuitive rules, these controllers mimic human decision-making processes, enabling them to effectively handle the vagaries and uncertainties inherent in complex plants [40][41][42]. Such complex plants may include robotic systems, power plants, chemical industry facilities, alternative energy installations, etc.…”

Section: Main Tasks and Designing Principlesmentioning

confidence: 99%

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Intelligent IoT-based Control System of the UAV for Meteorological Measurements

Kozlov,

Kondratenko,

Skakodub

2024

JMM

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This study focuses on the creation and examination of an intelligent automated control system for UAVs utilized in meteorological measurements based on the Internet of Things (IoT) and mobile technologies. The proposed system enables the achievement of commendable flight control standards for UAVs during meteorological data gathering, thereby markedly enhancing the overall effectiveness of meteorological stations. Notably, this system is constructed on the foundation of three integrated principles: (a) a hierarchical two-level approach for control and data collection based on IoT and mobile technologies, (b) a straightforward and dependable fuzzy logic control characterized by high performance, and (c) the effective optimization of fuzzy control components through the application of bio-inspired multi-agent computing techniques. To assess the performance of the suggested intelligent system, this study involves the creation and bioinspired optimization of the climb speed fuzzy controller. Subsequent simulation experiments are conducted to evaluate the automatic control of UAV’s flight processes under different modes. The analysis of the simulation results indicates that the developed system, utilizing fuzzy control, exhibits superior efficiency and higher quality metrics when compared to existing counterparts, especially in diverse flight scenarios such as uniform climbing, gradual approach to designated altitude levels, and smooth landing during meteorological measurements.

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Section: Brief Literature Reviewmentioning

confidence: 99%

Section: Main Tasks and Designing Principlesmentioning

confidence: 99%

Intelligent IoT-based Control System of the UAV for Meteorological Measurements

Kozlov,

Kondratenko,

Skakodub

2024

JMM

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“…However, its effectiveness in dynamic environments is yet to be verified. [123] addressed the problem that the quadrotor load and its strong coupling characteristics would cause large interference to the flight control performance, a comprehensive analysis of the classical PID system and the fuzzy control PID system was carried out, and the previous method of frequent adjustment of PID parameters was replaced by designing and improving the fuzzy control rule table. MATLAB simulations show that the method can improve the adaptability of PID and reduce the instability of flight attitude control during operation.…”

Section: A Research On Pid Controlmentioning

confidence: 99%

A Survey of Indoor UAV Obstacle Avoidance Research

Xiong

Yan

et al. 2023

IEEE Access

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UAV obstacle avoidance technology is one of the key factors to realize UAV autonomous flight, efficient and accurate obstacle avoidance is significant to complete the UAV autonomous flight task. In contrast, the dynamic, real-time and uncertainty of the environment in which the UAV is located makes the problem very tricky, especially in the indoor environment. At present, a large number of scholars have shown strong interest in the indoor UAV obstacle avoidance problem. With the rapid development of computer technology and hardware devices, many intelligent algorithms have been proposed to solve the obstacle avoidance problem. However, the research on indoor UAV obstacle avoidance technology is not comprehensive enough, and there is a lack of summarization of the research results in recent years. This paper introduces the sensor modules commonly used for indoor UAV environment sensing, related obstacle avoidance methods based on sensory detection. Classifies and composes the commonly used UAV path planning obstacle avoidance algorithms, and gives several representative UAV flight control research methods. This paper summarizes the advantages and disadvantages of different perception modules and detection methods applied to UAV obstacle avoidance tasks, and compares various current path planning methods. Finally, the critical difficulties and challenges faced in the field of indoor UAV obstacle avoidance are discussed, and future research in the field of UAV obstacle avoidance has prospected.

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“…PID controllers for quadrotors have been successfully used by numerous studies [5], [6]. Some researchers have modified the standard PID and achieved good results in improving flight stability and control accuracy [7], [8].…”

Section: Linear Controllersmentioning

confidence: 99%

Comparative analysis and the prospect of flight control strategies and performance of quadrotor UAV

Wang

2023

ACE

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Quadcopter UAVs are increasingly used for military and civilian applications such as surveillance, reconnaissance, pesticide spraying, and traffic monitoring due to their simplicity of operation, ease of attitude adjustment, and ability to take off and land vertically. The flight control system is the key to the aircraft's ability to perform flight tasks. However, when faced with external disturbances, obstacles, and uncertain parameters, traditional PID control is unable to meet the demands of complex flight tasks. Research on more advanced control strategies is the trend of future development. This paper surveys the flight control methods of quadrotor UAVs in the past two decades and classifies and introduces these methods one by one. Finally, the experimental feasibility of these methods is discussed, the advantages and disadvantages of these methods are briefly compared, and the future development trend of UAV flight control systems is analyzed. An important reference is provided for the development of quadrotor UAV flight control algorithm research.

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Research on the Attitude Control of Civil Quad-Rotor UAV Based on Fuzzy PID Control

Cited by 10 publications

References 6 publications

Intelligent IoT-based Control System of the UAV for Meteorological Measurements

Intelligent IoT-based Control System of the UAV for Meteorological Measurements

A Survey of Indoor UAV Obstacle Avoidance Research

Comparative analysis and the prospect of flight control strategies and performance of quadrotor UAV

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