Fuzzy logic–based decision support system for selection of optimum input shaping techniques in point-to-point motion systems

Bilgiç, Hasan Hüseyin; Conker, Çağlar; Yavuz, Hakan

doi:10.1177/0959651820965705

Cited by 7 publications

(3 citation statements)

References 35 publications

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“…In the fuzzy logic controller, the experience and control strategy of an expert opinion on the system are used as a database. While designing a fuzzy logic controller, in order to get the best efficiency from the controller, the expert who creates the control strategy must know the system very well [28]. The general structure of the fuzzy inference system is given in Figure 9 [29].…”

Section: Control Of 2r-uav Balance System Using Offered Adaptive Fuzz...mentioning

confidence: 99%

Balance Control of Brushless Direct Current Motor Driven Two-Rotor UAV

Cukdar,

Yigit,

Celik

2024

Applied Sciences

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In this study, the balance control of a Brushless Direct Current Motor (BLDCM) driven Two-Rotor UAV (2R-UAV) was carried out. First, a MATLAB/Simulink model of the balance system of the 2R-UAV was built. Afterwards, classical and 2-DOF PID, and proposed Adaptive Fuzzy (AF) 2-DOF PID control structures were created on the STM32F4 microprocessor for both balance angle of the system and speed control of the BLDCMs. Classical and 2-DOF PID controller parameters were determined via Particle Swarm Optimization (PSO), a technique that is commonly used in control applications. For the balance control of the 2R-UAV, a Co-Simulation structure was created using the STM32F4 microprocessor and MATLAB/Simulink, and the performances of classical and 2-DOF PID, and AF 2-DOF PID controllers were examined comparatively. Upon examining the comparison results, it was found that the classical and 2-DOF PID, and AF 2-DOF PID stably controlled the balance of the 2R-UAV. The AF 2-DOF PID controller, proposed in this research, performed better than the classical and 2-DOF PID, especially under variable operating conditions.

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Section: Control Of 2r-uav Balance System Using Offered Adaptive Fuzz...mentioning

confidence: 99%

Balance Control of Brushless Direct Current Motor Driven Two-Rotor UAV

Cukdar,

Yigit,

Celik

2024

Applied Sciences

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“…For the hoisting crane with heavy parts at sea, its operation quality is directly related to the execution efficiency of related work. Because of the relatively heavy lifting weight, it is difficult to adjust the positioning manually [1][2] . In view of this, the positioning research based on heavy lifting crane has attracted more and more attention.…”

Section: Introductionmentioning

confidence: 99%

Research on automatic positioning of hoisting crane for heavy parts at sea based on BIM and RFID technology

Liu

2024

International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023)

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Due to the constraints of crane positioning, its behavior accuracy is relatively low. Therefore, the research on automatic positioning of crane for offshore heavy parts based on BIM and RFID technology is proposed. This paper makes a comprehensive analysis of the positioning constraints of offshore heavy lifting cranes from three perspectives: environmental constraints, operational constraints and safety constraints, and determines the corresponding control elements. In the positioning process, BIM and RFID technology are introduced, and the actual running state data of the hoisting crane is collected with the help of RFID technology. Based on the analysis results of the positioning constraint control elements of the hoisting crane with heavy offshore parts, the identification tag of RFID technology is set up. BIM model is used to decompose the scope of construction area and hoisting tasks in the early stage of hoisting, which is coupled with the data acquisition results of RFID technology to realize the location of specific positions. In the test results, the positioning error of the offshore heavy lifting crane in the X direction is stable within 0.4m, and the positioning error of the offshore heavy lifting crane in the Y direction is stable within 0.3m, which has high accuracy.

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“…Motion systems have been found wide applications in the fields of mechatronics, automation and intelligentization. [1][2][3] High-quality position and velocity signal are the key prerequisites for fast transient and highprecision control of these systems. However, it is always difficult to obtain both position and velocity and large commercially available motion systems only provide high-accuracy position measurement, considering the expense and complex mechanical structures.…”

Section: Introductionmentioning

confidence: 99%

A fast transient tracking differentiator for high-precision motion systems

Wang

2023

Proceedings of the Institution of Mechanical Engineers, Part I:

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High-quality velocity signal plays an important role in fast and precise motion systems, but most commercially available motion systems are not commonly equipped with velocity sensors; hence, full access to the system states is impossible. A fast transient tracking differentiator is proposed in this article for obtaining the noise-less time derivative from a noisy measurement. The fast transient tracking differentiator is conceived within the framework of tracking differentiator methodology and is accomplished by integrating a power-like function with a smooth hyperbolic sine function. Tracking differentiator theory and Lyapunov direct method are employed to show the global asymptotic convergence. Advantages of the proposed fast transient tracking differentiator include the easy implementation with intuitive structure and high computational efficiency and faster transient and higher noise attenuation for both small and large initial estimation errors. The proposed fast transient tracking differentiator can be applied to a large class of motion systems by cascading to a robust output feedback proportional–derivative control for fast and high-precision positioning with position measurement only. Numerical simulation and real-time experimental comparisons demonstrate that the proposed approach provides an easygoing model-free output feedback solution for fast and accurate velocity reconstruction and high-performance positioning of uncertain motion systems with position measurement only.

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Fuzzy logic–based decision support system for selection of optimum input shaping techniques in point-to-point motion systems

Cited by 7 publications

References 35 publications

Balance Control of Brushless Direct Current Motor Driven Two-Rotor UAV

Balance Control of Brushless Direct Current Motor Driven Two-Rotor UAV

Research on automatic positioning of hoisting crane for heavy parts at sea based on BIM and RFID technology

A fast transient tracking differentiator for high-precision motion systems

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