Development of RFID dressing robot using DC servo motor with fuzzy-PID control system

Kantawong, Songkran

doi:10.1109/iscit.2013.6645814

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…One of the main elements of Engsys is robot arm manipulator dynamic that deals with the analytical study of the geometry of motion of a Engsys arm with respect to a fixed reference of the system without regard to the forces that cause the motion, thus kinematics deals with the analytical description Engsys as a function of time [4,5].…”

Section: Manipulator Dynamicsmentioning

confidence: 99%

“…Engsys arm dynamics deals with the mathematical formulations of the equations of Engsys arm motion. The dynamic equations of motion of a manipulator are a set of mathematical equations [5,6].…”

Section: Manipulator Dynamicsmentioning

confidence: 99%

“…Since, the Engsys have complicated nonlinear mathematical models. Control systems based on the model are difficult to design [2][3][4][5][6][7]. Controlling the position and velocity of the Engsys axes of motion generates the motion of the end effector.…”

Section: Introductionmentioning

confidence: 99%

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Improving of Engineering System Based on Fuzzy Control in Mechanical Application

.¹

2018

IJRET

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The Engineering System (Engsys) depends on many factors such as: inputs, outputs, and automation. This work contributes the linguistic control for industrial applications. Also, it is the development of a linguistic approach for designing Fuzzy Controller "FC" for Engsys. This paper introduced FC in Engsys (robot arm manipulator dynamic) in the mechanical applications, the constant gains for different points not sufficient to satisfy the performance for Engsys manipulator. Therefore, the knowledgebased FC is proposed ether to meet the operating conditions or to remove any fixed mode. The FC uses the error and the change of error as fuzzy linguistic inputs to satisfy the system performance. The proposed programs are developed to simulate the performance of the Engsys. The new controller uses only the available information of the input-output for controlling the position and velocity of the Engsys axes of the motion of the end effectors.

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Section: Manipulator Dynamicsmentioning

confidence: 99%

Section: Manipulator Dynamicsmentioning

confidence: 99%

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Improving of Engineering System Based on Fuzzy Control in Mechanical Application

.¹

2018

IJRET

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“…Ref. [12] presents a clothdressing robot system, which uses RFID as key elements for data management to command an adaptive cloth-dressing robot control with a fuzzy-PID controller, which is used to adjust the robot's posture. [13] proposes a UHF-RFID mobile robot platform, which uses eight parallel channels for multiple-input multiple-output localization and uses threedimensional product maps for inventory counting but does not consider the identification efficiency and time.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Control Algorithm Based on Q-Learning for UHF Passive RFID Robots in Dynamic Scenarios

Wang

Pan

et al. 2022

Mathematics

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The Identification State (IS) of Radio Frequency Identification (RFID) robot systems changes continuously with the environment, so improving the identification efficiency of RFID robot systems requires adaptive control of system parameters through real-time evaluation of the IS. This paper first expounds on the important roles of the real-time evaluation of the IS and adaptive control of parameters in the RFID robot systems. Secondly, a method for real-time evaluation of the IS of UHF passive RFID robot systems in dynamic scenarios based on principal component analysis (PCA)-K-Nearest Neighbor (KNN) is proposed and establishes an experimental scene to complete algorithm verification. The results show that the accuracy of the real-time evaluation method of IS based on PCA-KNN is 92.4%, and the running time of a single data is 0.258 ms, compared with other algorithms. The proposed evaluation method has higher accuracy and shorter running time. Finally, this paper proposes a Q-learning-based adaptive control algorithm for RFID robot systems. This method dynamically controls the reader’s transmission power and the robot’s moving speed according to the IS fed back by the system; compared with the default parameters, the adaptive control algorithm effectively improves the identification rate of the system, the power consumption under the adaptive parameters is reduced by 36.4%, and the time spent decreases by 29.7%.

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“…Since, the robotic manipulators have complicated nonlinear mathematical models. Control systems based on the system model are difficult to design [1][2][3][4][5][6]. Controlling the position and velocity of the robot axes of motion generates the motion of the end effectors.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Logic Controllerfora Two-Link Functional Manipulator

Hussein¹,

Saleh²

2014

IJCNC

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This paper presents a new approach for designing a Fuzzy Logic Controller "FLC"for a dynamically multivariable nonlinear coupling system. The conventional controller with constant gains for different operating points may not be sufficient to guarantee satisfactory performance for Robot manipulator. The Fuzzy Logic Controller utilizes the error and the change of error as fuzzy linguistic inputs to regulate the system performance. The proposed controller have been developed to simulate the dynamic behavior of A Two-Link Functional Manipulator. The new controller uses only the available information of the inputoutput for controlling the position and velocity of the robot axes of the motion of the end effectors KEYWORDS

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Development of RFID dressing robot using DC servo motor with fuzzy-PID control system

Cited by 7 publications

References 8 publications

Improving of Engineering System Based on Fuzzy Control in Mechanical Application

Improving of Engineering System Based on Fuzzy Control in Mechanical Application

An Adaptive Control Algorithm Based on Q-Learning for UHF Passive RFID Robots in Dynamic Scenarios

A Fuzzy Logic Controllerfora Two-Link Functional Manipulator

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