A torque estimator using online tuning grey fuzzy PID for applications to torque-sensorless control of DC motors

Liem, Dao Thanh; Dinh, Truong Quang; Ahn, Kyoung Kwan

doi:10.1016/j.mechatronics.2015.01.004

Cited by 33 publications

(13 citation statements)

References 29 publications

(40 reference statements)

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“…It is assumed that the dynamical model ( 11) is determined exactly for the PD-type computed torque controller, whereas PIDtype computed torque controller only uses exact values of M, , G, Q*, and Q is unknown. Especially, the fuzzy controller does not use dynamical equations (11) to adjust control force/torque U.…”

Section: Kinematic Analysismentioning

confidence: 99%

A control solution for closed-form mechanisms of relative manipulation based on fuzzy approach

Toan

Khôi

2019

International Journal of Advanced Robotic Systems

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Closed-form mechanisms of relative manipulation robot is an effective structure which helps to improve the accuracy and flexibility in technological processes. Unfortunately, the requirement about knowledge of exact dynamics of closed-form mechanisms of relative manipulation robot is arduous since it consists of numerous joints and links, and the identification of the kinematic relationship of closed-form structure is also complicated. This causes several shortcomings for controlling closed-form mechanisms of relative manipulation robot by using vector control algorithms because these methods require exactly dynamical equations of control systems. In contrast, the fuzzy controllers do not require knowledge of detailed mathematical equations of the control system since the fuzzy sets aim to capture the semantics of natural linguistic terms present in the fuzzy controller knowledge. Moreover, they have capability of handling uncertain and noisy signals, this helps to deal with the external environmental forces. This article proposes a fuzzy-based controller for closed-form mechanisms of relative manipulation robot to overcome mentioned problems by eliminating the identification of exact dynamics and kinematic constraints of closed-form structure. To verify the performance of the proposed method, the fuzzy-based controller is applied to a welding task by using a model of two-component mechanism which includes one closed-form manipulator and one serial manipulator. The welding task is also conducted by using conventional controllers in which the detailed dynamical equation is applied for the proportional-derivative (PD)-type and proportional integral derivative (PID)type computed torque controllers, whereas the fuzzy-based controller just uses several nominal parameters.

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Section: Kinematic Analysismentioning

confidence: 99%

A control solution for closed-form mechanisms of relative manipulation based on fuzzy approach

Toan

Khôi

2019

International Journal of Advanced Robotic Systems

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“…At present, it is often used to test the parameters of PID control algorithm [8][9][10] of intelligent car. Due to the lack of the necessary theoretical guidance and lack of experience, we often waste a lot of time in the adjustment process.…”

Section: Figure 1 Runway Loading Modulementioning

confidence: 99%

Design of Experimental Platform for Intelligent Car

Yu¹,

Wang²,

Wang³

et al. 2017

Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)

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Abstract. Based on the study of the principle of intelligent car movement, this paper designs the tracking process, the PID adjustment process, the real-time monitoring process, and displays the simulation interface on the intelligent car software platform. So that the simulation results can be used to determine the scope of the actual adjustment results to facilitate the adjustment of the actual debugging process. The simulation experiment is done on the experimental platform, and the rationality of the simulation platform and the effectiveness of the path tracking control algorithm are verified by analyzing the debugging results of the actual intelligent car.

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“…2017, 9(4S), 160-172 162 been applied to improve the robustness and hybrid control of fuzzy and PID. In the meantime, Fuzzy PID controllers are used in many applications such as speed control, robot manipulator and DC motor [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Modeling and controller design on ARX model of Electro-Hydrolic actuator

Ishak¹,

Hamdan²,

Tajuddin³

et al. 2018

J. Fundam and Appl Sci.

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Electro-hydraulic actuator (EHA) is commonly used in industry for its linear movement, quick response and accurate positioning of heavy loads. However, the uncertainties, highly nonlinearities and time varying characteristic of EHA caused difficulties in controlling the system. This paper studies the performance of Fuzzy PID controller on ARX model parameters of vertical position of electro obtained via system identification technique using MATLAB Toolbox. The performance of the controller is analyzed through simulation by using step and square type reference input.

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A torque estimator using online tuning grey fuzzy PID for applications to torque-sensorless control of DC motors

Cited by 33 publications

References 29 publications

A control solution for closed-form mechanisms of relative manipulation based on fuzzy approach

A control solution for closed-form mechanisms of relative manipulation based on fuzzy approach

Design of Experimental Platform for Intelligent Car

Modeling and controller design on ARX model of Electro-Hydrolic actuator

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