Co-simulation research of a novel exoskeleton-human robot system on humanoid gaits with fuzzy-PID/PID algorithms

Pan, Dalei; Gao, Feng; Miao, Yunjie; Cao, Rui

doi:10.1016/j.advengsoft.2014.09.005

Cited by 61 publications

(30 citation statements)

References 22 publications

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“…However , the limitation of PID algorithm is evident that it is adaptation to control the nonlinear and complex system; its parameters can not be tuned on-line. Therefore, a solution is introduced to deal with non-linearity and complexity, which existing the intelligent algorithm such as neural network and fuzzy theory [12].The intelligent algorithm has been widely used, and dose not need precise dynamic model [18]. Developing an adaptive controller by combining fuzzy logic with PID will integrate the advantages of both the fuzzy and PID also will reduce their disadvantages as illustrated from the previous work [13].…”

Section: Figure 2: the Combination Of Humanoid With Exoskeletonmentioning

confidence: 99%

“…The control methodology is key technology in the exoskeleton area. Literatures shows that many types of controllers have been used such as EMG, PID and intelligent algorithms [12].PID control is the widely used for its reliability and simplicity. However PID control may not be very efficient for exoskeleton systems because of the system is complex and nonlinear [13].…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy PID control of lower limb exoskeleton for elderly mobility

Rezage

Tokhi

2016

2016 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR)

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Abstract-This paper presents investigations into the development of an assistive device for elderly mobility. An exoskeleton is designed as an assistive device, to enhance the lower extremity and provide supporting torque to augment the torque of hip and knee during the walking cycle. A humanoid and actuated exoskeleton frame are designed in solid works and then imported to Visual Nastran 4D virtual environment. Fuzzy PID Control algorithm uses to control the actuated exoskeleton. Simulated walking tasks are performed with a humanoid wearing the exoskeleton. It is assumed that the humanoid representing an elderly person, is able to provide 60% of the whole torque required to complete the gait cycle, and the assistive device providing 40% of the overall torque.

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Section: Figure 2: the Combination Of Humanoid With Exoskeletonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fuzzy PID control of lower limb exoskeleton for elderly mobility

Rezage

Tokhi

2016

2016 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR)

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show abstract

“…A controller based on a GA-fuzzyimmune PID, a robot dexterous hand control system, and a mathematical model of an index finger were also presented [17]. Co-simulations of a novel exoskeletonhuman robot system based on humanoid gaits with Fuzzy PID algorithms was presented [3].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy PID control method of deburring industrial robots

Tao

Zheng

Lin

et al. 2015

IFS

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Abstract. This paper proposes a fuzzy PID control method for deburring industrial robots. The adaptive fuzzy PID controller relates to the trajectory and joint angular parameters of the end-effector on a robot. The PID controller parameters update online at each sampling time to guarantee trajectory accuracy of the end-effector. The simulation of the fuzzy PID control is provided based on the 6-DOF deburring industrial robot. Experimental results demonstrate the efficiency of the fuzzy PID control method.

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“…Fuzzy-PID [13] control has been used widely in industrial control. The fuzzy-PID control algorithm is a promising control method for complex nonlinear problems [1,16,21].…”

Section: Introductionmentioning

confidence: 99%

Motion analysis and fuzzy-PID control algorithm designing for the pitch angle of an underwater glider

Liu¹,

Su²,

L³

et al. 2017

J. Math. Computer Sci.

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Underwater gliders are used for deep-water gliding to observe large areas with minimal energy consumption. The pitch angle of the underwater glider is an important control parameter. This study involved designing a fuzzy-PID controller for the pitch angle of an underwater glider based on hydrodynamics analysis. The formula of pitch angle is obtained and a system identification method was used to identify the transfer function based on the time-domain equation and initial experimental data. The fuzzy-PID control algorithm was used to design the controller. Lake and sea trials indicated that the minimum overshoot reached 0% and the settling time was about 34s when the change of the angle was 15 • . The minimum steady-state error was 0.8 • . These advantages could reduce the consumption of energy and improve the accuracy of gliding trajectory. Therefore, this control algorithm should be applied to control the pitch of the gliders.

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Co-simulation research of a novel exoskeleton-human robot system on humanoid gaits with fuzzy-PID/PID algorithms

Cited by 61 publications

References 22 publications

Fuzzy PID control of lower limb exoskeleton for elderly mobility

Fuzzy PID control of lower limb exoskeleton for elderly mobility

Fuzzy PID control method of deburring industrial robots

Motion analysis and fuzzy-PID control algorithm designing for the pitch angle of an underwater glider

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