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Development of a GA-fuzzy-immune PID controller with incomplete derivation for robot dexterous hand.

Liu XH, Chen XH, Zheng XH, Li SP, Wang ZB - ScientificWorldJournal (2014)

Bottom Line: The control system of a robot dexterous hand and mathematical model of an index finger were presented.Moreover, immune mechanism was applied to the controller design and an improved approach through integration of GA and fuzzy inference was proposed to realize parameters' optimization.Finally, a simulation example was provided and the designed controller was proved ideal.

View Article: PubMed Central - PubMed

Affiliation: School of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, China ; Xuyi Mine Equipment and Materials R&D Center, China University of Mining and Technology, Huai'an 211700, China.

ABSTRACT
In order to improve the performance of robot dexterous hand, a controller based on GA-fuzzy-immune PID was designed. The control system of a robot dexterous hand and mathematical model of an index finger were presented. Moreover, immune mechanism was applied to the controller design and an improved approach through integration of GA and fuzzy inference was proposed to realize parameters' optimization. Finally, a simulation example was provided and the designed controller was proved ideal.

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Unit step responses of system.
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Related In: Results  -  Collection


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fig8: Unit step responses of system.

Mentions: The input of robot dexterous hand system is a unit step signal and the simulation time is 1 s. The unit step responses of this system are shown in Figure 8. The first curve is response obtained with fuzzy inference, the second curve is response obtained with immune algorithm, the third curve is response obtained with fuzzy-immune inference (F-I), the fourth curve is response obtained with real-coded GA, and the fifth curve is response obtained through integration of improved genetic algorithm and fuzzy-immune inference (GA-F-I).


Development of a GA-fuzzy-immune PID controller with incomplete derivation for robot dexterous hand.

Liu XH, Chen XH, Zheng XH, Li SP, Wang ZB - ScientificWorldJournal (2014)

Unit step responses of system.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4109120&req=5

fig8: Unit step responses of system.
Mentions: The input of robot dexterous hand system is a unit step signal and the simulation time is 1 s. The unit step responses of this system are shown in Figure 8. The first curve is response obtained with fuzzy inference, the second curve is response obtained with immune algorithm, the third curve is response obtained with fuzzy-immune inference (F-I), the fourth curve is response obtained with real-coded GA, and the fifth curve is response obtained through integration of improved genetic algorithm and fuzzy-immune inference (GA-F-I).

Bottom Line: The control system of a robot dexterous hand and mathematical model of an index finger were presented.Moreover, immune mechanism was applied to the controller design and an improved approach through integration of GA and fuzzy inference was proposed to realize parameters' optimization.Finally, a simulation example was provided and the designed controller was proved ideal.

View Article: PubMed Central - PubMed

Affiliation: School of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, China ; Xuyi Mine Equipment and Materials R&D Center, China University of Mining and Technology, Huai'an 211700, China.

ABSTRACT
In order to improve the performance of robot dexterous hand, a controller based on GA-fuzzy-immune PID was designed. The control system of a robot dexterous hand and mathematical model of an index finger were presented. Moreover, immune mechanism was applied to the controller design and an improved approach through integration of GA and fuzzy inference was proposed to realize parameters' optimization. Finally, a simulation example was provided and the designed controller was proved ideal.

Show MeSH