Hybrid genetic algorithm PID control for a five-fingered smart prosthetic hand

Authors:
Cheng-Hung Chen;D. Subbaram Naidu
Affiliations:
Measurement and Control Engineering Research Center, Department of Electrical Engineering and Computer Science School of Engineering, Idaho State University, Pocatello, ID;Measurement and Control Engineering Research Center, Department of Electrical Engineering and Computer Science School of Engineering, Idaho State University, Pocatello, ID
Venue:
ACA'12 Proceedings of the 11th international conference on Applications of Electrical and Computer Engineering
Year:
2012

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An adaptive control strategy for a five-fingered prosthetic hand

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Abstract

A hybrid of soft control technique of adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA) and hard control technique of proportional-integral-derivative (PID) for a five-fingered, smart prosthetic hand is presented. The ANFIS is used for inverse kinematics and GA is used for tuning the PID parameters with the objective of minimizing the error squared between desired and actual angles of the links of the fingers of the prosthetic hand. Simulation results for all the five fingers with GA-tuned PID controller exhibit superior performance compared to the PID control without GA.