ARM Rehabilitation Device Controller Based On Fuzzy Logic Techniques

Na Eisyah Sarah, Mustafa (2015) ARM Rehabilitation Device Controller Based On Fuzzy Logic Techniques. Project Report. UTeM, Melaka, Malaysia. (Submitted)

Text (24 pages) ARM Rehabilitation Device Controller Based On Fuzzy Logic Techniques 24 Pages.pdf - Submitted Version Download (409kB)

Abstract

In this thesis, the arm rehabilitation device controller based on fuzzy logic techniques is presented. Patients who has post-stroke may lose control of their upper limb. If they are treated with functional rehabilitation training, the patients can rehabilitate their motion functions and working abilities. These rehabilitation devices are used to recover the movement of arm after stroke. Many controllers had been used for the rehabilitation device and one of them is ANFIS-PID controller where Adaptive Neuro-Fuzzy Inference System (ANFIS) technique is the combination of fuzzy logic and neural network system. The objectives of this project are to develop arm rehabilitation device based on fuzzy logic techniques for rehabilitation. This paper presents the development mathematical modeling of the arm rehabilitation device by using System Identification and to design ANFIS-PID controller. Several transfer function is evaluated in order to represent the best performances for the system. The derived model is validated via simulation and experimental for stability analysis. Whereas the developed ANFIS is purposely as an inverse model to the system and there is a proportional-integral-derivative (PID) controller as a feedback control. EMG model also is integrated to the control system where Artificial Neural Network (ANN) is used to model the EMG. Simulation is conducted using MATLAB to validate the system performance that is integrated with EMG model via simulation. Then the performance is compared between ANFIS-PID controller and PID alone controller. ANFIS–PID controller reduced more tracking error compared to PID controller and demonstrates better results when applied to control system via simulation.

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