showing 3 related works from this author
Non-linear active disturbance rejection control for upper limb rehabilitation exoskeleton
2020
Trajectory tracking in upper limb rehabilitation exercises is utilized for repeatability of joint movement to improve the patient’s recovery in the early stages of rehabilitation. In this article, non-linear active disturbance rejection control as a combination of non-linear extended-state observer and non-linear state error feedback is used for the sinusoidal trajectory tracking control of the two-link model of an upper limb rehabilitation exoskeleton. The two links represent movements like flexion/extension for both the shoulder joint and the elbow joint in the sagittal plane. The Euler–Lagrange method was employed to acquire a dynamic model of an upper limb rehabilitation exoskeleton. T…
Improved Active Disturbance Rejection Control for Trajectory Tracking Control of Lower Limb Robotic Rehabilitation Exoskeleton.
2020
Neurological disorders such as cerebral paralysis, spinal cord injuries[acronym](SCI), and strokes, result in the impairment of motor control and induce functional difficulties to human beings like walking, standing, etc. Physical injuries due to accidents and muscular weaknesses caused by aging [english]affectsaffect people and can cause them to lose their ability to perform daily routine functions. In order to help people recover or improve their dysfunctional activities and quality of life after accidents or strokes, assistive devices like exoskeletons and orthoses are developed. Control strategies for control of exoskeletons are developed with the desired intention of improving the qual…
Multi-Agent Based Energy Management in Microgrids Using MACSimJX
2019
Excessive growth in electricity consumption has been experienced over the past few years due to an increase in population around the world.This tends to increase the use of renewable energy and randomness of the load. So.it is important to improve the traditional methodologies and techniques applied on microgrid to make it more intelligent. In this paper, multi agent system is employed over autonomous microgrid framework to endorse its intelligence. The Multi-Agent system is simulated in Java Agent Development Environment (JADE) environment and matlab toolbox Simulink is used for the implementation of the microgrid model. Further, MACSimJX is used to communicate between the micro grid and a…