scholarly journals HYBRID CONTROL SYSTEM IN BIONIC LEG USING MYOWARE SENSOR

2021 ◽  
Vol 56 (4) ◽  
pp. 104-116
Author(s):  
W. Widhiada ◽  
M.A. Parameswara ◽  
I.G.N.N. Santhiarsa ◽  
I.N. Budiarsa ◽  
I.M.G. Karohika ◽  
...  
Keyword(s):  
Control System ◽  
Steady State ◽  
Hybrid Control ◽  
Persons With Disabilities ◽  
Hybrid Controller ◽  
Innovation Product ◽  
Programming Software ◽  
Hybrid Control System ◽  
System Time ◽  
State Error

A bionic robot leg (BRL) is a contrivance used to supersede a loss component of the lower limb due to amputation or congenital disability. Hybrid control of BRL is opted to obtain the maximum performance of BRL equipped with precise forms of kineticism and expeditious response by truncating the error and maximum overshoot and reducing time settle. This research aims to create a BRL innovation product for persons with disabilities at the Bali Puspadi Foundation. The novelty of this BRL is the implementation of the algorithm as outlined in the hybrid control system in the Arduino support package. The BRL utilizes a MyoWare sensor and an Arduino Mega 2560 microcontroller equipped with Matlab/Simulink R2020a programming software. The sensor is utilized to read the angular movement of the DC motor between 0 - 60° degrees and vice versa, following the concept of the gate cycle. The results obtained from the hybrid control simulation are 0.0713% on maximum overshoot, 0.0415% on steady-state error, and 1.292s on system time settle. Furthermore, the results obtained from the hybrid controller experiment are 0.627% on maximum overshoot, 0.257% on steady-state error, and 0.8s on system time settle.

scholarly journals Design and Simulation of Eight-Rotor Unmanned Aerial Vehicle Based on Hybrid Control System

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xueqiang Shen ◽  
Jiwei Fan ◽  
Haiqing Wang
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicle ◽  
Flight Control ◽  
Hybrid Control ◽  
Dynamic Performance ◽  
System Response ◽  
Hybrid Controller ◽  
Aerial Vehicle ◽  
Switching Method ◽  
Hybrid Control System

In order to control the position and attitude of unmanned aerial vehicle (UAV) better in different environments, this study proposed a hybrid control system with backstepping and PID method for eight-rotor UAV in different flight conditions and designed a switching method based on altitude and attitude angle of UAV. The switched process of hybrid controller while UAV taking off, landing, and disturbance under the gust is verified in MATLAB/Simulink. A set of appropriate controllers always matches to the flight of UAV in different circumstances, which can speed up the system response and reduce the steady-state error to improve stability. The simulation results show that the hybrid control system can suppress the drift efficiently under gusts, enhance the dynamic performance and stability of the system, and meet the position and attitude of flight control requirements.

Research on hybrid control system of quadrotor UAV

2013 ◽  
Vol 33 (3) ◽  
pp. 858-861 ◽  
Author(s):  
Guoqing XIA ◽  
Yuefeng LIAO ◽  
Lu WANG
Keyword(s):  
Control System ◽  
Hybrid Control ◽  
Quadrotor Uav ◽  
Hybrid Control System

CMAC Based Hybrid Control System for Solving Electrohydraulic System Nonlinearities

2014 ◽  
Vol 4 (2) ◽  
pp. 47-72
Author(s):  
Amro Shafik ◽  
Magdy Abdelhameed ◽  
Ahmed Kassem
Keyword(s):  
Neural Network ◽  
Control System ◽  
Hybrid Control ◽  
Learning Algorithm ◽  
Cerebellar Model Articulation Controller ◽  
Stick Slip ◽  
Electrohydraulic System ◽  
Cmac Neural Network ◽  
Wide Range ◽  
Hybrid Control System

Automation based electrohydraulic servo systems have a wide range of applications in nowadays industry. However, they still suffer from several nonlinearities like deadband in electrohydraulic valves, hysteresis, stick-slip friction in valves and cylinders. In addition, all hydraulic system parameters have uncertainties in their values due to the change of temperature while working. This paper addresses these problems by designing a suitable intelligent control system that has the ability to deal with the system nonlinearities and parameters uncertainties using a fast and online learning algorithm. A novel hybrid control system based on Cerebellar Model Articulation Controller (CMAC) neural network is presented. The proposed controller is composed of two parallel controllers. The first is a conventional Proportional-Velocity (PV) servo type controller which is used to decrease the large initial error of the closed-loop system. The second is a CMAC neural network which is used as an intelligent controller to overcome nonlinear characteristics of the electrohydraulic system. A fourth order model for the electrohydraulic system is introduced. PV controller parameters are tuned to get optimal values. Simulation and experimental results show a good tracking performance obtained using the proposed controller. The controller shows its robustness in two working environments. The first is by adding different inertia loads and the second is working with noisy level input signals.

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