International Review of Automatic Control

Silvianita Silvianita

Farel Noval Jamaluddin

Wimala Lalitya Dhanistha

Suntoyo Suntoyo

Dendy Satrio

Wahyudi Wahyudi

International Review of Automatic Control (IREACO)

Fuzzy Logic Approach to Risk Management and Control for Safe Work in Jacket Structure Load Out Process

基于模糊逻辑的导管架结构装船过程风险管理与控制方法研究

Abdullah Elsayed Elewa

Amal F. Abd EL Gawad

Mohammed A. Farahat

Waheed Sabry

A Dynamic Virtual Inertia Controller Testing to Improve Load Frequency Efficacy of a Power System Penetrated with Renewable Energy Sources

动态虚拟惯性控制器测试以提高可再生能源渗透电力系统的负荷频率效能

Mohamed Bakir

My Abdelkader Youssefi

Rachid Dakir

Mouna El Wafi

Enhancing the PRM Algorithm: an Innovative Method to Overcome Obstacles in Self-Driving Car Path Planning

增强PRM算法：一种克服自动驾驶汽车路径规划障碍的创新方法

Zahraa A. Abdullah

Nabil Hassan Hadi

Autonomous Obstacle Avoidance for Skid Steering Mobile Robot Based on Fuzzy Logic

基于模糊逻辑的滑移转向移动机器人自主避障

Convolution Neural Networks are used with a Reinforcement Learning algorithm to control a robotic arm. The objective is to move the end-effector to a desired position using minimum actions without prior knowledge of the robot’s structure nor its mathematical model. The proposed methodology processes camera images from the environment and inputs this information as raw pixels to the agent. Then, Deep Q-Network algorithm trains the agent to provide the appropriate actions based on a value function that estimates future rewards. An experience replay feature is used to improve the agent’s performance by memorizing the highest rewarded-sequence of actions episode and replays it when needed. Simulation runs, using the graphical robotic simulator CoppeliaSim, validate the proposed algorithm as the agent provides the optimal number of actions to move the robot’s end-effector to the desired target using camera images as inputs. Four different cases are presented and the results show that the proposed algorithm can reduce the number of required actions significantly.

Abdullah Al-Zabt

Tarek A. Tutunji

Robotic Manipulator Control Using CNN and Deep Q-Network Algorithm

使用CNN和深度Q网络算法的机器人操作臂控制

Wilson Edmundo Sánchez-Ocaña

Washington Eduardo Loza-Herrera

Daniel Esteban Cabezas-Montero

Martha Elizabeth Salazar-Jácome

Local and Remote Control and Monitoring Through SmartClient and WebServer of an Industrial Network of an S7-1200 and a LOGO! PLC Based on the Industrial Ethernet Protocol for Electro-Pneumatic Processes

基于工业以太网协议的S7-1200和LOGO! PLC工业网络的智能客户端和Web服务器本地及远程控制与监控用于电-气动过程

ISSN	1974-6059, 1974-6067, 2533-2260
h-index	16

Publication Information	Publisher: Praise Worthy Prize S.r.l，Publishing cycle: ，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 2012，Proportion of original research papers: 0.00%，Self Citation Rate:N.A.， Gold OA Rate: 0.00%

International Review of Automatic Control

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Fuzzy Logic Approach to Risk Management and Control for Safe Work in Jacket Structure Load Out Process

A Dynamic Virtual Inertia Controller Testing to Improve Load Frequency Efficacy of a Power System Penetrated with Renewable Energy Sources

Enhancing the PRM Algorithm: an Innovative Method to Overcome Obstacles in Self-Driving Car Path Planning

Autonomous Obstacle Avoidance for Skid Steering Mobile Robot Based on Fuzzy Logic

Robotic Manipulator Control Using CNN and Deep Q-Network Algorithm

Fuzzy Logic Approach to Risk Management and Control for Safe Work in Jacket Structure Load Out Process

A Dynamic Virtual Inertia Controller Testing to Improve Load Frequency Efficacy of a Power System Penetrated with Renewable Energy Sources

Enhancing the PRM Algorithm: an Innovative Method to Overcome Obstacles in Self-Driving Car Path Planning

Autonomous Obstacle Avoidance for Skid Steering Mobile Robot Based on Fuzzy Logic

Local and Remote Control and Monitoring Through SmartClient and WebServer of an Industrial Network of an S7-1200 and a LOGO! PLC Based on the Industrial Ethernet Protocol for Electro-Pneumatic Processes