Paper Machine Industrial Analysis on Moisture Control Using BF-PSO Algorithm and Real Time Implementation Setup through Embedded Controller

Rapid advancements in Software Verification and Validation have been critical in the wide development of tools and techniques to identify potential Concurrent bugs and hence verify the software correctness. A concurrent program has multiple processes and shared objects. Each process is a sequential program and they use the shared objects for communication for completion of a task. The primary objective of this survey is retrospective review of different tools and methods used for the verification of real-time concurrent software. This paper describes the proposed tool ‘F-JAVA’ for multithreaded Java codebases in contrast with existing ‘FRAMA-C’ platform, which is dedicated to real-time concurrent C software analysis. The proposed system is comprised of three layers, namely Programming rules generation stage, Verification stage with Particle Swarm Optimization (PSO) algorithm, and Performance measurement stage. It aims to address some of the challenges in the verification process such as larger programs, long execution times, and false alarms or bugs, and platform independent code verification

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Real-Time Order Acceptance and Scheduling Problems in a Flow Shop Environment Using Hybrid GA-PSO Algorithm

IEEE Access ◽

10.1109/access.2019.2935375 ◽

2019 ◽

Vol 7 ◽

pp. 112742-112755 ◽

Cited By ~ 2

Author(s):

Humyun Fuad Rahman ◽

Mukund Nilakantan Janardhanan ◽

Izabela Ewa Nielsen

Keyword(s):

Real Time ◽

Flow Shop ◽

Pso Algorithm ◽

Scheduling Problems ◽

Order Acceptance ◽

Time Order ◽

Order Acceptance And Scheduling

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Design real-time embedded optimal PD fuzzy controller by PSO algorithm for autonomous vehicle mounted camera

10.1063/1.5138401 ◽

2019 ◽

Author(s):

N. X. Chiem ◽

N. D. Anh ◽

A. D. Lukianov ◽

P. D. Tung ◽

H. D. Long ◽

...

Keyword(s):

Real Time ◽

Fuzzy Controller ◽

Autonomous Vehicle ◽

Pso Algorithm

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IT Assembly Process Gripper Real-Time Embedded System Design

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.865.463 ◽

2017 ◽

Vol 865 ◽

pp. 463-467

Author(s):

Sun Lim ◽

Hak Sang Jung ◽

Seung Yong Lee ◽

Young Woo Park ◽

Il Kyun Jung

Keyword(s):

Embedded System ◽

System Design ◽

Real Time ◽

Functional Ability ◽

Robot Manipulator ◽

Assembly Process ◽

Robot Controller ◽

Embedded Controller ◽

Process Operation ◽

Ethernet Interface

In this paper we propose the gripper handle real-time based embedded system for operating robot manipulator. The general gripper has only a simple function and has also I/O module. Thus general gripper and position based robot controller combination is not suitable for precision process operation, IT assembly process. In order to give various functions and intelligence to the gripper, it is necessary to have an embedded controller that real-time guarantees. The proposed embedded system have five component that handle the pose of the gripper, measure the pose and translation of gripper, motoring the gripping tip, operate the stiffness of the gripper and communicate with Ethernet interface to the external robot controller. The external robot interface parts are supported to communicate with various external robot maker, KUKA, DENSO, ROBOSTAR etc. The validation and functional ability is tested on the LAB environment.

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Real-time detection of microgrid islanding considering sources of uncertainty using type-2 fuzzy logic and PSO algorithm

PLoS ONE ◽

10.1371/journal.pone.0257830 ◽

2021 ◽

Vol 16 (9) ◽

pp. e0257830

Author(s):

Taghi Hosseinzadeh Khonakdari ◽

Mehrdad Ahmadi Kamarposhti

Keyword(s):

Fuzzy Logic ◽

Real Time ◽

Pso Algorithm ◽

Suggested Method ◽

Islanding Detection ◽

Sources Of Uncertainty ◽

Real Time Detection ◽

Sample System ◽

Made In

In this paper, a new innovative type-2 fuzzy-based for microgrid (MG) islanding detection is proposed in the condition of uncertainties. Load and generation uncertainties are two main sources of uncertainties in microgrids (MGs). Regardless of the uncertainties, the results cannot be confirmed. The proposed controller detects islanding in the fastest time under different conditions, and the uncertainties in the system will not considerably affect the controller’s performance. The proposed method is simulated on the sample system and examined in different scenarios. Then, a comparison is made in different conditions and scenarios between the suggested method and some common methods that have been presented so far to demonstrate the ability of the proposed method for islanding detection.

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Model Predictive Control for Automatic Carrier Landing with Time Delay

International Journal of Aerospace Engineering ◽

10.1155/2021/8613498 ◽

2021 ◽

Vol 2021 ◽

pp. 1-19

Author(s):

Kaikai Cui ◽

Wei Han ◽

Yujie Liu ◽

Xinwei Wang ◽

Xichao Su ◽

...

Keyword(s):

Time Delay ◽

Model Predictive Control ◽

Real Time ◽

Predictive Control ◽

Estimation Error ◽

Estimation Algorithm ◽

Pso Algorithm ◽

Delay Estimation ◽

Control Block ◽

Landing Control

This paper focuses on the problem of automatic carrier landing control with time delay, and an antidelay model predictive control (AD-MPC) scheme for carrier landing based on the symplectic pseudospectral (SP) method and a prediction error method with particle swarm optimization (PE-PSO) is designed. Firstly, the mathematical model for carrier landing control with time delay is given, and based on the Padé approximation (PA) principle, the model with time delay is transformed into an equivalent nondelay one. Furthermore, a guidance trajectory based on the predicted trajectory shape and position deviation is designed in the MPC framework to eliminate the influence of carrier deck motion and real-time error. At the same time, a rolling optimal control block is designed based on the SP algorithm, in which the steady-state carrier air wake compensation is introduced to suppress the interference of the air wake. On this basis, the PE-PSO delay estimation algorithm is proposed to estimate the unknown delay parameter in the equivalent control model. The simulation results show that the delay estimation error of the PE-PSO algorithm is smaller than 2 ms, and the AD-MPC algorithm proposed in this paper can limit the landing height error within ±0.14 m under the condition of multiple disturbances and system input delay. The control accuracy of AD-MPC is much higher than that of the traditional pole assignment algorithm, and its computational efficiency meets the requirement of real-time online tracking.

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Nonlinear Modeling of Moisture Control of Drying Process in Paper Machine

Procedia Engineering ◽

10.1016/j.proeng.2012.06.139 ◽

2012 ◽

Vol 38 ◽

pp. 1104-1111 ◽

Cited By ~ 6

Author(s):

C. Karthik ◽

K. Valarmathi ◽

M. Rajalakshmi

Keyword(s):

Nonlinear Modeling ◽

Paper Machine ◽

Drying Process ◽

Moisture Control

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An Experimental Autonomous Path Tracking Mobile Robot

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.62-64.181 ◽

2009 ◽

Vol 62-64 ◽

pp. 181-186 ◽

Cited By ~ 1

Author(s):

Hasitha M. B. Senanayake ◽

Olaitan Akinsanmi ◽

Muhammed Bashir Mu’azu

Keyword(s):

Mobile Robot ◽

Real Time ◽

Optical Sensors ◽

Low Cost ◽

Path Tracking ◽

Detection And Tracking ◽

Embedded Controller ◽

Important Notion ◽

Path Detection

Autonomous Vehicular Navigation poses interesting challenges and, Automatically Guided Vehicle (AGV) Path Tracking presents an important notion in real-time Mechatronics applications. This paper describes the design of a Path Tracking Automatically Guided Vehicle that is capable of autonomously navigating a predefined path on a level navigating plane and, the designed AGV successfully completed a 3.42 meter test course in precisely 2 minutes 16 seconds. The AGV comprises a PIC16F84A microcontroller utilized as an embedded controller and, an array of Infrared reflective optical sensors to enable path detection and tracking. Among the primary objectives of the design that were achieved was to design the low-cost mobile robot from component parts sourced locally, from within Nigeria.

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An Adaptive Chaos Quantum-Behaved Particle Swarm Optimization Algorithm for Real-Time Dispatch in Power System with Wind Generation

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1070-1072.297 ◽

2014 ◽

Vol 1070-1072 ◽

pp. 297-302

Author(s):

Zhi Kui Wu ◽

Chang Hong Deng ◽

Yong Xiao ◽

Wei Xing Zhao ◽

Qiu Shi Xu

Keyword(s):

Particle Swarm Optimization ◽

Power System ◽

Real Time ◽

Wind Power ◽

Wind Farm ◽

Particle Swarm ◽

Pso Algorithm ◽

Swarm Optimization ◽

Good Convergence ◽

Proposed Model

A real-time dispatch (RTD) model for wind power incorporated power system aimed at maximizing wind power utilization and minimizing fuel cost is proposed in this paper. To cope with the prematurity and local convergence of conventional particle swarm optimization (PSO) algorithm, a novel adaptive chaos quantum-behaved particle swarm optimization (ACQPSO) algorithm is put forward. The adaptive inertia weight and chaotic perturbation mechanism are employed to improve the particle’s search efficiency. Numerical simulation on a 10 unit system with a wind farm demonstrates that the proposed model can maximize wind power utilization while ensuring the safe and economic operation of the power system. The proposed ACQPSO algorithm is of good convergence quality and the computation speed can meet the requirement of RTD.

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