scholarly journals A VLSI implementation of elevator control based on finite state machine using Verilog HDL

2018 ◽  
Vol 7 (2.8) ◽  
pp. 92
Author(s):  
Naresh Lagadapati ◽  
Manoj Karri ◽  
Tejaswini Vaddineni ◽  
Sk Mahaboob Subhani ◽  
K Hari Kishore
Keyword(s):  
Finite State Machine ◽  
Control Variable ◽  
Vlsi Implementation ◽  
Verilog Hdl ◽  
Control Module ◽  
Control Framework ◽  
Finite State ◽  
Control Procedures ◽  
High Utilization ◽  
Lift Control

In this cutting edge period, lifts have turned into a basic piece of any business or open complex. It encourages the quicker development of individuals and gear between floors. The lift control framework is a standout amongst the most critical perspectives in hardware control module that are utilized as a part of car application. Normally lifts are intended for a particular building considering the fundamental factors, for example, the tallness of the building, the quantity of individuals venturing out to each floor and the normal times of high utilization. The lift framework is composed with various control procedures. This usage depends on FPGA, which can be utilized for a working with any number of floors, with the predetermined sources of info and yields. This controller can be executed for a lift with the required number of floors by just changing a control variable in the HDL code. This approach depends on a calculation which decreases the measure of calculation required, by concentrating just on the pertinent guidelines that enhances the execution of the gathering of lift framework.

Hierarchical Hybrid Predictive Control of an Autonomous Road Vehicle

2015 ◽  
Author(s):  
Qian Wang ◽  
Thomas Weiskircher ◽  
Beshah Ayalew
Keyword(s):  
Decision Making ◽  
Predictive Control ◽  
Particle Motion ◽  
Vehicle Dynamics ◽  
Finite State Machine ◽  
Road Vehicle ◽  
Reduced Order ◽  
Control Framework ◽  
Finite State ◽  
Trajectory Guidance

This paper presents a hierarchical hybrid predictive control framework for an autonomously controlled road vehicle. At the top, an assigner module is designed as a finite state machine for decision-making. Based on the current information of the controlled vehicle and its environment (obstacles, and lane markings, etc), the assigner selects discrete maneuver states through pre-defined switching rules. The several maneuver states are related to different setups for the underlying model predictive trajectory guidance module. The guidance module uses a reduced-order curvilinear particle motion description of the controlled vehicle and obstacle objects as well as a corresponding description of the reference path, lane and traffic limits. The output of the guidance module interfaces with the lower level controller of the continuous vehicle dynamics. The performance of the proposed framework is demonstrated via simulations of highway-driving scenarios.

MARKOV MATHEMATICAL MODEL OF DYNAMIC ADAPTIVE TESTING OF AN ACTIVE AGENT

2018 ◽  
pp. 29-35
Author(s):  
N. V. Brovka ◽  
P. P. Dyachuk ◽  
M. V. Noskov ◽  
I. P. Peregudova
Keyword(s):  
Mathematical Model ◽  
Finite State Machine ◽  
Active Agent ◽  
Adaptive Testing ◽  
State Machine ◽  
Learning Activities ◽  
Independent Learning ◽  
Complex Object ◽  
Total Reward ◽  
Finite State

The problem and the goal.The urgency of the problem of mathematical description of dynamic adaptive testing is due to the need to diagnose the cognitive abilities of students for independent learning activities. The goal of the article is to develop a Markov mathematical model of the interaction of an active agent (AA) with the Liquidator state machine, canceling incorrect actions, which will allow mathematically describe dynamic adaptive testing with an estimated feedback.The research methodologyconsists of an analysis of the results of research by domestic and foreign scientists on dynamic adaptive testing in education, namely: an activity approach that implements AA developmental problem-solving training; organizational and technological approach to managing the actions of AA in terms of evaluative feedback; Markow’s theory of cement and reinforcement learning.Results.On the basis of the theory of Markov processes, a Markov mathematical model of the interaction of an active agent with a finite state machine, canceling incorrect actions, was developed. This allows you to develop a model for diagnosing the procedural characteristics of students ‘learning activities, including: building axiograms of total reward for students’ actions; probability distribution of states of the solution of the problem of identifying elements of the structure of a complex object calculate the number of AA actions required to achieve the target state depending on the number of elements that need to be identified; construct a scatter plot of active agents by target states in space (R, k), where R is the total reward AA, k is the number of actions performed.Conclusion.Markov’s mathematical model of the interaction of an active agent with a finite state machine, canceling wrong actions allows you to design dynamic adaptive tests and diagnostics of changes in the procedural characteristics of educational activities. The results and conclusions allow to formulate the principles of dynamic adaptive testing based on the estimated feedback.

PENERAPAN FINITE STATE MACHINE UNTUK PENGENDALIAN ANIMASI PADA VIDEO GAME RPG NUSANTARA LEGACY

2018 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Mustofa Mustofa ◽  
Sidiq Sidiq ◽  
Eva Rahmawati
Keyword(s):  
Life Cycle ◽  
Video Game ◽  
Finite State Machine ◽  
Role Playing ◽  
State Machine ◽  
Game Development ◽  
Development Life Cycle ◽  
Finite State ◽  
Role Playing Game

Perkembangan dunia yang dinamis mendorong percepatan perkembangan teknologi dan informasi. Dengan dorongan tersebut komputer yang dulunya dibuat hanya untuk membantu pekerjaan manusia sekarang berkembang menjadi sarana hiburan, permainan, komunikasi dan lain sebagainya. Dalam sektor hiburan salah satu industri yang sedang menjadi pusat perhatian adalah industri video game. Begitu banyaknya produk video game asing yang masuk ke dalam negeri ini memberikan tantangan kepada bangsa ini. Tentunya video game asing yang masuk ke negara ini membawa banyak unsur kebudayaan negara lain. Ini semakin membuat kebudayaan nusantara semakin tergeserkan dengan serangan kebudayaan asing melalui berbagai media. Maka dari itu peneliti mencoba untuk menerapkan Finite State Machine dalam merancang sebuah video game RPG (Role-Playing game) yang memperkenalkan kebudayaan. Dalam perancangan video game ini peneliti menggunakan metode GDLC(Game Development Life Cycle) agar penelitian ini berjalan secara sistematis. Dalam suatu perancangan video game tedapat banyak elemen, pada penelitian ini penulis lebih fokus pada pengendalian animasi karakter yang dimainkan pada video game ini. Dari perancangan yang dilakukan, disimpulkan bahwa Finite State Machine dapat digunakan untuk pengendalian animasi yang baik pada video game RPG. Diharapkan video game ini dapat menjadi salah satu media untuk mengenalkan kebudayaan nusantara

Human action recognition using simple geometric features and a finite state machine

2013 ◽  
Vol 18 (2-3) ◽  
pp. 49-60 ◽  
Author(s):  
Damian Dudzńiski ◽  
Tomasz Kryjak ◽  
Zbigniew Mikrut
Keyword(s):  
Action Recognition ◽  
Finite State Machine ◽  
Recognition Rate ◽  
Human Action Recognition ◽  
Human Action ◽  
Video Stream ◽  
State Machine ◽  
Recognition Algorithm ◽  
Finite State ◽  
Correct Recognition Rate

Abstract In this paper a human action recognition algorithm, which uses background generation with shadow elimination, silhouette description based on simple geometrical features and a finite state machine for recognizing particular actions is described. The performed tests indicate that this approach obtains a 81 % correct recognition rate allowing real-time image processing of a 360 X 288 video stream.

User permission isolation model based on finite state machine

2013 ◽  
Vol 33 (1) ◽  
pp. 149-152
Author(s):  
Jianjun LI ◽  
Yixiang JIANG ◽  
Jie QIAN ◽  
Wei LI ◽  
Yu LI
Keyword(s):  
Finite State Machine ◽  
State Machine ◽  
Model Based ◽  
Finite State

scholarly journals Data Driven Modelling of Nuclear Power Plant Performance Data as Finite State Machines

Modelling ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 43-62
Author(s):  
Kshirasagar Naik ◽  
Mahesh D. Pandey ◽  
Anannya Panda ◽  
Abdurhman Albasir ◽  
Kunal Taneja
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Finite State Machine ◽  
State Machine ◽  
Plant Performance ◽  
Series Data ◽  
Cyberphysical Systems ◽  
Finite State ◽  
Machine Representation

Accurate modelling and simulation of a nuclear power plant are important factors in the strategic planning and maintenance of the plant. Several nonlinearities and multivariable couplings are associated with real-world plants. Therefore, it is quite challenging to model such cyberphysical systems using conventional mathematical equations. A visual analytics approach which addresses these limitations and models both short term as well as long term behaviour of the system is introduced. Principal Component Analysis (PCA) followed by Linear Discriminant Analysis (LDA) is used to extract features from the data, k-means clustering is applied to label the data instances. Finite state machine representation formulated from the clustered data is then used to model the behaviour of cyberphysical systems using system states and state transitions. In this paper, the indicated methodology is deployed over time-series data collected from a nuclear power plant for nine years. It is observed that this approach of combining the machine learning principles with the finite state machine capabilities facilitates feature exploration, visual analysis, pattern discovery, and effective modelling of nuclear power plant data. In addition, finite state machine representation supports identification of normal and abnormal operation of the plant, thereby suggesting that the given approach captures the anomalous behaviour of the plant.

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