Diseño de interfaz gráfica para analizar el ciclo de marcha del cuerpo humano en software libre

Currently in the country there are more than 27 thousand cases of annual amputations and more than 80% correspond to lower limbs, therefore, the demand for prosthetic equipment is greater than what the health sector institutions can provide. It should be noted that the equipment developed by these institutions is only passive equipment, so that only 10% of patients who receive a prosthetic equipment successfully complete their rehabilitation. The main problems that the patient faces when adapting to their prosthetic equipment is the response time and alignment vs the healthy limb, since it does not have an intelligent control system that allows them to respond in real time as the losted limb did. This causes gaps when performing your gait cycle, this over time can bring about abnormalities in your posture affecting the alignment of your motor system. This work allows us to analyze the range of motion of the ankles and knees, in addition to determining the angular velocity of both, it is essential information for the development of control systems necessary for active prosthetic equipment. The programming language where it was developed is the Python 3.7 software and additionally reproduce the simulation of the gait cycle.

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Model of an intelligent control system for an irrigation complex

The Agrarian Scientific Journal ◽

10.28983/asj.y2021i2pp103-108 ◽

2021 ◽

pp. 103-108

Author(s):

Dmitry Aleksandrovich Solovyev ◽

Galina Nickolaevna Kamyshova ◽

Dmitry Alexandrovich Kolganov ◽

Nadezhda Nickolaevna Terekhova

Keyword(s):

Control System ◽

Control Systems ◽

Intelligent Control ◽

Process Automation ◽

Automated Control ◽

Simple Process ◽

Intelligent Control System ◽

Irrigation Technologies ◽

Traditional Approaches ◽

Precision Irrigation

The article presents the results of modeling an intelligent control system for an irrigation complex. The introduction of precision irrigation technologies requires the development of new approaches to technical support. Traditional approaches based on simple process automation often do not lead to effective solutions. An approach based on the model of intellectualization of automated control systems is proposed. The structure of the intelligent control system for the irrigation complex is substantiated, which is based on an artificial neural network.

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Expert Guided Autonomous Mobile Robot Learning

Knowledge-Based Intelligent System Advancements ◽

10.4018/978-1-61692-811-7.ch011 ◽

2011 ◽

pp. 216-231

Author(s):

Gintautas Narvydas ◽

Vidas Raudonis ◽

Rimvydas Simutis

Keyword(s):

Control System ◽

Mobile Robot ◽

Mobile Robots ◽

Control Systems ◽

Intelligent Control ◽

Main Idea ◽

Autonomous Mobile Robots ◽

Autonomous Mobile Robot ◽

Intelligent Control System ◽

Objective Function Values

In the control of autonomous mobile robots there exist two types of control: global control and local control. The requirement to solve global and local tasks arises respectively. This chapter concentrates on local tasks and shows that robots can learn to cope with some local tasks within minutes. The main idea of the chapter is to show that, while creating intelligent control systems for autonomous mobile robots, the beginning is most important as we have to transfer as much as possible human knowledge and human expert-operator skills into the intelligent control system. Successful transfer ensures fast and good results. One of the most advanced techniques in robotics is an autonomous mobile robot on-line learning from the experts’ demonstrations. Further, the latter technique is briefly described in this chapter. As an example of local task the wall following is taken. The main goal of our experiment is to teach the autonomous mobile robot within 10 minutes to follow the wall of the maze as fast and as precisely as it is possible. This task also can be transformed to the obstacle circuit on the left or on the right. The main part of the suggested control system is a small Feed-Forward Artificial Neural Network. In some particular cases – critical situations – “If-Then” rules undertake the control, but our goal is to minimize possibility that these rules would start controlling the robot. The aim of the experiment is to implement the proposed technique on the real robot. This technique enables to reach desirable capabilities in control much faster than they would be reached using Evolutionary or Genetic Algorithms, or trying to create the control systems by hand using “If-Then” rules or Fuzzy Logic. In order to evaluate the quality of the intelligent control system to control an autonomous mobile robot we calculate objective function values and the percentage of the robot work loops when “If-Then” rules control the robot.

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A SoC for Intelligent Control Systems

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.571.514 ◽

2012 ◽

Vol 571 ◽

pp. 514-517 ◽

Cited By ~ 1

Author(s):

Zheng Xing Zheng ◽

Guo Min Tang ◽

Li Min Liu

Keyword(s):

Control System ◽

Embedded System ◽

Control Systems ◽

Intelligent Control ◽

Industrial Automation ◽

Intelligent Controller ◽

Intelligent Control System ◽

Intelligent Control Systems ◽

Software And Hardware

Intelligent control is a new direction of industrial automation. An intelligent control system is composed of algorithm, software and hardware. SoC is one of the best embedded system hardware. SoC may get some new progress for intelligent control. In this paper, intelligent control, SoC and some intelligent controller based on SoC are discussed. The new controller can be the smaller and more reliable.

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Innovative Teaching Research on the Course of Intelligent Control System and Simulation

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.709.441 ◽

2013 ◽

Vol 709 ◽

pp. 441-444

Author(s):

Zhao Yang Yang ◽

Jie Chen ◽

Pan Wang

Keyword(s):

Control System ◽

Control Systems ◽

Intelligent Control ◽

Teaching Model ◽

Innovative Teaching ◽

Teaching System ◽

Intelligent Control System ◽

Teaching Research ◽

Systems Simulation ◽

And Control

Innovative teaching research on the teaching system of intelligent control and control systems simulation is developed: based on the principle of methodological integration, a teaching model in classroom with seminars is established; an intelligent teaching software system is developed for effectively supporting the teaching.

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Development of an intelligent electric drive control system anchor winch

MORSKIE INTELLEKTUAL`NYE TEHNOLOGII ◽

10.37220/mit.2021.54.4.051 ◽

2021 ◽

pp. 195-200

Author(s):

С.П. Черный ◽

А.В. Бузикаева ◽

А.К. Тимофеев

Keyword(s):

Control System ◽

Control Systems ◽

Intelligent Control ◽

Electric Drive ◽

Fuzzy Controller ◽

Electric Drives ◽

Intelligent Control System ◽

Advantages And Disadvantages ◽

Drive Control ◽

Control Procedures

Данная работа посвящена моделированию интеллектуальной системы управления электроприводом якорной лебедки с применением теории нечетких множеств. Был приведен анализ существующих систем управления электроприводами якорно-швартовных узлов основанных на различных традиционных схемах регулирования, показаны достоинства и недостатки традиционных систем управления, а также выявлены основные возмущения, носящие существенно-недетерминированный характер. Процедуры интеллектуального управления в реализуемой модели системы управления электроприводом реализуются нечетким регулятором. Интеллектуальная система управления в своей основе имеет нечеткий регулятор с алгоритмом вывода Сугено, формализация входных сигналов по ошибке осуществляется двумя лингвистическими переменными. Кроме того, показано преимущество предлагаемого подхода при построении систем управления электроприводами якорно-швартовных узлов на основании базовых показателей качества. This paper is devoted to the modeling of an intelligent control system for the electric drive of an anchor winch using the theory of fuzzy sets. The analysis of the existing control systems for electric drives of anchor and mooring units based on various traditional control schemes was given, the advantages and disadvantages of traditional control systems were shown, and the main disturbances of a significantly non-deterministic nature were identified. Intelligent control procedures in the implemented model of the electric drive control system are implemented by a fuzzy controller. The intelligent control system is based on a fuzzy controller with the Sugeno output algorithm, the formalization of input signals by error is carried out by two linguistic variables. In addition, the advantage of the proposed approach in the construction of control systems for electric drives of anchor and mooring units on the basis of basic quality indicators is shown.

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Peculiarities of development intelligent control systems for the production of entomophages

Energy and automation ◽

10.31548/energiya2021.03.04 ◽

2021 ◽

pp. 42-50

Author(s):

V. Lysenko ◽

◽

I. Chernova ◽

Keyword(s):

Control System ◽

Knowledge Base ◽

Control Systems ◽

Air Temperature ◽

Intelligent Control ◽

Semantic Network ◽

Research Management ◽

Production Rules ◽

Intelligent Control System ◽

Intelligent Control Systems

The article reveals the features of the development of intelligent control systems for the production of entomophages, the relevance of the selected research area is determined. The aim of the study was to substantiate the feasibility of using intelligent control systems in the production of entomophages. Object of research – management process the cultivation of caterpillars Ephestia kuehniella in a specialized box in the production of entomophage Habrobracon hebetor. Research methods – systems approach, data mining, semantic modeling, situational management. A structural diagram of a hybrid intelligent system for controlling the air temperature of a box for growing entomocultures has been developed; knowledge representation model in relation to the construction of a hybrid intelligent control system in the form of a predicate semantic network. The production rules of the knowledge base of the intelligent control system have been developed, which allow to clarify the process of its creation. At the same time, attention is focused on: the sequence of formation of the training sample, which affects the accuracy of control of the air temperature of the box and, accordingly, the costs of electricity; use of ANFIS-editor MATLAB, which developed a self-learning neural network that automatically created a knowledge base regarding dependency the temperature setting of the meter-controller from the error of air temperature regulation. The expediency of using intelligent control systems in the production of entomophages has been scientifically substantiated. Formalized process of creating a hybrid intelligent box air temperature control system for growing entomocultures in the form of a predicate semantic network using production rules. The abovementioned makes it possible to systematize knowledge in relation to the processes of managing the production of entomophages, improve energy efficiency and the level of automation of the production process, which has a positive effect on both the state of the biological component of the object and the economy of the enterprise. The research results were introduced in the laboratory production of the entomophage Habrobrakon hebetor.

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