Integrated Design and Implementation of Embedded Control Systems with Scilab

Embedded systems are playing an increasingly important role in control engineering. Despite their popularity, embedded systems are generally subject to resource constraints and it is therefore difficult to build complex control systems on embedded platforms. Traditionally, the design and implementation of control systems are often separated, which causes the development of embedded control systems to be highly time-consuming and costly. To address these problems, this paper presents a low-cost, reusable, reconfigurable platform that enables integrated design and implementation of embedded control systems. To minimize the cost, free and open source software packages such as Linux and Scilab are used. Scilab is ported to the embedded ARM-Linux system. The drivers for interfacing Scilab with several communication protocols including serial, Ethernet, and Modbus are developed. Experiments are conducted to test the developed embedded platform. The use of Scilab enables implementation of complex control algorithms on embedded platforms. With the developed platform, it is possible to perform all phases of the development cycle of embedded control systems in a unified environment, thus facilitating the reduction of development time and cost.Comment: 15 pages, 14 figures; Open Access at http://www.mdpi.org/sensors/papers/s8095501.pd

Model-Based Development of Distributed Embedded Systems by the Example of the Scicos/SynDEx Framework

The embedded systems engineering industry faces increasing demands for more functionality, rapidly evolving components, and shrinking schedules. Abilities to quickly adapt to changes, develop products with safe design, minimize project costs, and deliver timely are needed. Model-based development (MBD) follows a separation of concerns by abstracting systems with an appropriate intensity. MBD promises higher comprehension by modeling on several abstraction-levels, formal verification, and automated code generation. This thesis demonstrates MBD with the Scicos/SynDEx framework on a distributed embedded system. Scicos is a modeling and simulation environment for hybrid systems. SynDEx is a rapid prototyping integrated development environment for distributed systems. Performed examples implement well-known control algorithms on a target system containing several networked microcontrollers, sensors, and actuators. The addressed research question tackles the feasibility of MBD for medium-sized embedded systems. In the case of single-processor applications experiments show that the comforts of tool-provided simulation, verification, and code-generation have to be weighed against an additional memory consumption in dynamic and static memory compared to a hand-written approach. Establishing a near-seamless modeling-framework with Scicos/SynDEx is expensive. An increased development effort indicates a high price for developing single applications, but might pay off for product families. A further drawback was that the distributed code generated with SynDEx could not be adapted to microcontrollers without a significant alteration of the scheduling tables. The Scicos/SynDEx framework forms a valuable tool set that, however, still needs many improvements. Therefore, its usage is only recommended for experimental purposes.Comment: 146 pages, Master's Thesi

Hybrid approach for energy aware management of multi-cloud architecture integrating user machines

International audienceThe arrival and development of remotely accessible services via the cloud has transfigured computer technology. However, its impact on personal computing remains limited to cloud-based applications. Meanwhile, acceptance and usage of telephony and smartphones have exploded. Their sparse administration needs and general user friendliness allows all people, regardless of technology literacy, to access, install and use a large variety of applications.We propose in this paper a model and a platform to offer personal computing a simple and transparent usage similar to modern telephony. In this model, user machines are integrated within the classical cloud model, consequently expanding available resources and management targets. In particular, we defined and implemented a modular architecture including resource managers at different levels that take into account energy and QoS concerns. We also propose simulation tools to design and size the underlying infrastructure to cope with the explosion of usage. Functionalities of the resulting platform are validated and demonstrated through various utilization scenarios. The internal scheduler managing resource usage is experimentally evaluated and compared with classical method-ologies, showing a significant reduction of energy consumption with almost no QoS degradation

EVALUATION OF A MODELING AND AUTOMATIC C CODE GENERATION TOOLSET AS AN OPEN SOURCE ALTERNATIVE SOLUTION

International audienceThis paper is focused on the model based design (MBD) approach, more particularly on the automatic C code generation. The goal of our project consists in evaluating how far the toolset called Scilab-Scicos and GeneAuto can be used as the open source alternatives to other solutions

A Review On The Comparative Roles Of Mathematical Softwares In Fostering Scientific And Mathematical Research

Mathematical software tools used in science, research and engineering have a developmental trend. Various subdivisions for mathematical software applications are available in the aforementioned areas but the research intent or problem under study, determines the choice of software required for mathematical analyses. Since these software applications have their limitations, the features present in one type are often augmented or complemented by revised versions of the original versions in order to increase their abilities to multi-task. For example, the dynamic mathematics software was designed with integrated advantages of different types of existing mathematics software as an improved version for understanding numerical related problems for advanced mathematical content (advanced simulation). In recent times, science institutions have adopted the use of computer codes in solving mathematics related problems. The treatment of complex numerical analysis with the aid of mathematical software is currently used in all branches of physical, biological and social sciences. However, the programming language for mathematics related software varies with their functionalities. Many invaluable researches have been compromised within the confines of unacceptable but expedient standards because of insufficient understanding of the valuable services the available variety of mathematical software could offer. In the developing countries, some mathematical software like Matlab and MathCAD are very common. A comparative review for some mathematical software was embarked upon in order to understand the advantages and limitations of some of the available mathematical software

A comparison of software engines for simulation of closed-loop control systems

A wide array of control system design and simulation software engines is available in market. It includes MATLAB-Simulink, LabVIEW, Maple-MapleSim, Scilab-Scicos, VisSim and Mathematica-Control Professional Suite (CPS). Among all of them MATLAB-Simulink is dominant and widely used software engine. The main aim of this study is to implement different state space control methods for non-linear Furuta pendulum system in each one of them and to compare performance against MATLAB-Simulink. Different parameters like learning curve, interoperability, flexibility, control design tools, documentation and tech support are considered for efficiency comparison. It is shown that MapleSim has multi-body intuitive physical modeling (acausal) approach faster than Simulink with unique control animation feature. It is found that MapleSim has the ability to generate differential equations from acausal modeling. It was verified that differential equations generated by MapleSim were similar to original equations. Scilab-Scicos is cost-efficient being open source engine with all control design and simulation capability similar to Matlab-Simulink. LabVIEW has better front end and back end for control design simulation at the cost of steep learning curve. VisSim has complete symbolic modeling approach with great flexibility and ease of learning. Mathematica\u27s Control System Professional does not have symbolic modeling capability. It is observed that CPS has a cumbersome approach for modeling non linear systems

Initialization of a Multi-objective Evolutionary Algorithms Knowledge Acquisition System for Renewable Energy Power Plants

pp. 185-204The design of Renewable Energy Power Plants (REPPs) is crucial not only for the investments' performance and attractiveness measures, but also for the maximization of resource (source) usage (e.g. sun, water, and wind) and the minimization of raw materials (e.g. aluminum: Al, cadmium: Cd, iron: Fe, silicon: Si, and tellurium: Te) consumption. Hence, several appropriate and satisfactory Multi-objective Problems (MOPs) are mandatory during the REPPs' design phases. MOPs related tasks can only be managed by very well organized knowledge acquisition on all REPPs' design equations and models. The proposed MOPs need to be solved with one or more multiobjective algorithm, such as Multi-objective Evolutionary Algorithms (MOEAs). In this respect, the first aim of this research study is to start gathering knowledge on the REPPs' MOPs. The second aim of this study is to gather detailed information about all MOEAs and available free software tools for their development. The main contribution of this research is the initialization of a proposed multi-objective evolutionary algorithm knowledge acquisition system for renewable energy power plants (MOEAs-KAS-FREPPs) (research and development loopwise process: develop, train, validate, improve, test, improve, operate, and improve). As a simple representative example of this knowledge acquisition system research with two selective and elective proposed standard objectives (as test objectives) and eight selective and elective proposed standard constraints (as test constraints) are generated and applied as a standardized MOP for a virtual small hydropower plant design and investment. The maximization of energy generation (MWh) and the minimization of initial investment cost (million €) are achieved by the Multi-objective Genetic Algorithm (MOGA), the Niched Sharing Genetic Algorithm/Non-dominated Sorting Genetic Algorithm (NSGA-I), and the NSGA-II algorithms in the Scilab 6.0.0 as only three standardized MOEAs amongst all proposed standardized MOEAs on two desktop computer configurations (Windows 10 Home 1709 64 bits, Intel i5-7200 CPU @ 2.7 GHz, 8.00 GB RAM with internet connection and Windows 10 Pro, Intel(R) Core(TM) i5 CPU 650 @ 3.20 GHz, 6,00 GB RAM with internet connection). The algorithm run-times (computation time) of the current applications vary between 20.64 and 59.98 seconds.S

Scilab and MATLAB Interfaces to MUMPS (version 4.6 or greater)

This document describes the Scilab and MATLAB interfaces to MUMPS version 4.6. We describe the differences and similarities between usual Fortran/C MUMPS interfaces and its Scilab/MATLAB interfaces, the calling sequences and functionalities. Examples of use and experimental results are also provided.Nous décrivons les séquences d’appel et les fonctionnalités de nos interfaces Scilab/MATLAB et nous évoquons ses différences et similarités avec les interfaces Fortran/C habituelles de MUMPS. Nous présentons aussi des exemples d’utilisation et quelques résultats expérimentau