ISSN: 1841-0626 CNCSIS code 11 category B+ internationally indexed, starting with 2010, (Copernicus, Inspec)
    Semiannual publication
    Occasionally, conferences dedicated special issues may be published

    Year 2015 Volume 12 (39) no. 1
  1. Method for Fault Detection (pp. 1 - 6)

    Eugen Iancu*, Sergiu Ivanov**, Eugen Bobasu*, Emil Petre*
    *Department of Automation and Electronic, University of Craiova, 107 Decebal Street, RO-200440 Craiova, Romania (e-mail:, **Department of Electromechanics, Environment and Industrial Informatics, University of Craiova, 107 Decebal Street, RO-200440 Craiova

    Abstract: This study shows a method for analytical fault detection that can be applied to monitor an electric motor brushless DC. The fault detection and the isolation (FDI) problem is an inherently complex one and for this reason the immediate goals is to preserve the stability of the process and, if is possible, to control the process in a slightly degraded manner. The authors propose a practical method to detect the presence of failures of sensors using a prediction solution. It was used for this purpose a mathematical model of BLDC motor and single exponential smoothing. Also is proposed a structure to detect the presence of failures.
    Keywords: Brushless DC motor, fault detection and isolation, analytical redundancy, single exponential smoothing.

  2. Fault Detection in Educational Kit Festo (pp. 7 - 12)

    Camelia Maican*, Gabriela Canureci**
    * Automation and Electronics Department, University of Craiova, Romania (e-mail: ** Research and Development, Engineering and Manufacturing for Automation Equipment and Systems SC IPA SA CIFATT Craiova, Romania (e-mail:

    Abstract: In this paper is study the faults detection and localization, in educational kit Festo, using residual methods. The level control system and the faults detection structure were developed under Matlab Simulink. This faults detection structure allows us to detect two faults that can occur in the plant, separately and simultaneously. The proposed method was theoretically developed and experimentally verified on the plant model.
    Keywords: Control, Fault detection and localization, Level, Residue.

  3. Compact Dynamic Model of the Brushless DC motor (pp. 13 - 16)

    Sergiu Ivanov*, Dan Selisteanu**, Virginia Ivanov*, Dorin Sendrescu**
    *Faculty of Electrical Engineering, University of Craiova, Romania, (e-mail:, **Faculty of Automation, Computer and Electronics, University of Craiova, Romania, (e-mail:{dansel, dorins}

    Abstract: Both the researchers and manufacturers are interested by the light urban electric vehicles. More ways are investigated for the used motors, the most important concern being the compactness of the solution. Thanks to the high power density, the most preferred motors are the permanent magnet synchronous motors (PMSM) and brushless DC motors (BLDC). These are preferred also thanks to their high efficiency and low maintenance cost. For both, the main manufacturing technology and associated power electronics are quite similar. The differences occur in the controlling technology, for BLDC being simpler and more advantageous. As integration technology, the direct drive in-wheel technology improves the safety, efficiency, weight, controllability and finally the costs. The development of the control strategies implies the need for a simple and compact model of the BLDC. The paper deals with an efficient dynamic model of this type of motor. It will be applied for the most used control strategy, the preset currents respectively.
    Keywords: BLDC motor model, S-function, in-wheel motor, control.

  4. Adaptive and Predictive Control Algorithms for a Microalgae Process (pp. 17 - 23)

    Emil Petre
    Department of Automatic Control and Electronics, University of Craiova, Craiova, Romania (e-mail: epetre@

    Abstract: This paper deals with the design and the analysis of two control structures for microalgae culture process to regulate the substrate concentration at a chosen setpoint. The control strategies are developed under the realistic assumptions that the reaction rates are time varying and incompletely known and the influent substrate concentration as well as the light intensity are strongly time-varying. The first control structure is an adaptive control algorithm. This controller is designed by coupling a linearizing controller with a parameter estimator used for estimation of unknown kinetics. The predictive control structure is based on classical nonlinear model predictive control law under model parameter uncertainties implying solving a nonlinear least squares optimization problem for setpoint trajectory tracking. The proposed approaches are validated in simulation and numerical results are given to illustrate its efficiency for setpoint tracking in the presence of parameters uncertainties.
    Keywords: Bioprocesses, Microalgae, Droop model, Photobioreactor, Adaptive control, Predictive control, Nonlinear least squares optimization.

  5. Method for Anticipative Control of Bioprocess (pp. 24 - 28)

    Eugen Iancu, Emil Petre
    Department of Automation and Electronics, University of Craiova, 107 Decebal Street, RO-200440 Craiova, Romania (e-mail:,,

    Abstract: The control of bioprocesses remains an inherently complex problem. The necessity to obtain good performances without installing a lot of dedicated and expensive equipment, forces the developers to use many techniques available to processing all the information that are "hidden" in the technological process. A difficulty for the design of high-performance control techniques of such living processes lies in the fact that, in many cases, the models contain kinetic parameters and/or yield coefficients that are highly uncertain and time varying. The aim of this paper is to present some possible predictive control methods, able to deal with the model uncertainties in an adaptive way, for a complex biotechnological process.
    Keywords: Photoautotrophic growth bioprocess, Predictive control, Single exponential smoothing.

  6. Improving of the Backtracking Algorithm using different strategy for solving the 2-d problems (pp. 29 - 33)

    Bogdan Popa, Dan Popescu
    Department of Automation and Electronics, University of Craiova, 107 Decebal Street, RO-200440 Craiova, Romania (e-mail:;

    Abstract: Nowadays, many algorithms in the field of artificial intelligence are based on the backtracking principles. These algorithms require highly efficient systems due to the high cost of execution time of solving backtracking, significant adjustments are needed to optimize these complex methods. Whether parallel programming or differentiated approach to the problem can bring better results of such as algorithms that responds to all possible solutions to a scenario. This article illustrates a method to improve backtracking algorithm, depending on the problem solved by using new systems for software development. This article can offer a new perspective over the mapping systems for different fields where there we need to find all the solutions and also to give different contexts to the searching for the solutions. The results of this study consisted in methods for give a better time execution for finding the solutions for the proposed problems and an analysis for every strategy chosen.
    Keywords: Backtracking algorithm, Artificial intelligence, Improving algorithms, Strategy for 2-d problems.

  7. An implementation in BlueJ used in teaching object-oriented programming (pp. 34 - 37)

    Adrian Runceanu
    Department of Automation, Energy, Environment and Sustainable Development, Constantin Brancusi University of Targu-Jiu, (e-mail:

    Abstract: In this paper we present a visual programming environment oriented, BlueJ, in which we can built it using applications developed with classes. The approach in this paper proposes to use interactive teaching in BlueJ. In this way the student can better understand concepts related to object-oriented programming (OOP) and especially may make changes, improvements at the implemented applications. The paper is implementing the Tower of Hanoi problem, practical application of the method of Divide and Conquer programming.
    Keywords: Object-oriented programming, Java, BlueJ, Divide et Impera, Recursion.

  8. Running Complex Queries on a Graph Database: A Performance Evaluation of Neo4j (pp. 38 - 44)

    Calin Constantinov, Mihai Mocanu, Cosmin Poteras
    Department of Computers and Information Technology, University of Craiova, Romania (e-mail:,,

    Abstract: Computer science, by far one of the most dynamic research domains, manages to produce concepts, prototypes and paradigms at a pace that is sometimes hard to follow. Although most of these ideas set goals that are more or less realistic, some of them are able to fascinate by their potential to lead to dramatic changes. One particular case is represented today by graph databases, a type of NOSQL solution which can be applied to very power demanding tasks in data analysis frameworks. They allow for the expansion of data sources, including social media feeds, thus making complex systems such as recommendation engines much more powerful. No matter the controversies among both simple technology enthusiasts and large corporations, these databases are rapidly expanding, managing to not only generate interest, but also remarkable solutions. In this paper, we will have a deep look over the most popular graph database, Neo4j, evaluating its performance and scalability options when running very complex statistics and recommendation queries over a dataset of a signicant size, containing strongly interconnected Facebook data. The evolution from a simple standalone database scenario to a Highly-Available (HA) cluster setup is described step by step by analysing the impact that each conguration change has on the system's both read and write performance. Given the positive results of this paper, we believe that graph technologies represent a very promising research domain as, considering their performance, they are likely to hold the key to building an ecient, distributed social-network graph mining framework on which data analysis jobs can be continuously run, further enhancing the data.
    Keywords: Graph Database, Facebook Data, Performance Evaluation, Social Recommendation Engine, Data Analysis.