RESEARCHING STRATEGIES FOR OPTIMIZING EDUCATIONAL TECHNOLOGIES BY OFFERING ALTERNATIVE DESIGNS Carol Zoller1, Mihai Cernat2, Stylianos Papazis3, Remus Dobra1 1
University of Petrosani, Romania,
[email protected],
[email protected] 2
Transilvania University of Brasov, Email:
[email protected] 3
Technical Higher Vocational School, Aharnes, Greece
Abstract Modern electronic technologies that are continually expanding allow relatively easy design and implementation of new concepts and processes regarding the efficiency in terms of educational process. To make possible optimisation educational solutions, is obvious that should be designed first of all different alternatives for solving problems, so that the decision about optimum to be facilitated by the existence of measurable set of decisions criteria that quantify the proposed variants.
conditions of a power system, the following steps mast strictly be taken: Specification (description) of digital system; Synthesis and Simulation of the project, thus transforming it into a list of links containing basic drivers and interconnections between them; Programmation and Implementation of the circuit by adjusting the list of connections in order to be use efficiently the available resources of circuit.
For exemplification, in the paper, it shows synthetically how can be materialized the alternative designs concept for an electrical engineering application developed and implemented for specific specializations in higher education.
Key
Words:
Researching strategies, educational technologies, alternative designs, virtual instrumentation, programmable systems.
1. Introduction An alternative design requires systematic approaches based on some basic concepts such as black box, the systemic structure, modular design, simulation and functional electronics. Based on this analysis, the programmable system can be divided into blocks or modules with clearly defined inputs, outputs and functions performed which can be analyze and make independent and then incorporated into the final structure. To provide various alternatives for solving a problem and for designing the operating
Figure 1. The flowchart design of digital systems using programmable circuits
In the figure 1 is presented the flowchart design of digital systems using programmable circuits, the exemplification of every stage is described as follows: classical solution presentation for the chosen electrical system; technical design selection, allows the user to choose from alternative design concepts; input/output configuration, development of the systemic structure;
logic process flowchart development; programming of the digital system, which assume the placement of components using graphical methods;
start with or without the delay Δt; if the delay Δt is programmed the numerical system will give an appropriate optical signal;
save the project and simulation of system operation based on the list of connections obtained before to implementation in a circuit; implementation of a circuit by adjusting the list of connections to effectively use available resources of the circuit; configuration (programming) circuit for it to achieve the desired function; solution optimising by chosen one of the alternative technical designs;
2. Process synthesis A numerical system is use to process digital information by making them on a series of arithmetic and logical operations in accordance with a process flowchart. Figure 2. Control system flowchart
2.1 Flowchart development Synthesized and proposed process flowchart, presented in figure 2, offers the following sequential facilities to the work program corresponding to each numerical unit, as follow: Initialization of the unit output ports immediately after the voltage supplying; each port is brought into logical 1 within the first machine cycles. conditions of the protection systems are checked; if one or more protections are energised, the optical signalling is auctioned, if not the switching on conditions regarding the electrical protections must be suitable optical signalling; the cycle resumes sequentially until the normal operating conditions are fulfilled.
before the starting command is given to the electrical motor M, is checked whether there has been restrictions or a switching off command, O after switching on the motor an optical signal is giving that indicate that the engine is running 2.2 Systemic structure The first step in the process of designing a basic system is to decide which components will be used for inputs and outputs. Some types of components are in terms of reliability are less good, and their use should be avoided.
if the switching on conditions is are adequate, the program will go to contact control lockout condition K1, allowing access to the switching on command that only authorized persons that have access to the key; If his K1 condition is inappropriate, it signals this command and control the cycle resumption; the start button state I is check; When it is pressed it can start the query over contact K2 by determining whether the electrical motor will
Figure 3. Input/Output configuration development of the systemic structure
In figure are inventoried all inputs into the Black-Box logical system, eight on the left side of it and all the outputs, nine on the right side of it.
3. Alternative Designs for Numerical Control of a Power System For optimal choice of a numerical control, further are described four ways to solve a classical numerical control problem, as fallow:
03
5
04
6
05
7
06
8
07
9
08
Microprocessor design;
Microcontroller design;
10
09
Programmable Logic Controller design;
11
0A
Virtual Instrumentation design.
12
0B
13
0C
The methods presented below are regarding Numerical Control - software control of manufacturing processes, based on a code of letters, numbers & special characters called a program and Computerized Numerical Control – numerical control machine with the addition of an on-board computer referred to as a machine control unit or MCU. These approaches represent the latest technologies in the numerical control domain, each providing certain facilities but also some limitations. 3.1 Implementation of a Microprocessor Circuit A microprocessor, in addition to the central unit, subsystem includes memory and inputs / outputs that are connected via an external bus. A microprocessor system is built around buses that have serves way to transfer information. For reasons of research teaching methods at this stage a control logic solution was developed based on a microprocessor that uses 14.000A kit, one bit microprocessor equipped with MMC-4500 from Motorola. Table 1: Summary of proposed flowchart source No. Prog. Prog. step addr. 1
00
2 3
4
ET 0
Source code
Machine Code
IEN I0
AO
01
OEN I0
BO
02
LD I0
10
Obs. IEN=1 OEN= 1 RR=1
STOC Q0 STO Q1 STO Q2 STO Q3 STO Q4 STO Q5 STO Q6 STO Q7 STO Q8 NOPO SUBR 1
90 81 82 83 84 85 86 87 88
Q0=0, LED +5V Q1=1 Q2=1 Q3=1 Q4=1 Q5=1 Q6=1 Q7=1 Q8=1
04
In table 1 is presented a fragment of the proposed flowchart source. The machine code program will be loaded into RAM and run on a development kit, named SED type 14, prepared for application development on 14.000A processor kit, during which it can be tested and corrected. By attaching the chip to PROMEPROM-marked application program on a new kit this processor can work independently in the system design, with the corresponding logic functions 3.2 Implementation of a Microcontroller Circuit Another solution to the same application uses a different technology like microcontroller. Further will be described the implementing of a microcontroller in the systemic structure, this micro programmable system belonging to Cypress MicroSystems. PSoC is a Programmable embedded System-onChip integrating configurable analog and digital peripheral functions, memory and a microcontroller on a single chip. The development software suite, PSoC express is the visual embedded system design tool that allows a user to create an entire project without writing a single line of code.
To develop the proposed application the same systematic structure presented in figure 3 was used, and from the graphically library program were choose the input/output components.
3.3 Implementation of a Programmable Logic Controller (PLC) As shown in the systemic structure, to solve the problem by choosing a PLC this must contain at least eight logical data inputs and at least eight logical outputs. In figure 6, is presented the Easy Soft Pro graphic editor used for chosen the programmable module Easy 620-DC-TC.
Figure 4. Graphical interface of the control circuit using PSoC Designer 5.0
After choosing all devices driver from library program, a graphical interface similar to that shown in figure 4 must be obtained. Table 2: The priority encoder transfer functon
Figura 6. Chosen the programmable module using
Easy Soft Pro In fugures 7, 8 are presented the graphical interfaces of the project were is checks whether contacts are connected in parallel or in series and stores the switching states of all the contact fields.
Truth table corresponding to the switchin on command transfer function is shown in the table 2. Figure 7. Simulation of the logic outputs using Easy
620-DC-TC
Figure 5. Graphical simulation interface using PSoC Designer 5.0
After graphical designing and writing classical expressions we proceed to simulate the project developed, like in figure 5.
Figure 8. Simulation of the logic inputs using Easy
620-DC-TC Using the simulation mode, the user can test the circuit configuration of the Easy 620-DC-TC
without connecting the hardware to ensure that the circuit functions as intended. 3.4 Implementation Instrumentation
using
Graphical structure of the model simulation for the electrical application was made using Agilent VEE Pro 6.0.
Virtual
The concept of “virtual instrumentation” is the technical means of measurement, analysis and processing using a personal computer. A virtual instrument represents a set of hardware that together with a computer, an application development environment and associated drivers performed the functions of a traditional instrument. The main advantage of virtual instruments is their flexibility.
Figure 11. Graphical panel of the switching on electrical motor using VEE Pro 6.0 facilities
For interfacing with the graphics program was necessary to implement communications with the outside hardware tools. To bring information into the computer from the process a data acquisition must be use. In figure 10 is presented the interfaces for bringing data into the computer and in figure 11 the simulation interface of the application.
4. Optimal solution using fuzzy theory
Figure 9. Graphical interface of VEE Pro 6.0 for the electrical application In figure 9 is presented the graphical program developed based on the process flowchart and the systemic structure.
Figure 10. Automatic operation through a data acquisitions interface
Considered the multitude of parameters and docimologic techniques that can be taken into account for improving educational processes relating to the proposed and solved problem in the paper, the fuzzy technologies can be fitted as a suitable decision method. In case of fuzzy control the crisp values are going to have attached a fuzzy characterization reflected in an adequate linguistic wording and in mathematical characterization of the linguistic wording under the form of membership function(s) (MF or MFS) corresponding to some linguistic variables. The linguistic wording further permits the clear engineering definition of the rules that make up the base of fuzzy inference. The terminology of linguistic variables (LVs) and linguistic terms (LTs) corresponding to fuzzy sets is used in the linguistic characterization of the fuzzy sets (FSs). So, resuming our example to the optimizing educational technologies, the linguistic variables (LV) introduced are: DD - difficulty degree, CD - complexity degree and ST solving problem time, as complex variables. The corresponding linguistic terms (LTs) for difficulty degree are: very low difficulty -
VLDD, low difficulty - LDD, moderate difficulty - MDD, high difficulty - HDD, very high difficulty - VHDD; The corresponding linguistic terms (LTs) for complexity degree are: low complexity - LCD, moderate complexity - MCD, high complexity - HCD; The corresponding linguistic terms (LTs) for solving problem time are: low time - LST, high time - HST.
4. Conclusion Four alternative design concepts of an electrical engineering application were developed using programmable technologies. The optimal solution for solving another problem can be more easily approached later based on the understanding of the described scenarios. The final decision of choosing the optimal solution cannot be taken unless it takes into account previous experience and expertise of each person engaged in the educational process. 5. References [1] Janet F. Asteroff, Technics and Higher Education, Columbia University, New York, [2] Michel G., Programmable Logic Controllers Architecture and Applications”, Wiley, 1990. [3] Moise, A., Automate Programabile. Proiectare. Aplicaţii, Ed. MatrixRom, Bucureşti, 2004. [4] Bryan L. A., Bryan E. A., Programmable controllers theory and implementation, Library of Congress Cataloging-în-Publication Data, 1997. [5] Oliver H. B., The beginnner's guide to PSoC Express, Microcontroler Development without writing code, Timeslines Industries, 2007.
Figure 12. Fuzzification of the optimizing educational technologies as membership functions MF(S)
[6] Robert A., Designer's Guide to the Cypress PsoC, Elsevier, Printed în the Unites States of America, 2005.
Different ways are used for representing membership functions, (parametric representations under the form of analytical functions, direct graphical representations by means of graphics, discrete representations by singletons, in case of fuzzy systems with finite number of discrete elements). For exemplifying the concept of fuzzy set, FS, as graphics are figure 12 that represents the membership function of the difficulty degree (DD), the complexity degree (CD) and the solving problem time (ST). To choose the optimal method for solving the problem an orthogonal spatial representation is proposed for all three fuzzification functions and in that space an appropriate decision can be taken depending on each person aprioristic training.
[7] *** Agilent Technologies: VEE Pro user‘s guide. Agilent Technologies, Inc, E2110-90062. USA, 2000. [8] ***DT VPI TM User’s Manual, version 6.0 Datatranslation UM 16150-C, Data Translation, Inc., 100 Locke Drive, Marlboro, MA 01752-1192 USA. [9] *** Datatranslation DT 300 User’s Manual, Data Translation, Inc., 100 Locke Drive, Marlboro, MA 01752-1192 USA. [10] Kevin Self, Designing with fuzzy logic, IEEE SPECTRUM, November 1990, 42:44,105. [11] Earl Cox, Fuzzy Fundamentals, IEEE SPECTRUM, October 1992, 58:61. Notes from this article constitute the core of this tutorial. [12] "Fuzzy Controller Challenges 8-bit MCUs", Computer design, November 1995.
