Editorial & Advisory Board - Acta Technica Corviniensis

More documents

Recommendations

Info

ACTA TECHNICA CORVINIENSIS – Bulletin of Engineering Figure 12. Yalls_array_fetch_field_symbols Memory analysis Figure 13. Yalls_array_fetch_table (wa) Memory analysis And speaking of memory used, array fetch technique with accessing data from internal table with the symbol field is the most effective. CONCLUSIONS This paper collects several studies referring to the involvement of the control tools, such as ABAP Runtime Analysis and Memory Analysis in order to analyze all methods to optimize data processing codes of the level of persistence on SAP Netweaver 2004’s, ABAP Application Server. The analysis performed showed that the most effective reading data technique from one data table is array fetch. As far as access to data in internal table is concerned, it is efficient to use the symbol field both in terms of processing time and memory used. These studies can be of great use for an efficient coding of this integrated system which is also an ERP system (Enterprise Resource Planning). REFERENCES [1.] SAP Help Portal (http://help.sap.com), [2.] SAP Developer Network (http://sdn.sap.com), [3.] Horst Keller, Wolf Hagen Thummel, Official ABAP Programming Guidelines, Galileo Press, 2010 [4.] Horst Keller, Sascha Krüger, ABAP Objects, SAP Press, Bonn Germany, 2007 [5.] Ulrich Gellert, Ana Daniela Cristea, Web Dynpro ABAP for Practitioners, Springer Publishing House, 2010 [6.] Cristea Ana Daniela, Berdie Adela, Osaci Mihaela, Working With ABAP Persistent Data, ISIRR Hunedoara, 23‐24 April, 2009, Proceedings Conference, CD Edition ACTA TECHNICA CORVINIENSIS – BULLETIN of ENGINEERING ISSN: 2067‐3809 [CD‐Rom, online] copyright © UNIVERSITY POLITEHNICA TIMISOARA, FACULTY OF ENGINEERING HUNEDOARA, 5, REVOLUTIEI, 331128, HUNEDOARA, ROMANIA http://acta.fih.upt.ro 110 2012. Fascicule 2 [April–June]
1. Anayet U. PATWARI, 2. Muammer D. ARIF, 3. S. M. Tawfiq ULLAH CONTROLLER DESIGN FOR BEHAVIOR PREDICTION OF SECOND ORDER CLOSED LOOP SYSTEM IN AUTOMATED INDUSTRIAL PROCESSES 1. DEPARTMENT OF MECHANICAL AND CHEMICAL ENGINEERING, ISLAMIC UNIVERSITY OF TECHNOLOGY (IUT), BOARD BAZAR, GAZIPUR, DHAKA: 1704, BANGLADESH ABSTRACT: The process requirements, in a manufacturing environment, are subject to fluctuations dependent on both internal and external factors. Thus, most modern industries utilize automated control systems, which can make the necessary dynamic adjustments for achieving optimum productivity and product quality. The PID, PI, and PD controllers are widely relied upon for such automated control of processes. However, the adjustment and optimization of some of the functional aspects of these controllers, according to the process demands, are time consuming. Such fine tunings are usually done based upon expert knowledge and tech manuals. This study addresses this problem and presents a solution. The authors illustrate the simulation and development of a controller, using a GUI in MATLAB 2008, which is able to accept the process requirements as input and simulate necessary control actions based on the predictions made. The simulator, discussed, only handles Second Order Systems, which are prevalent in automated industrial control systems. The inputs required are the transfer function of the process and some relevant data from the corresponding frequency response domain. From these, the simulator can predict the closed loop behavior of the system. After the predictions, the GUI provides three viable controller choices to the user. The controller options are PI, PD, or PID types which offer greater flexibility to the user in optimizing the present condition of the process based on the fine tuned parameters for the chosen controller as determined by the simulator. Hence, the efficient operation and optimum output of the automated process is ensured. KEYWORDS: Dynamic Control Simulator, Closed Loop System, Second Order System, PID Controller, Automated Industrial Processes INTRODUCTION Manufacturing processes, in today’s competitive market, have to balance many almost mutually exclusive goals such as: higher productivity, stringent quality control, flexibility, short product lifetime, lower lead time, and reduced product price. Invariably, such adjustment and optimization of the process are too complex for manual oversight and control. Thus, a majority of modern industries have switched over to dynamic and automated process control systems. Such controllers perform online monitoring and fine tuning of the processes in order to meet all the manufacturing goals. Albaker et al. [1] utilized PID controllers to design the dynamic nonlinear flight control of a propeller driven fixed wing Unmanned Ariel Vehicle (UAV). Their simulator could correctly predict the actions necessary for maintaining the commanded flight path of the UAV. Their predicted results were verified using actual experiments performed on the flight guidance of the UAV. Upadhyay et al. [2] developed an adaptive non‐linear feedback controller using PID controllers in order to maintain the temperature of a Continuously Stirred Tank Reactor (CSTR) in a chemical plant. They observed that the results of their simulation were in accord with experimental data. It was also mentioned that their particular controller design was very robust to modeling errors and random disturbances occurring in the tank; CSTRs by nature have strong non‐linear behaviors. Li et al. [3] discussed the application and importance of PID controllers in their review article. They also presented many cases of computer simulation of PID controllers’ actions and their experimental validations. They concluded that there was a significant difference between academic research findings on PIDs and the problems encountered in using such controllers in the industry. However, the development of a simple and user friendly GUI based software, for the prediction of common controller actions and their fine tuning to meet process requirements, has rarely been researched. The authors of this research, therefore, have developed a simulator using MATLAB 2008 [4, 5] in order to predict the closed loop response of second order systems from the process requirements and corresponding frequency domain data as inputs. For guidelines the authors referred to the seminal work of Patwari et al. [6]. Patwari et al. had previously utilized MATLAB 2008 and Visual Basic 6 Enterprise Edition to develop a simulator for the prediction of chip serration frequency during end milling operation. The authors’ simulator has a built‐in Graphical User Interface (GUI) that illustrates the results of the prediction and provides the user, in vivid details, with © copyright FACULTY of ENGINEERING ‐ HUNEDOARA, ROMANIA 111
Page 2 and 3:
ACTA TECHNICA CORVINIENSIS - BULLET
Page 4 and 5:
ACTA TECHNICA CORVINIENSIS - Bullet
Page 6 and 7:
Page 8 and 9:
Regional Editors from MALAYSIA Abde
Page 10 and 11:
Imre TIMÁR University of Pannonia,
Page 12 and 13:
Ioan MILOŞAN Transilvania Universi
Page 14 and 15:
Member from GREECE Nicolaos VAXEVAN
Page 16 and 17:
Page 18 and 19:
Page 20 and 21:
Page 22 and 23:
Other cases, when the variable spac
Page 24 and 25:
optimization). The displacements of
Page 26 and 27:
[16.] Maire, E., Schmidt, T.: Topol
Page 28 and 29:
Left part of the main window (Figur
Page 30 and 31:
Generated XML file has node as roo
Page 32 and 33:
Page 34 and 35:
ecause can influences of security a
Page 36 and 37:
Therefore, development should be di
Page 38 and 39:
To measure has not been used extens
Page 40 and 41:
Page 42 and 43:
and enrichment, design, capturing,
Page 44 and 45:
EXAMPLE PLM SOLUTIONS With the anal
Page 46 and 47:
[10] Kajmakoska, B., Koeck, A.M, Wi
Page 48 and 49:
est known is Drude‐Lorentz model
Page 50 and 51:
Page 52 and 53:
Sl. No 52 % of Red Soil % of Sand T
Page 54 and 55:
Page 56 and 57:
Page 58 and 59:
Where, f s is the steel stress; f y
Page 60 and 61: NUMERICAL RESULTS As it was describ
Page 62 and 63: Welding sleeve Basic material ACTA
Page 64 and 65: ACTA TECHNICA CORVINIENSIS - Bullet
Page 66 and 67: help learners throughout their care
Page 68 and 69: In the frame of the same idea, the
Page 70 and 71: METHODOLOGY OF INVESTIGATION HEAT T
Page 72 and 73: Significant increase in the concent
Page 76 and 77: In addition the vision and mission
Page 78 and 79: sharing between pre‐contract and
Page 80 and 81: [21.] Oyediran, O. S., & Akintola,
Page 82 and 83: 2006, 208 large dams had been const
Page 84 and 85: original area and to skip unnecessa
Page 86 and 87: Figure 4: An example of cutting for
Page 88 and 89: [4]. Or: extracting evidence from c
Page 90 and 91: tampered with or altered, helping t
Page 94 and 95: e attaching on the discharge wires.
Page 98 and 99: SDS‐PAGE FOR LPS (Modified proced
Page 100 and 101: to be 2H‐Pyaran,2, 5‐diethenylt
Page 104 and 105: MATHEMATICAL MODEL MINIMALIZATION O
Page 106 and 107: Management. Journal of Manufacturin
Page 108 and 109: We can now read the ABAP instructio
Page 112 and 113: three types of basic controllers to
Page 114 and 115: experimental case compared to 1170
Page 116 and 117: was heated in a resistance furnace.
Page 118 and 119: overview how the error, i.e. differ
Page 124 and 125: Optimization of the processes for d
Page 128 and 129: Engineering Hunedoara - Internation
Page 130 and 131: According to these basic types of m
Page 132 and 133: Load of contact areas on the die dr
Page 136 and 137: Access Control: Access control mech
Page 138 and 139: Another technique based on access c
show all

Editorial & Advisory Board - Acta Technica Corviniensis

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?