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İNSAN-MAKİNA SİSTEMLERİ VE MANUEL KONTROL MODELİ

MAN-MACHINE SYSTEMS AND MODELLING OF MANUAL CONTROL

Journal Name:

  • Deniz Harp Okulu Deniz Bilimleri ve Mühendisliği Dergisi

Publication Year:

  • 2009

Key Words:

Keywords (Original Language):

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Abstract (2. Language): 
Despite the developments of classical and intelligent control methods, since many applications are complex and uncertain, automatic controlled machines still cann’t be used instead of human operators. Generally, a human operator interacts with a machine using visual sensing. Human operator decides on the type and amount of action to be taken based on the visual information, hence closing the loop between the controlled and the control variables of the system. The Human operator in a man machine system is the archetype, hieararchical, adaptive, optimalizing, decision-making controller . Besides the technological aspects of manual control, interdisciplinary activities between control engineers, physiologists and experimental psyschologists have led to control theory descriptions of human subsystem behaviour and to the interpretation of the human’s psycho-physiological outputs in control engineering .
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Abstract (Original Language): 
Klasik ve akıllı kontrol metotlarındaki bütün gelişmelere rağmen, birçok uygulamanın karmaşık ve belirsiz olması nedeni ile hala insan operatörlerin yerine otomatik kontrol sistemli makinalar kullanılamamaktadır. Genellikle insan operatör görsel geri besleme bilgisinden faydalanarak makina ile etkileşim halindedir. Bu görsel bilgiye dayanarak operatör yapacağı eylemin tipine ve miktarına karar verir ve böylece kapalı çevrimi oluşturur. İnsan-Makine Sistemlerinde insan operatör, adaptif, optimal, karar veren kontrolör olarak görev yapmaktadır. Manuel kontrol teorisine teknolojik tarafının yanı sıra, kontrol mühendisliği, fizyoloji, deneysel psikoloji konularını içeren disiplinler arası aktiviteleri insan operatörün davranışlarının kontrol teorisinin tanımlanmasında ve insan psiko-fizyolojik yorumlarının kontrol mühendisliğinde sistem çıkışlarının tespitinde rehber olmuştur .
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  • 3
91-103
  • Turkish

REFERENCES

References: 

[1] Sheridan,T.B.,Ferrell,W.R, 1974, Man-Machine Systems, The MIT Press
[2] Cacciabue P.C., 1996, Understanding and modelling man-machine interaction,
Commision of the European Communities, Joint Research Center, Institıte for Systes
engineering and Informatics, Nuclear Engineering and design 165 pp 351-358
[3] McRuer, D.T., 1980, Human Dynamics in Man-Machine Systems, Automatica, Vol.16,
pp.237-253.
[4] Kleinman, D.L., Baron, S., Levison, W.H., 1970, An Optimal Control Model of Human
Response Part I: Theory and Validation, Automatica, Vol.6, pp.357-369
[5] Baron, S., Kleinman, D.L., Levison, W.H., 1970, An Optimal Control Model of Human
Response Part II: Prediction of Human Performance in a Complex Task, Automatica, Vol.6,
pp.371-383
[6] Doman, D.B., Anderson, M.R.,2000, Fixed-Order Optimal Control Model of Human
Operator Response, Automatica, Vol.36, pp.409-418
[7] Kleinman, D.L.,1969, Optimal Lineer Control For Systems with Time Delay and
Observation Noise, IEE Transactions on Automatic Control, Vol.AC-14, No:4, pp357-
367,October
[8] Enab,Y.M., 1994, Controller Design for an Unknown Process, Using Simulation of a
Human Operator, Eng. Application Artificial Intelligent, Pergamon, Vol.8 No.3 pp:299-308
[9] Enab, Y.M., 1996, Intelligent Controller Design for The Ship Steering Problem, IEE,
Vol 143, No.1
[10] Kosko,B., 1992, Neural Networks and Fuzzy Systems : A Dynamical Systems
Approach to Machine Intelligence. Prentice Hall, New York
[11] James, H.M., Nichols, N.B, Phillips, R.S., 1947, Theory of Servomechanism ,
McGrawHill, New York, pp 360-368,
[12] Tustin, A., 1947, An Investigation Of The Operator’s Response in Manual Control and
its Implications For Controller Design, J.Inst. Elec.Engrs. 94
[13] Wiener, P., 1950, Extrapolation, Interpolation and Smoothing of Stationary Time
Series, John Wiley, New york
[14] Elkind, J.I., 1956, Characteristics of Simple Manual Control Systems, TR111, Mass.
Inst. Tech. Lincoln Lab., Lexington, April
[15] MacRuer, D.T., Krendel, E.S., 1957, Dynamic Response of Human Operators. Wreight
Air Dev. Center WADC TR56-524, Wreight-Patterson Air Force Base, Ohio, October
[16] McRuer, D.T., Graham,D., Krendel, E.S., Reisener, W., 1965, Human Pilot Dynamics
in Vompensatory Systems, Theory, Models and Experiments with Controlled Element and
Focusing Function Variations. AFFDL-TR-65-15, July
[17] McRuer, D.T., Ashkenas, I.L., Pass, H.R., 1964, Analysis of Multiloop Vehicular
Control Systems, ASD-TDR-62-1014, March
[18] Stapelford, R.L., MacRuer,D.T, Magdaleno, R., 1966, Pilot Describing Function
Measurement in a Multiloop Task, NASA CR-542, August
[19] McRuer, D.T., Hofman,L.G, 1968, New Approaches to Human Pilot / Vehicle
Dynamic Analysis. AFFDL-TR-67-150, February
[20] Elkind, J.I., Falb, P.F., 1968, An Optimal Control Method For Prediction Control
Characteristics And Display Reqıirements of Manned-Vehicle systems. AFFDL-TR-67-187,
April
[21] Kleinman, D.L., Perkins,T.R., 1974, Modeling Human Performance in a Time-Varying
Anti-Aircraft Tracking Loop , IEEE Transactions on Automatic Control, Vol.AC-19, No:4,
pp.297-306, August
[22] Weir, D.H., McRuer, D.T., 1970, Dynamics of Driver Vehicle Steering Control,
Automatica, Vol.6, pp.87-98
[23] Gingrich, C G; Kuespert, D R; McAvoy, T J., 1992, Modeling human operators using
neural networks, Chemical Engineering Department, University of Maryland, ISA
Transactions, Volume 31, Issue 3 pp 81-90
[24] Boss,J.F.T, Stassen, H.G., Lunterern, A.V., 1995, Aiding The Operator in the Manual
Control of A Space Manipulator, Control Eng. Practice, Pergamon, Vol.3 No.2 pp:223-230
[25] Hoc, J.M., 2000, From Human-Machine Interaction to Human-Machine Cooperation,
Ergonomics ,ISSN: 0014-0139 ,Volume 43, Issue 7 ,pp 833-843, July
[26] Murray, S A; Caldwell, B S., 1996, Human Performance and Control of Multiple
Systems, Human Factors ,ISSN: 0018-7208 ,Volume 38, Issue 2 ,Pages 323-329, June
[27] Takashima, M., 1980, Yoshizawa, S; Nagumo, J., Human Operator Dynamics in
Manual Tracking Systems With Auditory Input, Biological Cybernetics ,ISSN: 0340-1200,
Volume 37, Issue 3 .pp 159-166
[28] Sutton, R., 1990, Modelling Human Operators in Control System Design, Royal Naval
Engineering College, Plymouth UK
[29] McCulloch, W.S.,Pitts,W.A., 1943, A Logical Calculus of the Ideas Immanent in
Nervous Activity, Bulletin of Mathematics and Biophysics, 5, pp.115-133
[30] Hebb, D. O., 1949, The Organization of Behaviour, New York, Willey, introduction
and Chapter 4 The First Stage of Perception , growth of the assembly, pp.60-78
[31] Caianiello, E.R., 1961, Outline Of A Theory Of Thought-Processes and Thinking
mavhines, Journal of Theoretical Biology, 2, pp. 204-235
[32] Jang, J.R., and Sun, C.T., 1995, Neuro-Fuzzy Modeling and Control, Proc. of IEEE,
83(3), 378-405
[33] Jang, J.R., 1993, ANFIS:Adaptive-Network-Based Fuzzy Inference System, IEEE
Trans.Syst.,Man, Cybern., 23(3), 665-684
[34] Jang, J.R., Sun, C.T., Mizutani, E., Neuro-Fuzzy and Soft Computing A Computational
Approach to Learning and Machine Intelligence, Prentice Hall, USA
[35] Patrick,J.,Duncan K.D., 1988, Training, Human Decision Making And Control,
University of Wales
[36] Zapato, G.O.A., Galvao, R.K.H.,Yoneyema,T., 1999, Extracting Fuzzy Control Rules
from Experimental Human operator Veri, IEE Trans. on Systems, Man, and Cybernetics-
Part B: Cybernetics, Vol.29, No:3,pp.398-406, June
[37] Şimşir, U., 2007, Dar Su Yolarında El Kumandası ile Seyir Yapan Gemilerin
Konmunun Yapay Sinir Ağları Kullanılarak Öngörülmesi, Doktora Tezi, İTÜ, Şubat
[38] Ertugrul, Ş., 2008, Modeling Human Operator Actions Using Adaptive Neuro-Fuzzy
Inferencing System Based on a Man-Machine Interaction Computer Experiment,
Engineering Applications of Artificial Intelligence, vol.21, pp.259-268

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