A variety of geometric, material structure, and stress/distortion attributes are needed to characterize the quality of thermally manufactured products. Because of in-process sensing difficulties and transportation lags, these features must be regulated in real time through appropriate thermal outputs, measured by non-contact infrared pyrometry. In thermal processes with a localized, sequentially moving heat source, the necessary heat input distribution on the part surface is supplied by an innovative timeshared or scanned torch modulation, in a raster or vector pattern. A unified lumped multivariable and a distributed-parameter quasilinear modeling formulation provide a design methodology and real-time reference for the development of finite- or infinite-state adaptive thermal control systems. These controllers modulate the power and motion of a single torch, supplying distinct concentrated heat inputs or a continuous power distribution on the part surface, so as to obtain the specified thermal characteristics or the entire temperature field. These regulation strategies are computationally tested and implemented experimentally in arc welding, but their applicability can be extended to a variety of thermal manufacturing processes.

Issue Section:
Technical Papers
Topics:
Manufacturing, Heat, Arc welding, Control equipment, Control systems, Design methodology, Modeling, Stress, Temperature, Transportation systems
1.
Astrom, K. J., and Wittenmark, B., 1992, Computer-Controlled Systems, 2nd ed, Prentice-Hall.
2.
Carslaw, H. S., and Jaeger, J. C., 1959, Conduction of Heat in Solids, 2nd ed, Oxford Press, London U.K.
3.
Cristensen
N.
,
Davies
V. L.
, and
Gjermundsen
K.
,
1965
, “
The Distributions of Temperatures in Arc Welding
,”
British Welding Journal
, Vol.
12
, Feb., pp.
54
–
75
.
4.
Delfour, M., Bensoussan, A., and Mitter, S. K., 1983, Linear Infinite Dimensional Systems, MIT Press, Cambridge, MA.
5.
Doumanidis, C. C., 1988, “Modelling and Control of Thermal Phenomena in Welding,” Ph.D. thesis, Department of Mechanical Engineering, MIT, Cambridge, MA.
6.
Doumanidis
C. C.
, and
Hardt
D. E.
,
1991
, “
Multivariable Adaptive Control of Thermal Properties During Welding
,”
ASME JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL
, Vol.
113
, No.
1
, pp.
82
–
92
.
7.
Doumanidis, C. C., 1993, “Eulerian Multiple-Source Simulation of Serial Fusion Manufacturing Processes,” IASTED Intl. Conf. on Applied Modelling and Simulation, Vancouver, Canada.
8.
Goodwin
G. C.
,
Ramadge
P. J.
, and
Caines
P. E.
,
1980
, “
Discrete-Time Multivariable Adaptive Control
,”
IEEE Transactions on Automatic Control
, Vol.
AC-25
(
3
), June, pp.
449
–
456
.
9.
Hardt, D., 1990, “Real-Time Process Control: Limits to Progress,” ASME Manufacturing Review.
10.
Linnert, G. E., et al., 1968, “Arc Welding,” Metals Eng. Inst, ASM Intl, Metals Park, OH.
11.
Lukens, W. E., and Morris, R. A., 1982, “Infrared Temperature Sensing of Cooling Rates for Arc Welding Control,” Welding Journal, June, pp. 27–39.
12.
Rohrs
C. E.
,
Valavani
L.
,
Athans
M.
, and
Stein
G.
,
1985
, “
Robustness of Adaptive Control Algorithms in the Presence of Unmodelled Dynamics
,”
IEEE Trans. on Automatic Control
, Vol.
AC-30
No.
9
, pp.
881
–
889
.
13.
Webster, P. J., 1992, “Welding Applications on Neutron Strain Scanning,” ASM Intl. Trends in Welding Science and Technology, Gatlinburg, TN, pp. 95–98.
14.
Yang, I. J., and Chen, S. H., 1992, “The Properties of 316L Steel Tubes Welded by Pulse TIG Welding Technology,” ibid. pp. 575–580.
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