THE APPLICATION OF MULTIVARIABLE ADAPTIVE CONTROL TO AN INDUSTRIAL RUN-OF-MINE MILLING PROCESS

1991 ◽  
pp. 163-169 ◽  
Author(s):  
G. Metzner ◽  
I.M. MacLeod
Keyword(s):  
Adaptive Control ◽  
Milling Process

An Investigation of the End Milling Process Under Varying Machining Conditions

1989 ◽  
Vol 111 (1) ◽  
pp. 27-36 ◽  
Author(s):  
B. K. Fussell ◽  
K. Srinivasan
Keyword(s):  
Adaptive Control ◽  
Feedback Loop ◽  
End Milling ◽  
Milling Process ◽  
Operating Conditions ◽  
Machining Conditions ◽  
Adaptive Control Systems ◽  
Proper Design ◽  
Process Mechanics ◽  
End Milling Process

Varying machining conditions are encountered in adaptively controlled machining situations where operating conditions such as the feedrate and spindle speed are adjusted continuously to achieve desired objectives. Proper design, of constraint-type adaptive control systems in particular, requires models of the milling process mechanics since the milling process is usually part of the feedback loop. The adequacy of available models of milling process mechanics is evaluated here experimentally for many cases of varying machining conditions, including changing axial and radial depths of cut and feedrate. Startup transients in the force as the cutter engages the workpiece are also investigated. The significance of dynamic effects in the milling process and of effects such as runout, for constraint-type adaptive control system design, is then evaluated.

CAD Assisted Adaptive Control for Milling

1991 ◽  
Vol 113 (3) ◽  
pp. 444-450 ◽  
Author(s):  
A. Spence ◽  
Y. Altintas
Keyword(s):  
Adaptive Control ◽  
Control Method ◽  
Adaptive Controller ◽  
Milling Process ◽  
Force Model ◽  
Online Information ◽  
Geometric Information ◽  
Milling Force ◽  
Part Geometry ◽  
Milling Force Model

A milling process adaptive control method, which prevents force overshoots during sudden part geometry changes, has been developed by providing online information to the controller from the part’s CAD representation. A first-order discrete model structure to represent the milling process for adaptive control was analytically developed and experimentally identified. Provided with geometric information obtained from the part’s CAD model, and utilizing the milling force model, the adaptive controller predicts the maximum cutting force expected in advance of dangerous immersion changes. The technique permits the controller to anticipate the changing workpiece in time to eliminate force overshoots which would otherwise break the tool, yet adaptive control at all times remains active to respond to other geometrical and material variations. Simulation and experimental results are presented to confirm the viability of the proposed method.

Programming of milling process using adaptive control system

Mechanik ◽  
2016 ◽  
pp. 218-219
Author(s):  
Jan Burek ◽  
Paweł Sułkowicz ◽  
Piotr Żurek ◽  
Marcin Sałata
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Milling Process ◽  
Adaptive Control System

Control of Cutting Force for End Milling Processes Using an Extended Model Reference Adaptive Control Scheme

1996 ◽  
Vol 118 (3) ◽  
pp. 339-347 ◽  
Author(s):  
S. J. Rober ◽  
Y. C. Shin
Keyword(s):  
Adaptive Control ◽  
Cutting Force ◽  
End Milling ◽  
Model Reference Adaptive Control ◽  
Milling Process ◽  
Recursive Least Squares ◽  
Extended Model ◽  
Random Component ◽  
Model Reference ◽  
Model Reference Adaptive

In this work an extended Model Reference Adaptive Control (MRAC) technique is used to control the cutting force of an end milling process. The technique incorporates Zero Phase Error Tracking Control (ZPETC) into the MRAC system. The extended MRAC controller remains stable even in the presence of marginally stable and nonminimum phase process zeros. A modified recursive least-squares estimation algorithm is used for on-line parameter identification. Simulation results are presente to compare the extended MRAC controller to the standard MRAC controller. A microprocessor system is used to implement adaptive force control of a single-input single-output milling process where the microprocessor monitors the system cutting forces and controls the desired feedrate. A constant cutting force is maintained in the presence of time-varying plant gains and a high random component of the output force. Experimental results are presented for standard MRAC and extended MRAC controllers for comparison.

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