A Comparison of Model Predictive Control and PID Temperature Control in Friction Stir Welding

Keywords

Model predictive control, Friction stir welding, Friction stir processing, Heat source method, Temperature control, PID, Temperature models

Abstract

Temperature control of friction stir welding (FSW) via model predictive control (MPC) is investigated in Al 7075-T7. Two MPC controllers are compared against two well-tuned PID controllers to obtain a direct comparison of MPC and current FSW controllers. One MPC controller uses a first-order plus dead-time (FOPDT) model derived from a simplified conduction-advection view of the stir zone. The other MPC controller uses the Hybrid Heat Source model that describes heat conduction in the plate and tool.

At quasi steady-state conditions, all four controllers can easily hold temperature within 2 °C of the setpoint in the absence of large disturbances. Once the weld is past the initial traverse, the FOPDT controller is superior to the Hybrid Heat Source controller with regards to modeled-disturbance rejection and setpoint changes. The FOPDT controller is competitive with well-tuned PID controllers in this region of the weld. During the initial traverse, the Hybrid Heat Source controller and PID controller with regulator gains were able to control temperature within 5 °C of the setpoint, compared to a typical deviation of 20–30 °C when uncontrolled. During this period, the FOPDT controller and PID controller with servo gains could not maintain satisfactory temperature control.

MPC is demonstrated to be a viable control method for FSW. Temperature control before reaching steady state for both MPC and PID is shown to be feasible, but more difficult than for steady state. Recommendations are given for when each controller might be preferred in various circumstances, based upon the results shown herein.

Original Publication Citation

Taysom, S., Hedengren, J., & Sorensen, C. (2017). A comparison of model predictive control and PID temperature control in friction stir welding. Journal of Manufacturing Processes, 29. https://www.sciencedirect.com/science/article/pii/S1526612517301792

Document Type

Peer-Reviewed Article

Publication Date

2017-10

Permanent URL

http://hdl.lib.byu.edu/1877/4033

Publisher

Elsevier

Language

English

College

Ira A. Fulton College of Engineering and Technology

Department

Chemical Engineering

University Standing at Time of Publication

Associate Professor

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