System identification
System identification (2nd ed.): theory for the user
System identification (2nd ed.): theory for the user
Feedback control systems (4th ed.)
Feedback control systems (4th ed.)
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
| Hi-index | 0.00 |
This paper describes a promising approach using simulation to support design of real time control in robotized metal fusion welding. For this case study, a simple PI-controller was employed but this approach is intended for general applications where any model-based controller is possible. The finite element method has been used for thermal modeling of gas tungsten arc welding on a simplified test object. Data for model calibration and validation was acquired through thermal imaging during weld experiments on test objects of the alloy SS316. An optimization scheme for inverse modeling was employed in the calibration of the distributed weld process model. Parametric system identification was applied to get a low order model of the single-input single-output dynamics between a simulated welding source (actuator) and a simulated sensor. The control input is welding current and the measured output is a moving spot temperature. This low order model was then successfully used for controller design and the closed-loop performance was evaluated by simulation of the weld process model.