This application paper addresses the control of a nonminimum-phase plant with variable large orders and delays. The process concerned is full penetration gas tungsten arc welding. Based on an analysis of accepted adaptive algorithms, the generalized predictive control algorithm presented by Clarke et al. is selected as the principal control strategy. An adaptive generalized predictive decoupling control scheme is constructed. To decouple our nonminimum-phase multivariable plant, a predictive decoupling algorithm is also proposed. Simulations are performed to determine the default parameters of the algorithms. The performance has been tested by both simulations and experiments.
Control of weld penetration is currently one of the most important and crucial research issues in the area of welding. The weld pool can provide accurate and instantaneous information about the weld penetration, however, the establishment and confirmation of the correlation between weld pool and weld penetration require numerous accurate measurements and suitable geometrical modeling of weld pool. A normalized model is proposed to characterize the weld pool two-dimensionally. More than 6,000 weld pools are measured from experiments using a developed real-time weld pool sensing system. A data analysis shows that the weld penetration is correlated with the weld pool which is specified by the three characteristic parameters proposed in the study. However, the correlation is nonlinear. To approximate the complicated nonlinearity, neural networks are used. Comparative modeling trails show that the weld penetration can be more accurately calculated if the adjacent weld pools are also used. This implies that the correlation between the weld penetration and weld pool is dynamic. Hence, an on-line nonlinear dynamic estimation system is developed to estimate the weld penetration.
We observe an unusual combination of normal and superconducting state properties without any signature of strong spin fluctuations in single-crystal Ir 3 Te 8 .The electrical resistivity does not saturate by 700 K, but exhibits a low resistivity ratio; and it also exhibits two extended linear regimes (approximately 20 to 330 K and 370 to 700 K) with the same slope, separated by a small hysteretic interval marking a strongly first-order phase transition from cubic to rhombohedral lattice symmetry at T S = 350 K. The electronic heat capacity coefficient (11 mJ/mole-K 2 ) is consistent with a net diamagnetic, rather than Pauli paramagnetic, normal state that yields to superconductivity below a critical temperature T C = 1.8 K. The size of the heat capacity jump near T C indicates bulk superconductivity.2
Weld penetration sensing and control with a weld-face sensor are among the most relevant research issues in automated welding. Previous studies showed that the geometry of the weld pool contains accurate, instantaneous information about the weld penetration. In this study, the weld pool is measured in real-time to provide the feedback of the weld penetration, and the welding current is selected as the control variable. Analyses reveal that the influence of mandatory variations in welding conditions on the process dynamics can be described by an interval model that has bounded parameter intervals. A robust control algorithm with guaranteed closed-loop stability is used to overcome the interval uncertainty in the process dynamics. Dynamic experiments are performed using different welding conditions and varied welding parameters. From the experimental data the bounded parameter intervals are identified for the model of the process being controlled. Closed-loop control experiments are done under different perturbations. Experimentation shows that the variations encountered in practical welding can be overcome by the developed control system. In addition to penetration control, this work provides an example for developing robust manufacturing process control systems based on objective quantitative descriptions of the process uncertainty.
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