Adaptive predictive decoupling control of full penetration process in GTAW
13 Sep 1992-pp 938-943
TL;DR: In this paper, an adaptive generalized predictive decoupling control scheme is constructed for non-minimum-phase plants with a large and variable order, variable delays, and variable model parameters.
Abstract: The control of a nonminimum-phase plant with a large and variable order, large and variable delays, and variable model parameters is addressed. The model concern is the full penetration process. The generalized predictive algorithm presented by D.W. Clarke et al. (1987) is selected as the principal control strategy, and an adaptive generalized predictive decoupling control scheme is constructed. Simulations are performed to determine the default parameters of the algorithm. The effectiveness and the robustness to various disturbances (which result in variation in order, delays and parameters) of the designed control scheme have been confirmed by both the simulations and the experiments. >
Citations
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Journal Article•
TL;DR: In this article, a structured-light three-dimensional vision sensor is employed to measure the weld-face geometric parameters of the cross-section of full joint penetration welds in real-time.
Abstract: Many studies have been conducted into the control of weld joint penetration utilizing a weld-face sensor. In this paper, a weld-face vision-based strategy is presented. The strategy employs a structured-light three-dimensional vision sensor to measure the weld-face geometric parameters of the cross-section of full joint penetration welds in real-time. The principle behind this strategy depends on the relationship between the root surface weld width and the measured weld-face parameters
62 citations
01 Jan 2003
TL;DR: In this paper, the automatic control techniques that have been used in the Gas Metal Arc Welding (GMAW) process are analyzed. But, the authors do not discuss the safety aspects of the welding operation.
Abstract: This chapter analyzes the automatic control techniques that have been used in the Gas Metal Arc Welding (GMAW) process. It provides a brief discussion of manual control and many automatic control techniques. Automatic welding simply means that some aspects of the welding operation are performed without the intervention of human such as welder or welding operator. Closed-loop control strategies have several forms such as optimal control, adaptive control, robust control, and learning or intelligent control. Statistical quality control (SQC) is the application of statistical methods for the purpose of determining if a given component of production (input) is within acceptable statistical limits and if there is some result of production (output) that can be shown to be statistically acceptable to required specifications. On the other hand, statistical process control (SPC) is the application of statistical methods for the purpose of determining if a given process is within the operating control parameters established by statistical procedures. A number of different hazards present in electric arc welding and their effective control are achieved by conventional environmental engineering solutions.
6 citations
01 Jan 2008
TL;DR: In this paper, the authors propose a method of disassembling a set of disassembly points, called DISSERTATION, which is based on disassemblage-of-dispersal.
Abstract: OF DISSERTATION
3 citations
Cites background from "Adaptive predictive decoupling cont..."
...1 Control of full penetration on DB-GMAW The full penetration process is a non-minimum phase plant with large and variable model order, large and variable delays and variable model parameters [59]....
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TL;DR: In this paper, an experimental system is constructed to implement dual bypass gas metal arc welding (DB-GMAW) and full penetration weld is produced on aluminum, and a nonlinear model is proposed, identified, and validated based on process analysis and through experiments.
1 citations
01 Jan 2011
TL;DR: In this paper, a strong coupling multi-input and multi-output (MIMO) system was simulated using pulse current duty cycle and wire feed speed as control input, and wire extension and pool width as control output.
Abstract: Based on system identification of pulsed MIG welding process for aluminum alloy, due to strong coupling among the welding parameters, PID controller, fuzzy PID controller and neural network inverse controller were designed, the strong coupling multi-input and multi-output (MIMO) system was simulated using pulse current duty cycle and wire feed speed as control input, and wire extension and pool width as control output. The results show that the neural network inverse control provides faster response and better robustness, which lays a foundation for decoupling control of aluminum pulsed MIG welding.
1 citations
Cites methods from "Adaptive predictive decoupling cont..."
...In [1, 2 ] multi-variable control model was established on the basis of selfadaptive control method in GMAW....
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References
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TL;DR: A novel method—generalized predictive control or GPC—is developed which is shown by simulation studies to be superior to accepted techniques such as generalized minimum-variance and pole-placement and to be a contender for general self-tuning applications.
3,576 citations
DOI•
01 Sep 1986TL;DR: In this paper, the state estimation and adaptive control of fed-batch fermentation for penicillin production is investigated. But the work forms part of an industrial collaborative project, the aim of which is the optimising control of large feed-batch fermenters, and the results obtained from simulation studies while validation studies are carried out on both a 30 1 pilot plant fermenter and the industrial plant.
Abstract: The paper describes an investigation into the application of state estimation and adaptive control to fed-batch fermentation for penicillin production. The work forms part of an industrial collaborative project, the aim of which is the optimising control of large fed-batch fermenters. Estimates of biomass are made using an extended Kalman filter from on-line measurements of carbon dioxide production rate and fermentation volume. The estimated biomass is controlled to a reference trajectory by an adaptive generalised predictive controller manipulating the sugar feed rate. A comparison of performance is made with control by conventional proportional plus integral (PI) techniques. The results presented are obtained from simulation studies while validation studies are carried out on both a 30 1 pilot plant fermenter and the industrial plant.
36 citations
01 Jan 1992
1 citations