Fuzzy logic control was originally introduced and developed as a model free control design approach. However, it unfortunately suffers from criticism of lacking of systematic stability analysis and controller design though it has a great success in industry applications. In the past ten years or so, prevailing research efforts on fuzzy logic control have been devoted to model-based fuzzy control systems that guarantee not only stability but also performance of closed-loop fuzzy control systems. This paper presents a survey on recent developments (or state of the art) of analysis and design of model based fuzzy control systems. Attention will be focused on stability analysis and controller design based on the so-called Takagi-Sugeno fuzzy models or fuzzy dynamic models. Perspectives of model based fuzzy control in future are also discussed

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A Survey on Analysis and Design of Model-Based Fuzzy Control Systems

This work was supported in part by the National Natural Science Foundation of China under Grants 61329301,
61374039, 61473163, and 61374127, the Hujiang Foundation of China under Grants C14002 andD15009, the Engineering and Physical Sciences Research Council (EPSRC) of the UK, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany.

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Fuzzy-Logic-Based Control, Filtering, and Fault Detection for Networked Systems: A Survey

Automatic welding technology is a solution to increase welding productivity and improve welding quality, especially in thick plate welding. In order to obtain high-quality multi-pass welds, it is necessary to maintain a stable welding bead in each pass. In the multi-pass welding, it is difficult to obtain a stable weld bead by using a traditional teaching and playback arc welding robot. To overcome these traditional limitations, an automatic welding tracking system of arc welding robot is proposed for multi-pass welding. The developed system includes an image acquisition module, an image processing module, a tracking control unit, and their software interfaces. The vision sensor, which includes a CCD camera, is mounted on the welding torch. In order to minimize the inevitable misalignment between the center line of welding seam and the welding torch for each welding pass, a robust algorithm of welding image processing is proposed, which was proved to be suitable for the root pass, filling passes, and the cap passes. In order to accurately track the welding seam, a Fuzzy-P controller is designed to control the arc welding robot to adjust the torch. The Microsoft Visual C++6.0 software is used to develop the application programs and user interface. The welding experiments are carried out to verify the validity of the multi-pass welding tracking system.

Autonomous seam acquisition and tracking system for multi-pass welding based on vision sensor

In this paper, an intelligent seam-tracking system is developed for fillet weld workpiece. Structured light vision is employed to detect the deviation of the welding torch. Two stripe lines are formed on the surface of the fillet weld workpiece by the structured laser light. Their intercepts are selected as the image feature, which can result in an approximately uncoupled relationship between the image feature and the movement of adjustment mechanism. A two-step feature-extraction method is designed to robustly detect the two lines in image. In order to get a favorable tracking precision in the welding process, a new self-tuning fuzzy controller is designed. Its input and output scaling factors are tuned according to its active working region. Moreover, a supervisory level is introduced into the control system to limit the output pulses in order to guarantee steady and safe tracking. Finally, experiments are well conducted to verify the performance of the proposed system and methods.

A Vision-Based Self-Tuning Fuzzy Controller for Fillet Weld Seam Tracking

Automatic multi-pass route planning is one of key technologies for thick plate in robotic metal active gas (MAG) arc welding. In this research, a scheme for the extracting feature points of the weld seam profile to implement automatic multi-pass route planning, and guidance of the initial welding position in each layer during MAG arc welding, is presented. It consists of two steps: first a vision sensor based on structured light is employed to capture laser stripes and molten pools simultaneously within the same frame, and the laser stripe, forming the weld seam profile is detected by a visual attention model based on saliency. Then a methodology of polynomial fitting plus derivatives for feature point extraction of the weld seam profile is suggested. With respect to the effectiveness of highlighting the laser stripe, the proposed model is much better than the classic ones in this field, whereas the feature point extraction methodology in this paper outperforms typical template matching. Finally, the performance of the proposed scheme is demonstrated on different weld seam images captured in different layers and different welding experiments. New vision sensor captures laser stripes and molten pools simultaneously.A visual attention model for detecting weld seam profiles is proposed.Three kinds of feature points of weld seam profiles can be extracted.Different images captured in different layers validate the proposed methods.The extracted feature points can be used for multi-pass route planning.

Weld seam profile detection and feature point extraction for multi-pass route planning based on visual attention model

This paper considers the problem of sensing and controlling torch position in the pulsed gas metal arc welding (P-GMAW) process. The attitude and positional control described is essential to the production of quality welds with a specified geometry. For constant current arc welding processes, as normally employed with P-GMAW, the arc voltage signal variations that occur as a function of changes in the contact-tube-to-work distance can be used to automatically control the welding system with respect to bead placement and proper sidewall fusion. However, the arc voltage signals are uncertain and noisy because of many inherent disturbances associated with the electrode tip, droplet formation, droplet detachment, and droplet transfer through the arc. To deal with the nonlinear time-varying process with its inherent stochastic disturbances associated with the metal transfer, the theory of fuzzy sets was used as a general framework to interpret the uncertain arc signals and provide logic for control. The fuzzy logic controller weld joint tracking system was implemented and tested with pulsed gas metal arc welds under a variety of conditions. The goal was to obtain quick and accurate response to tracking errors in the presence of disturbances. A series of experiments was conducted to evaluate the performance of the fuzzy logic controller. The experimental results show that the fuzzy logic controller was found to be suitable for these purposes and better than methods based on signal averaging and bipolar decision levels under these criteria.

Application of fuzzy logic to spatial thermal control in fusion welding

A model has been developed that correlates the anode temperature profile with the dynamic melting rate in gas metal arc welding. The components of this model are the electrode melting rate, the temperature dependent resistivity of the electrode, and the arc voltage. The differential equations describing the dynamic behaviour of the electrode extension were derived from the mass continuity and energy relations. The temperature of the electrode extension was determined by analysing conductive heat transfer and Joule heating effects. One­dimensional solutions for the temperature and heat content were used to obtain the dynamic melting rate equation. The purpose of the present paper is to provide quantitative analyses, concentrating on the thermal behaviour and the electrical characteristics of the arc welding system, to aid in achieving a fundamental understanding of the process, and to develop a dynamic model that can be used in adaptive control. The model is tested by comparison with experimental r...

Dynamic model for electrode melting rate in gas metal arc welding process

The dependence of electrode electrical parameters (resistivity and action) on temperature results in a variation of voltage drop along the electrode extension In the present work, effects and interactions of the temperature dependent electrical parameters in constant current gas metal arc welding and pulsed gas metal arc welding of mild steel are examined and the differences between these two welding processes are determined using the above mentioned electrical parameters, which are calculated based on a resistivity model The temperature dependent electrical parameters are also used to compute the electrode voltage drop and the arc voltage, which are very difficult to measure directly in practice Furthermore, the processes are compared using electrode resistive dissipation Use of the same input in both processes assists in the comparison of the two processes

Am Strauss

Papers

Application of fuzzy logic to spatial thermal control in fusion welding

Dynamic model for electrode melting rate in gas metal arc welding process

Comparison of constant current and pulsed gas metal arc welding processes on basis of electrode resistive dissipation