Abstract
By combining manual welders (with intelligence and versatility) and automatic welding systems (with accuracy and consistency), an intelligent welding system for human soft tissue welding can be developed in medicine. This paper presents a data-correction control approach to human welder intelligence, which can be used to control the automated human soft tissue welding process. Human soft tissue welding can preconnect the excised tissue, and the shape of the tissue at the junction ensures the recovery of the operative organ function. This welding technology has the advantages of rapid operation, minimal tissue damage, no need for suture materials, faster recovery of the mechanism and properties of the living tissue, and the maintenance of the function of the organs. Model of the welding system is identified from the data; an open-closed-loop iterative learning control algorithm is then proposed to improve the tracking accuracy of the system. The algorithm uses the tracking error of current and previous to update the control law. Meanwhile, to further improve the accuracy under the conditions of external interference, a system correction term is added to the proposed ILC algorithm, which can be adjusted according to the system’s errors and output and improve the capability of the target tracking greatly. A detailed convergence analysis for the ILC law has been given. Simulation results verify the feasibility and effectiveness of the proposed method for GTAW control tasks.
Highlights
Automatic welding [1,2,3] is a welding process which has been widely used in precision and stable joining
Focusing on welding quality issues, many domestic and foreign welding research works [9,10,11] have invested a lot of manpower and material resources, including arc height control [12], weld automatic tracking control [13, 14], and welding penetration control [15,16,17]. rough the application of various automatic control technologies, the welding process is automatically controlled to ensure the normal progress of the welding process
After the biomedical welding system is learned for 5 times, 10 times, 15 times, and 20 times respectively, the effect of the welding process and trace control is shown in Figures 3 and 4
Summary
Automatic welding [1,2,3] is a welding process which has been widely used in precision and stable joining. Erefore, human soft tissue welding is proposed, which uses high-frequency current to weld the human tissue. E algorithm inherits the characteristics of the traditional ILC control, such as simple structure, high reliability, and easy engineering implementation, and overcomes the shortcomings of the closed-loop controller, such as poor followability and inaccurate adjustment under strong interference, and has strong nonlinear and uncertain characteristics. The biggest disadvantage of welding technology is that it is easy to cause tissue burns, which lead to insufficient strength of the connection between tissues, so that the welding anastomosis is not firm enough, and the high incidence of postoperative complications is mainly due to the difficulty in controlling the position and current of the welding machine during the use. E biomedical welding process studied in this paper takes the welding current as the control input and the fracture position at the wound as the system output.
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