Robust Auto-Intelligent Sliding Accuracy for High Sensitive Surgical Joints

摘要

The use of robots in medical applications has increased considerably in the last decade. Today, there are robots being used in complex surgeries such as those of the brain, eye, heart, and hip. Complex surgeries have complex requirements, such as high precision, reliability over multiple and long procedures, ease of use for physicians and other personnel, and a demonstrated advantage, to the patient, of using a robot. Furthermore, all new technologies in the medical area have to undergo strict regulatory clearance procedures, which may include clinical trials, as outlined by various government regulatory agencies. Variable Structure controller is a powerful nonlinear robust controller under condition of partly uncertain dynamic parameters of system. This controller is used to control of highly nonlinear systems especially for surgical joints. Limitation of robustness in uncertain dynamic parameter is the main drawback in pure Variable Structure controller. This challenge in pure Variable Structure controller and intelligent Variable Structure controller is reduced by using sliding surface auto-tuning. Artificial intelligence theory is used to reduce the system's limitation. In this research, PI fuzzy sliding surface tuning Variable Structure controller is introduced. To eliminate the uncertain limitation, 49 rules Mamdani inference system is design and supervised the Variable Structure methodology. This method is based on resolve the on line sliding surface slope as well as improve the output performance by tuning the sliding surface slope coefficient. The sliding surface gain ( ) of this controller is adjusted online depending on the last values of error () and integral of error ( ) by sliding surface slope updating factor (). Fuzzy-based tuning controller is stable controller, which does not need to limits the dynamic model of surgical joints.