Event-Triggered Adaptive Position-Force Control of Robotic Manipulators in Medical and Cooperative Industrial Applications

Abstract

Motivated by human dexterity and coordination, robotic manipulators have drawn the attention of researchers in recent years. These manipulators can mimic the human manipulation property and provide assistance at improved accuracies far exceeding those of human operators. Therefore, the adoption of robotic manipulators is demanded in diverse medical and industrial scenarios to fulfill several tasks such as ultrasound scans, rehabilitation exercises, and cooperative manipulation. On the other hand, networked control systems (NCSs) have become very popular in the last few years, introducing several benefits such as flexibility, reliability, and ease of maintenance for practical robotic applications. However, the implementation of such communication poses different constraints, including limited bandwidth channels. Moreover, parametric uncertainties and interaction forces are crucial to consider in the human-robot and robot-environment interaction tasks. Therefore, designing an appropriate controller to achieve the desired position and force tracking for robotic manipulators under the network-induced limited bandwidth, parametric uncertainties, and interaction forces is challenging and open to research. This thesis proposes a few simultaneous position-force control schemes to overcome the aforementioned challenges and maintain the performance and stability of the robotic manipulators in different medical and cooperative industrial applications.