Physics-Informed Modeling and Control of Multi-Actuator Soft Catheter Robots

Catheter-based endovascular interventional procedures have become increasingly popular in recent years as they are less invasive and patients spend less time in the hospital with less recovery time and less pain. These advantages have led to a significant growth in the number of procedures that are performed annually. However, it is still challenging to position a catheter in a target vessel branch within the highly complicated and delicate vascular structure. In fact, vessel tortuosity and angulation, which cause difficulties in catheterization and reaching the target site, have been reported as the main causes of failure in endovascular procedures. Maneuverability of a catheter for intravascular navigation is a key to reaching the target area; ability of a catheter to move within the target vessel during trajectory tracking thus affects to a great extent the length and success of the procedure. To address this issue, this paper models soft catheter robots with multiple actuators and provides a time-dependent model for characterizing the dynamics of multi-actuator soft catheter robots. Built on this model, an efficient and scalable optimization-based framework is developed for guiding the catheter to pass through arteries and reach the target where an aneurysm is located. The proposed framework models the deflection of the multi-actuator soft catheter robot and develops a control strategy for movement of catheter along a desired trajectory. This provides a simulation-based framework for selection of catheters prior to endovascular catheterization procedures, assuring that given a fixed design, the catheter is able to reach the target location. The results demonstrate the benefits that can be achieved by design and control of catheters with multiple number of actuators for navigation into small vessels.

Modeling and Control of Grid-Connected Solar-Wind Hybrid Micro-Grid System with Multiple-Input Ćuk DC-DC Converter for Household & High Power Applications

There is a continuous global need for more energy, which must be cleaner than energy produced from the conventional generation technologies. As such, this need has necessitated the increasing penetration of distributed generation technologies and primarily on renewable energy sources. This paper presents a dynamic modeling and control strategy for a sustainable micro-grid, principally powered by multiple renewable energy sources (solar energy, wind energy and Fuel cell), micro sources (such as diesel generator, micro-gas turbine etc.) and energy storage scheme. More importantly, a current-source-interface, multiple-input dc-dc converter is utilized to coordinate the sustainable power sources to the main dc bus. Thus, for tracking maximum power available in solar energy, maximum power point tracking algorithm is applied. The proposed system is designed to meet load demand, manage power flow from various sources, inject excess power into the grid, and charge the battery from the grid as needed. More so, the proposed converter architecture has reduced number of power conversion stages with less component count, and reduced losses compared to existing grid-connected hybrid systems. This improves the efficiency and reliability of the system. The utilization of energy storage is essential owing to the intermittent nature of the renewable energy sources and the consequent peak power shift between the sources and the load. Following this further, a supervisory control system is designed to handle various changes in power supply and power demand by managing power intermittency, power peak shaving, and long-term energy storage. The entire hybrid system is described given along with comprehensive simulation results that reveal the feasibility of the whole scheme. The system model is designed and simulated in MATLAB SimPowerSystem in order to verify the effectiveness of the proposed scheme.

Underwater Soft Robotics: A Review of Bioinspiration in Design, Actuation, Modeling, and Control

Nature and biological creatures are some of the main sources of inspiration for humans. Engineers have aspired to emulate these natural systems. As rigid systems become increasingly limited in their capabilities to perform complex tasks and adapt to their environment like living creatures, the need for soft systems has become more prominent due to the similar complex, compliant, and flexible characteristics they share with intelligent natural systems. This review provides an overview of the recent developments in the soft robotics field, with a focus on the underwater application frontier.