We welcome original research articles and review articles on the topics mentioned below. The specific scope includes, but is not limited to: 1. Biophysiological, computational, and data-driven modeling approaches to account for the effect of VNS on the healthy and diseased physiology of internal organs, such as the heart, stomach, lungs, colons, urinary systems, etc. 2. System identification approaches applied to specific organ systems. 3. Parameter estimation techniques for physiological modeling of organs in healthy and diseased cases. 4. Application of AI/machine learning in modeling/optimizing the effect of VNS on specific organ physiology in healthy and diseased cases.
A physiology by stimulating vagal nerves, including classical control approaches as well as machine learning and reinforcement learning approaches.Autonomous systems, especially systems working outdoors such as AUVs, UAVs, and mobile robots often have uncertainties and encounter external
Spain phone number list disturbances in their working environments. The uncertainties can be the changing in their masses or the variant of internal parameters. The external disturbances can be obstacles, wind, waves, currents, or any other static or dynamic factors that interfere with or change the nominal conditions of the autonomous systems.
Without proper reactions or optimal control laws, the systems may fail to perform their tasks, or they may operate in unoptimized manners that lead to consuming more energy or time. Realization of the disturbances to drive the systems overcoming the interferences and instabilities to remain reliable and productive is key, and is what the researchers aim to address in this collection. This Research Topic proposes recent advanced approaches to robustly control autonomous systems with a focus on AUVs, UAVs, and robots. With recent developments in computer sciences, new hardware, software, and algorithms have been developed to be more powerful to support control engineers.
