Robust Semi-passive Velocity Field Control with Boundedness Guarantees for Safe Interaction between Mechanical Systems and Physical Environment
2026-08-31 • Robotics
Robotics
AI summaryⓘ
The authors study a way to control mechanical systems that interact safely with their environment by managing energy flow. Traditional methods keep the system always passive, which is safe but limits performance. They propose a smarter controller that allows better performance by relaxing these safety limits when energy is low but ensures safety by enforcing passivity only when energy gets too high. Their method also handles unexpected disturbances and keeps the system's energy and states within safe bounds. Simulations show that this approach can balance task success and safety better than fully passive controls.
energetic passivitymechanical system controlforce-velocity pairclosed-loop systemsemi-passive controltime-varying controlpower flow constraintexternal disturbancesrobust controlsafe human-robot interaction
Authors
Van Trong Dang, Sumitaka Honji, Takahiro Wada
Abstract
Controllers that guarantee energetic passivity with respect to the pair of external force and velocity realize safe interaction between the mechanical system and its physical environment. However, solely adhering to energetic passivity constraints may impose fundamental limitations on control performance and, in some cases, prevent the successful execution of controlled tasks. In addition, external disturbances from the physical environment can drive the system energy level and states beyond operational regions, thereby undermining task performance and safety. In this paper, we study a robust time-varying semi-passive velocity field control to aim to relax the inherently conservative nature of fully passive control methods in a controlled manner. Specifically, the proposed control method guarantees passivity of the closed-loop system with respect to the force-velocity input-output pair when the energy level exceeds a predefined level, while permitting non-passive behaviors to preserve task performance otherwise. Furthermore, the energy level and the states of the closed-loop system are proved to converge to bounded domains even in the presence of unpredicted disturbances. Additionally, the proposed method also enables constraining power flow between the closed-loop system and its physical environment to enhance safety in the interaction process. Numerical simulation examples demonstrate the effectiveness of the proposed method.