Soft manipulators face challenges in modeling and real-time control due to nonlinear dynamics, model mismatch and drift, as well as inadequate physical consistency of data-driven models. This paper proposes a Steady-State Constrained Adaptive Koopman Model Predictive Control (SSCAK-MPC) framework to tackle these challe...
Ya-Ping Cen, Zhao-Bing Liu· IEEE Transactions on Automat...· 0 citations
Soft robots pose significant challenges for model-based control due to their inherent high dimensionality and nonlinearity. To tackle these challenges, this letter develops a robust model predictive control (MPC) framework for soft robots, referred to as SSMR-PF-EKF, by adopting physics-data fused spectral submanifold...
Kai-Wei Zheng, Zhao-Bing Liu· IEEE Robotics and Automation...· 0 citations
Soft robotics has emerged as an important direction in robotics because of its inherent compliance and adaptability. Despite these advantages, conventional soft actuators often remain constrained in design flexibility, functional programmability, and mechanical performance. Mechanical metamaterials—engineered artificia...