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About

Kerui Peng is a leading researcher in soft robotics and intelligent control systems, with a focus on modeling and compensating for the complex nonlinear dynamics of soft pneumatic actuators (SPAs). Their work addresses a critical challenge in the field: the inherent hysteresis that degrades control performance in compliant robotic systems. Peng’s highly cited 2023 review on neural network-based control of robotic manipulators (63 citations) established a foundational framework for integrating artificial intelligence with robotic actuation. They further advanced the field by developing a novel fuzzy cascade strategy for dynamics control with hysteresis compensation, enabling SPAs to adapt across multiple environments (31 citations). In their most recent contributions, Peng introduced a global Koopman modeling strategy for hysteresis inversion-free predictive compensation (2023, 8 citations) and a data-driven Koopman framework tailored for soft robots (2025, 7 citations). These innovations represent a paradigm shift from traditional model-based approaches to data-efficient, model-free control. Peng’s work is pivotal for the next generation of soft robots—enabling safer, more precise, and adaptable machines for applications in medical devices, search-and-rescue, and human-robot interaction.