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About

Yeng Chai Soh is a multidisciplinary control systems researcher whose work spans robotics, fault-tolerant control, rehabilitation engineering, and multi-agent systems. With a career stretching from the early 1990s to the present day, Soh has made foundational contributions to constrained robot motion control, pioneering learning-based and robust adaptive approaches that enable manipulators to iteratively refine both motion and force accuracy — work that has accumulated dozens of citations and influenced industrial robotics practice. His 1999 paper on biped robot planning and control (79 citations) stands as his most impactful contribution, addressing the complex locomotion challenges that underpin modern humanoid robotics. Soh also advanced observer-based fault detection, designing sliding-mode observers capable of reconstructing faults in nonlinear systems (53 citations), and developed neural network-driven dead-zone compensation for fault-tolerant robot control. Beyond core robotics, his research extended into clinical rehabilitation, where he introduced integrated platforms combining body weight support, pelvic control, and over-ground walking for impaired gait recovery. His most recent work tackles cybersecurity threats in fuzzy multi-agent systems using distributed sliding-mode consensus strategies, demonstrating a remarkable ability to evolve with emerging challenges across more than three decades of influential research.