Song Ling

Papers

Total Citations

343

H-Index

About

Dr. Song Ling is a leading researcher in the field of nonlinear control systems, with a primary focus on the advanced control of flexible-joint robots. Her work addresses critical challenges in robotics, particularly the precise tracking control of these complex, underactuated systems. Dr. Ling’s major contributions lie in the development of innovative adaptive fuzzy control strategies that effectively handle system nonlinearities and practical constraints. Her highly cited 2019 paper (189 citations) introduced a novel command-filtered control approach, using fuzzy logic to approximate unknown dynamics and overcome the "explosion of complexity" inherent in traditional backstepping. Complementing this, her work on adaptive fuzzy dynamic surface control (154 citations) provided a robust solution for flexible-joint robots operating under input saturation, a common real-world limitation. By elegantly combining fuzzy logic systems with advanced control architectures, Dr. Ling has established a powerful framework for achieving high-performance, stable robot motion. Her research is foundational for engineers developing next-generation, high-precision robotic manipulators, and her papers serve as essential references for anyone working on the intersection of adaptive control and robotics.