Pingxin Wang

Jiangsu University of Science and Technology

Papers

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About

Pingxin Wang is a leading researcher in advanced robotics and intelligent control systems, with a primary focus on the development of model-free adaptive control strategies for robotic exoskeletons. Wang’s most cited work, “Model-Free Adaptive Sliding Mode Robust Control with Neural Network Estimator for the Multi-Degree-of-Freedom Robotic Exoskeleton” (2020), introduces a groundbreaking control method that eliminates the need for exact dynamic models, relying solely on input-output data. This innovation addresses a critical limitation of traditional model-based approaches, which often falter in real-world applications due to system uncertainties and nonlinearities. By integrating sliding mode control with neural network estimation, Wang’s method enhances robustness and adaptability, achieving stable and precise trajectory tracking even under varying loads and disturbances. With 7 citations, this paper has influenced subsequent research in wearable robotics and rehabilitation engineering. Wang’s contributions are particularly notable for bridging the gap between theoretical control design and practical exoskeleton deployment, offering a scalable solution for human-robot interaction. Their work continues to inspire advances in adaptive robust control, making Wang a key figure in the evolution of intelligent, data-driven robotic systems.