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About

Shuisheng Zeng is a leading researcher in advanced robotics, specializing in the intelligent control, dynamics, and vibration suppression of rigid-flexible parallel robots. His work addresses fundamental challenges in robotic precision and stability, particularly for high-speed, complex systems like the Delta robot. Zeng’s most impactful contribution is the development of an adaptive memetic differential evolution-back propagation-fuzzy neural network algorithm, which significantly enhances robot control accuracy and adaptability, earning 28 citations. He has also pioneered the application of singular perturbation methods to decompose rigid-flexible coupled systems into slow and fast subsystems, enabling effective trajectory control and vibration suppression—a breakthrough cited 14 times. Additionally, his studies on micro-chaotic phenomena in flexible robots provide critical insights into system stability. With a growing citation record and recent work on dynamics parameter identification for intelligent control, Zeng is shaping the future of next-generation robotic systems, making his research essential for engineers and students advancing automation and mechatronics.