Haiquan Wang
Papers
2
Total Citations
11
H-Index
2
About
Haiquan Wang is a researcher specializing in nonlinear control systems, robotics, and fault diagnosis. His work focuses on advancing the precision and reliability of robotic systems, particularly in the presence of uncertainties and faults. Wang’s major contributions include developing a robust nonlinear perfect tracking control method for robot arms using an operator-based robust right coprime factorization approach, which effectively compensates for plant uncertainties. This work, published in 2015, has garnered 7 citations and addresses a critical challenge in achieving high-performance control in real-world robotic applications. More recently, in 2022, Wang proposed a novel fault mechanism analysis and diagnosis method for closed-loop drive systems of industrial robots, leveraging nonlinear spectrum analysis. This approach overcomes the limitations of traditional methods by incorporating nonlinear characteristics often neglected in fault diagnosis, offering deeper insights into fault mechanisms. With 4 citations, this work underscores his commitment to enhancing robot safety and maintenance. Wang’s research bridges theoretical control advancements with practical industrial needs, making significant strides in robust control and intelligent fault detection for modern automation systems.
Research Focus
Key Achievements
Top Papers
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