Qijiang Yu

Papers

Total Citations

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About

Qijiang Yu is a robotics and control systems researcher whose work focuses on the intelligent motion control of mobile robots, with particular emphasis on trajectory tracking and dynamic control strategies. Yu's most notable contribution lies in the development of hybrid control architectures that combine classical control theory with neural network intelligence. His landmark 2006 paper on tracking control of mobile robots, which has garnered 12 citations, introduced an innovative scheme integrating backstepping-based velocity control with improved Radial Basis Function Neural Networks (RBF NNs) for torque control, leveraging sliding mode principles to handle system dynamics robustly. Building on this foundation, Yu extended the framework in 2009, presenting a real-time trajectory tracking solution that further refined the IRBFNN-based sliding mode approach for practical implementation. Together, these works demonstrate a consistent research vision: bridging the gap between theoretical control design and real-world robotic performance. Yu's contributions offer valuable tools for researchers tackling the challenges of nonlinear robot dynamics, uncertainty compensation, and adaptive control, making his work a meaningful reference point in the mobile robotics control literature.