Papers
1
Total Citations
2
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About
Dr. Jianguo Guo is a leading researcher in advanced nonlinear control systems, with a primary focus on robotics, fractional-order dynamics, and intelligent neural network-based control. His most influential work, "Fractional-Order Nonsingular Terminal Sliding Mode Control of Uncertain Robot Neural Network," addresses critical challenges in robotic trajectory tracking—namely, low accuracy and slow convergence under uncertainties and external disturbances. In this study, Dr. Guo pioneered an adaptive fractional-order fast terminal sliding mode controller integrated with a radial basis function (RBF) neural network, achieving robust, high-precision control without singularities. This contribution has garnered attention for its theoretical elegance and practical applicability in uncertain robotic environments. With a growing citation record, Dr. Guo’s research bridges the gap between fractional calculus and real-time robotic control, offering novel solutions for autonomous systems. His work is particularly notable for combining mathematical rigor with engineering implementation, making it a valuable reference for students and researchers in control theory, mechatronics, and intelligent robotics. Dr. Guo continues to advance the frontiers of adaptive and fractional-order control, shaping the future of resilient robotic systems.
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Top Papers
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