Papers
4
Total Citations
59
H-Index
3
About
Jianrong Chen is a leading researcher in computational mathematics and neural dynamics, specializing in the design of advanced zeroing neural network (ZNN) models for solving complex, time-varying problems. His major contributions center on developing discrete-time ZNN frameworks that unify the solution of different-kinds of future matrix equations—including Lyapunov equations, matrix inversion, and generalized inversion—as well as tackling future different-layer nonlinear and linear equation systems. Chen’s work on acceleration-level repetitive motion planning and control (ALRMPC) for redundant robot manipulators has also been influential, with his eight-node and nine-instant discretization formulas enabling more accurate and stable real-time computations. His most-cited paper (23 citations) introduces a new eight-node DZNN model that establishes a zeroing equivalency theorem, while his unified solution approach (17 citations) provides a powerful tool for diverse matrix equation problems. Chen’s research has direct applications in robotics, control systems, and industrial automation, where solving time-varying equations with high precision is critical. His innovative discretization formulas and theoretical contributions have made him a respected figure in the field of zeroing neural dynamics.
Research Focus
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