Xingding Zhao

Beijing University of Chemical Technology

Papers

Total Citations

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About

Xingding Zhao is a researcher in control theory and automation, with a primary focus on iterative learning control (ILC) and energy-optimal system design. His most cited work, "Energy-Optimal Time Allocation in Point-to-Point ILC With Specified Output Tracking" (2019, 17 citations), addresses a critical challenge in precision motion control: minimizing control energy while ensuring accurate output tracking at specified points. Zhao’s key contribution lies in treating time allocation as an optimization variable rather than a fixed parameter, enabling more efficient use of control effort in point-to-point (P2P) ILC systems. This approach is particularly valuable in applications where only certain output dimensions or discrete points need to be tracked, such as in robotics and manufacturing. By integrating energy minimization with time allocation, Zhao’s work advances the practical utility of ILC for industrial automation. His research bridges theoretical optimization and real-world control constraints, offering a framework that reduces energy consumption without sacrificing tracking performance. With a growing citation record, Zhao is establishing himself as a contributor to energy-aware control strategies, making his work relevant for students and researchers interested in efficient, precision-driven automation systems.