Mr. Weimin Xu | Engineering | Best Researcher Award
Associate professor, at Shanghai Maritime University, China.
Dr. Weimin Xu, Ph.D., is an accomplished associate professor specializing in Control Science and Engineering. 🎓 With a career spanning over three decades, Dr. Xu earned his bachelor’s degree in Automation from Northeastern University, China, in 1985, followed by a master’s in 1992 and a Ph.D. in 1997 from the same institution. He has been actively contributing to academia and research at Shanghai Maritime University since 2009. In 2013, he further enriched his academic exposure through a one-year visiting research program at the University of Southern California 🇺🇸. Dr. Xu’s expertise lies in nonlinear systems, adaptive and intelligent control, and robotics. 🤖 He has authored over 30 academic papers and holds more than 20 invention patents. His work significantly impacts robotics and intelligent systems, blending theoretical foundations with practical applications in automation and control.
Professional Profile
🎓 Education
Dr. Weimin Xu pursued all his academic qualifications from Northeastern University, China. He began with a Bachelor’s degree in Automation in 1985, where he gained foundational knowledge in electrical and mechanical systems. With a growing interest in system dynamics and process automation, he continued his studies at the same university, earning a Master’s degree in Control Science and Engineering in 1992. Driven by a deep curiosity about system behavior and advanced control theories, he completed his Ph.D. in Control Science and Engineering in 1997. 🧠 His doctoral research laid the groundwork for his current expertise in nonlinear and intelligent control systems. Later, in 2013, Dr. Xu broadened his international academic horizon through a one-year visiting research program at the University of Southern California, where he collaborated with global experts and explored modern advancements in robotics and adaptive control. 🌐
👨🏫 Experience
Dr. Xu began his professional journey in academia shortly after completing his Ph.D. in 1997. His early career involved contributing to control engineering projects and mentoring students at various institutions. Since 2009, he has been serving as a faculty member at Shanghai Maritime University, actively involved in teaching, supervising graduate students, and leading advanced research in control systems. 🏫 His academic responsibilities are complemented by hands-on research in intelligent systems and automation. In 2013, he was a visiting scholar at the University of Southern California, a pivotal experience that allowed him to engage with cutting-edge research and collaborate internationally. Over the years, Dr. Xu has become a recognized expert in the control and automation field, integrating theoretical knowledge with real-world applications in robotics, crane systems, and intelligent automation. ⚙️ His contributions have significantly enhanced the university’s research capabilities in engineering and intelligent control.
🔍 Research Interests
Dr. Xu’s research explores the dynamic landscape of control theory and intelligent systems. His key focus areas include nonlinear system theory, adaptive control, and sliding mode control—each critical for understanding and controlling complex engineering systems. ⚙️ He is particularly passionate about robot manipulator control, where precision and adaptability are essential. In addition, Dr. Xu’s work delves into bridge crane state detection and intelligent control, reflecting his commitment to real-world industrial applications. 🚢 His research often integrates classical control methodologies with modern AI techniques, creating intelligent, robust, and adaptive control strategies. Dr. Xu continually investigates how automation can enhance operational efficiency and safety in engineering systems. 🤖 His innovative approaches aim to bridge the gap between control theory and practice, ultimately improving the reliability and intelligence of machinery across various sectors.
🏅 Awards
Throughout his academic career, Dr. Xu has received multiple awards and recognitions that highlight his contributions to control engineering and intelligent systems. 🏆 His work on bridge crane detection and robotic control has earned accolades for both innovation and practical relevance. With more than 20 authorized invention patents, many of which focus on automation and intelligent detection, Dr. Xu’s inventive spirit has been consistently celebrated at national and institutional levels. 🇨🇳 He has also been recognized for excellence in research and teaching at Shanghai Maritime University, where he has played a pivotal role in advancing engineering education. His dedication to integrating cutting-edge research into student learning and real-world applications has made him a valuable mentor and leader. Dr. Xu’s achievements are a testament to his commitment to continuous innovation and the impactful dissemination of knowledge in the engineering community. 📘
📚 Top Noted Publications
Dr. Xu has published over 30 peer-reviewed academic papers, contributing significantly to nonlinear systems and intelligent control. His research is widely cited, reflecting his influence in the academic community. 📖 Some of his representative publications include:
1. Xu, W., et al. (2021)
Title: Adaptive Sliding Mode Control for Robot Manipulators with Input Nonlinearity
Journal: Robotics and Autonomous Systems
Citations: 45
Summary:
This paper presents an adaptive sliding mode control (ASMC) approach designed specifically for robot manipulators with significant input nonlinearities such as dead zones and input saturation. The authors develop a robust controller that adapts in real time to system uncertainties and unmodeled dynamics while preserving stability and convergence.
Key Contributions:
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A novel ASMC framework incorporating adaptive laws to handle unknown input nonlinearities.
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Lyapunov-based stability analysis ensures system convergence.
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Simulation and experimental results on a 2-DOF manipulator show improved trajectory tracking and robustness compared to traditional SMC.
Impact:
Widely cited for its robustness in dealing with non-ideal actuator behavior in robotics applications.
2. Xu, W., et al. (2020)
Title: Intelligent Control of Bridge Crane Based on Sensor Fusion and Neural Networks
Conference: IEEE Conference on Control and Automation
Citations: 30
Summary:
This work proposes an intelligent control strategy for bridge cranes using a combination of sensor fusion (gyroscopes, vision, encoders) and neural network-based control algorithms. The aim is to reduce swing and improve payload accuracy during transport.
Key Contributions:
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Development of a sensor fusion algorithm to accurately estimate the payload position and velocity.
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Neural networks are trained to mimic optimal control behavior under different load conditions.
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Simulation and real-time experiments confirm the effectiveness in swing suppression and trajectory accuracy.
Impact:
Recognized for advancing automation in industrial lifting systems using AI-based techniques.
3. Xu, W., et al. (2019)
Title: Nonlinear Adaptive Control with Observer for Uncertain Systems
Journal: Wireless Networks
Citations: 28
Summary:
This paper addresses the control of nonlinear uncertain systems using a nonlinear adaptive control scheme combined with an observer design to estimate unmeasurable states. The focus is on wireless-enabled systems with uncertain parameters and delays.
Key Contributions:
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Design of a state observer for nonlinear systems with partially known dynamics.
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Use of adaptive control to handle parametric uncertainties and time-varying disturbances.
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Stability proofs using Barbalat’s Lemma and Lyapunov theory.
Impact:
Cited in research on wireless sensor-actuator networks and embedded control in uncertain environments.
4. Xu, W., et al. (2018)
Title: Intelligent Fault Detection in Industrial Systems using Hybrid Neural Models
Journal: Expert Systems with Applications
Citations: 52
Summary:
This paper proposes a hybrid neural network model for fault detection in industrial systems, combining convolutional neural networks (CNNs) and recurrent neural networks (RNNs). It targets early-stage anomaly detection in time-series data from manufacturing sensors.
Key Contributions:
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A novel hybrid model that captures both spatial features (via CNN) and temporal dynamics (via RNN).
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A feature fusion strategy for improved diagnostic performance.
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Evaluation on real-world datasets from manufacturing processes shows high accuracy and low false alarm rates.
Impact:
One of the most cited papers in intelligent maintenance and predictive diagnostics, influencing work on Industry 4.0 and smart manufacturing.
Conclusion
Dr. Weimin Xu is a strong candidate for the Best Researcher Award due to his broad and practical research contributions, notable patent record, and long-standing academic service. His work bridges theoretical advancement and practical application in intelligent control systems, aligning with the priorities of innovation-driven recognition.