🤖 Duc-Cuong VU, BSc.

E-mail / ORCID / LinkedIn / Google Scholar / GitHub / CV

✍️ about me

I am currently pursuing a Master of Science in Automation and Controlat the Hanoi University of Science and Technology (HUST), Vietnam, under the supervision of Assoc. Prof. Dr. Tung Lam Nguyen. My research focuses on the application of Stewart platforms in marine environments, funded by the Vingroup Innovation Foundation (VINIF). I previously earned my Bachelor of Science in Automation and Control at HUST, where I received the Best Thesis Defense Award for my undergraduate thesis on balancing, motion planning, and tracking control for ballbot systems.

I am also a Robotics Engineer at VinRobotics, a pioneer in humanoid robotics in Vietnam. My work focuses on developing advanced control algorithms and implementing cutting-edge technologies for humanoid robots. My key responsibilities include system identification, state estimation, model predictive control (MPC), and whole-body control for humanoid platforms.

My research interests span control theory, optimization in control, robotics, and experimental systems. I am particularly interested in bridging the gap between simulation and real-world implementation, aiming to strengthen the connection between theoretical analysis and practical validation.

For more details about my work, visit the projects page, or explore my academic activities.

📷 My photo with the 6-dof parallel robot, Stewart platform, at Motion Control and Applied Robotics laboratory (MoCAR), C7-building, Hanoi University of Science and Technology (HUST).

📣 news

[Sep 17, 2025] My work for HUST project is accepted for publication in Ocean Engineering 🎉.

[Sep 08, 2025] Thrilled to begin a new chapter at VinRobotics! 🎉

[Jul 07, 2025] Our ship-mounted Stewart platform paper is accepted for publication in Ocean Engineering 🎉.

[May 28, 2025] My project with VinIF, related to my master's course, was completed with high appropriateness ✅.

[May 20, 2025] An Autonomous-Underwarter-Vehicle-related manuscript is submited to Ocean Engineering 🌊.

[Apr 16, 2025] A paper, forcusing on Ship-mounted Stewart platform, is submited to Ocean Engineering 🌊.

[Mar 27, 2025] Our paper on ballbot was accepted for publication in IEEE Access 🎉.

[Dec 30, 2024] Our paper on Stewart Platforms was accepted for publication in Results in Engineering 🎉.

[Sep 12, 2024] I am delighted to announce that I have decided to receive the VinIF scholarship for my master's course under a project 💰.

[Jul 01, 2024] I started my Master of Science in Automation and Control at HUST 🎓.

[May 11, 2024] I graduated with a Bachelor of Science in Automation and Control from HUST 🎓.

[Mar 27, 2024] Our paper on ballbot was accepted for publication in International Journal of Robust and Nonlinear Control (IJRNC) 🎉.

📚 selected publications

📝 Glocal trajectory generation and tracking control for AUVs with optimal coverage sensor networks

Duc Cuong Vu*, Son Tran*, Tung Lam Nguyen, and Duc Chinh Hoang

* equal contribution

Ocean Engineering, 2025 (SCIE, Q1)

[paper | pdf]

This paper presents a comprehensive framework for glocal trajectory generation with real-time tracking control for a group of Autonomous Underwater Vehicles (AUVs) equipped with distributed sensors. A two-stage approach is proposed to maximize the underwater area coverage of sensor systems while ensuring network connectivity between AUVs and free collision with terrains and floating obstacles. At the global level, a heuristic algorithm named Global Trajectory to Maximize Coverage (GT-MC) is introduced, which generate trajectory to optimize the final AUVs distribution. After that, the trajectory is further optimized to produce the final set of waypoints for the AUVs group. At the local level, a safety-critical trajectory generation method is developed by using a Model Predictive Control (MPC) scheme for a virtual AUV system with Control Barrier Functions (CBF) as constraints for floating obstacle avoidance. Then, the generated trajectories are tracked by the actual AUVs using a base controller, in this case a classical Sliding Mode Controller (SMC) combined with a thruster force allocation optimizer. The complete framework is validated via simulation studies using an open-source advanced physics tool called MuJoCo. The suggested methodology can facilitate the autonomy, scalability, and safety of sensor-AUVs distribution missions, making it a promising tool for intelligent marine sensing and monitoring.

📝 Lagrangian-based modeling and safety-critical controls for Stewart platforms under marine operations

Duc Cuong Vu, Danh Huy Nguyen, Minh Nhat Vu, and Tung Lam Nguyen

Ocean Engineering, 2025 (SCIE, Q1)

[paper | pdf]

The operation of waves, winds, and ocean currents that affect ships or marine vehicles poses a number of challenges for systems that require balance. To address this issue, this study introduces a 6-degree-of-freedom parallel robot Stewart platform erected on the ship deck to isolate vibrations. First, Lagrangian-based modeling is applied to the ship-mounted Stewart platform. Unlike previous systems that are based on Kane’s method or Newtonian mechanics, the Lagrangian-based approach does not require a large number of tedious mathematical transformations; instead, it can be generated by a computer. Because of the complexity of the simulation model, the control design model is simplified from the original. Following that, the Control Lyapunov Function (CLF) is employed to achieve zero convergence and the stabilization of the state errors. To ensure operational safety, the Quadratic Program (QP) problem takes into account the Control Barrier Function (CBF) and Exponential Control Barrier Function (ECBF) constraints. The controllers are equipped with High-Gain Disturbance Observation (DOB). Finally, the Lagrangian-based model is validated by comparison with the MATLAB Simscape Multibody platform. In addition, the performance of the proposed control strategies is analyzed.

📝 CBFs-based Model Predictive Control for Obstacle Avoidance with Tilt Angle Limitation for Ball-Balancing Robots

Minh Duc Pham, Duc Cuong Vu, Thi Thuy Hang Nguyen, Thi Van Anh Nguyen, Minh Nhat Vu, and Tung Lam Nguyen

IEEE Access, 2025 (SCIE, Q2)

[paper | pdf]

This study investigates an automatic navigation method for one type of underactuated system, ball-balancing robot (ballbot), in complex environments with both dynamic obstacles and complex-shaped obstacles. To ensure safe operations, which means that ballbot has to avoid obstacles and maintain tilt angles in a desired range, Nonlinear Model Predictive Control (NMPC) is formulated to predict the position and behavior of the ballbot, followed by the optimization problem assisted by Control Barrier Function (CBF) constraints to drive the ballbot in the safe trajectory. Instead of directly implementing tilt angle limitations on the main NMPC, another Quadratic Programming Optimizer based on CBF is designed outside the main controller to reduce the constraint complexity of optimization. An elliptic-bounded generation method is used to simplify the object boundary, especially concave obstacles definition in NMPC constraints, while Extended State Observer is used for observing, compensating the uncertainty terms, and estimating the velocities of the ballbot. In general, by combining this CBF-based NMPC and Quadratic Programming, this research addresses simultaneously high-quality observer, tracking control, balancing control, complex motion planning and safe-angle constraints for the 3D-ballbot system. The effectiveness of our proposed method is determined by simulations in complicated tracking scenarios with static, dynamic and complex-shaped objects.

📝 A novel approach of Consensus-based Finite-time Distributed Sliding Mode Control for Stewart platform manipulators motion tracking

Duc Cuong Vu, Danh Huy Nguyen, and Tung Lam Nguyen

Results in Engineering, 2025 (ESCI, Q1)

[paper | pdf]

The Gough-Stewart Platform, often referred to simply as the Stewart Platform, is a parallel mechanical system with six degrees of freedom, which is widely employed in simulation and precise applications. This study gives a thorough Lagrangian-based model of the Stewart Platform, emphasizing its dynamic behavior and control mechanisms. A novel distributed control technique based on Finite-time Distributed Sliding Mode Control (DSMC) is presented to establish second-order consensus in a multi-agent framework in which each leg of the platform is viewed as an autonomous agent. The control approach ensures accurate monitoring of reference trajectories. Simulations are used to validate the efficacy of the proposed control scheme by comparing it to typical decentralized PD control methods. The results simulated based on the Quasi-Physical Model show that consensus-based control outperforms the counterpart control approaches in terms of accuracy and stability.

📝 Time-optimal trajectory generation and observer-based hierarchical sliding mode control for ballbots with system constraints

Duc Cuong Vu, Minh Duc Pham, Thi Thuy Hang Nguyen, Thi Van Anh Nguyen, and Tung Lam Nguyen

International Journal of Robust and Nonlinear Control, 2024 (SCIE, Q1)

[paper | pdf]

This paper introduces a comprehensive motion planning–tracking–safety constraint scheme for a 3D ballbot system. A nonlinear control for the 3D ballbot system is designed based on three separate planes by utilizing extended state observer (ESO) to estimate coupling mechanisms. Three virtual control signals are generated from these distinct planes and can be used for formulating actual control signals. To overcome the complexity of nonlinear motion equations, flatness theory is used to construct the time-optimal trajectory through an optimization problem, facilitating smooth movement of the ballbot, and obstacle avoidance based on RRT* waypoints. Furthermore, our work manipulates the hierarchical sliding mode controller (HSMC) as the nominal controller to ensure that the ballbot tracks to the optimal trajectory, unifying with the exponential control barrier function (ECBF) to address safety constraints in the body's deflection angle. Through extensive simulations and comparative analysis, the system demonstrates its effectiveness and safe operation in various working conditions.

💼 work experience

Robotics Engineer at VinRobotics, Vingroup

Full-time (On-site) | Hanoi, Vietnam

Sep 2025 – Present

Responsible for System Identification, State Estimation, Model Predictive Control (MPC), and Whole Body Control (WBC) for VinRobotics Humanoids robot.

Research Project Assistant at HUST

Contract (Hybrid) | Hanoi, Vietnam

Jan 2025 – Present

Supervised by PhD. Chinh Hoang Duc (PI) and Assoc.Prof.PhD. Tung Lam Nguyen.

Work under project: Robot navigation system integrating sensor network and wireless communication.
Designed and developed a comprehensive MuJoCo-based simulation environment for AUVs, incorporating underwater dynamics, sensor feedback, environmental disturbances, and communication constraints to evaluate system performance.
Implemented and validated advanced control algorithms for navigation, obstacle avoidance, and trajectory tracking, while collaborating on integration, troubleshooting, and authoring a peer-reviewed scientific paper.

Research Project Assistant at HUST

Contract (Hybrid) | Hanoi, Vietnam

Jan 2025 – Oct 2025 (10 mos)

Supervised by PhD. Minh Nhat Vu (PI) and Assoc.Prof.PhD. Tung Lam Nguyen.

Work under project: Advanced Control of a Ship-Mounted Stewart Platform for Marine Applications.
Funded by KIST Korea Institute of Science and Technology.
Designed and implemented advanced control algorithms for the Stewart platform, including safety-critical and robust control strategies tailored for marine environments.
Implemented and validated advanced control algorithms for navigation, obstacle avoidance, and trajectory tracking, while collaborating on integration, troubleshooting, and authoring a peer-reviewed scientific paper.

Graduate Student Research at HUST

Part-time (Hybrid) | Hanoi, Vietnam

May 2024 – Present

Supervised by Assoc.Prof.PhD. Tung Lam Nguyen.

Work under master project: Design control structures for Parallel Platforms in Maritime applications.
Funded by VinIF.
Designed and implemented advanced control algorithms for a Stewart platform in marine environments, supported by high-fidelity simulations (Simscape, MuJoCo) and validated through a full experimental setup (mechanical assembly, hardware integration, Linux real-time kernel, EtherCAT communication).
Collaborated with cross-institutional teams on system integration, troubleshooting, and documentation, while authoring peer-reviewed publications and presenting outcomes to academic and industrial partners.

Student Intern at HUST

Internship (Hybrid) | Hanoi, Vietnam

Oct 2021 – Apr 2024 (2 yrs 7 mos)

Hanoi, Vietnam

Supervised by Assoc.Prof.PhD. Tung Lam Nguyen.

Work under bachelor project: Balancing, motion planning, and tracking control for ballbot systems.
Developed mathematical models and simulation environments for 3D ballbot systems, focusing on nonlinear dynamics, trajectory generation, and safety constraints.
Conducted research on modeling and simulation, advanced control strategies, and practical implementation for the Ball-Balancing Robot.
Authored and co-authored peer-reviewed journal papers based on the project outcomes, including publications in the International Journal of Robust and Nonlinear Control (RNC) and IEEE Access.

📣 news

📚 selected publications

💼 work experience

🎓 educations