Multi-UAV Control under Indoor-Outdoor Workspace Switch
Hongbo Yang. (2024). "Multi-UAV Control under Indoor-Outdoor Workspace Switch." Preparing.
Curriculum Vitae
Full version of my Curriculum Vitae can be downloaded here.
Education
- M.S. in Control Science and Engineering , SJTU, 2025
- B.S. in IEEE Pilot Class (Artificial Intelligence track), SJTU, 2022
Publications
Resilient Control Preserving Collaborative Spatio-Temporal Specifications
Hongbo Yang, Yuanyuan Zou, and Shaoyuan Li. (2024). "Resilient Control Preserving Collaborative Spatio-Temporal Specifications." Preparing.
Distributed Predictive Control under Multiple Sub-formula STL Specifications with Temporal Relaxation
Hongbo Yang, Yuanyuan Zou, and Shaoyuan Li. (2024). " Distributed Predictive Control under Multiple Sub-formula STL Specifications with Temporal Relaxation." Annual Conference of the IEEE Industrial Electronics Society (IECON). xx(xx).
Temporal Relaxation of STL Specifications in Distributed Multi-Agent Systems
Hongbo Yang, Yuanyuan Zou, and Shaoyuan Li. (2023). "Temporal Relaxation of STL Specifications in Distributed Multi-Agent Systems." IEEE 2nd Industrial Electronics Society Annual On-Line Conference (ONCON). pp.1-6.
Output Regulation of Discrete Event Dynamic Systems
Hongbo Yang, Peng Lv, Xiang Yin, and Shaoyuan Li. (2022). " Output Regulation of Discrete Event Dynamic Systems." Journal of Xiamen University(Natural Science).61(06)
Technical Skills
- Cloud-based machine development: Ubuntu, Git, Docker
- Academic writing tools: LaTeX, TikZ
- Simulation programming languages: Python, ROS, C, C++, MATLAB, Simulink, Julia
- Data analysis tools: Numpy, Pandas, SPSS, STATA
- Other skills: HTML5, PHP, JS, Gephi, Verilog, CAD, SolidWorks, CAXA, Arduino
- Control algorithms: ** Model Predictive Control, Optimal Control, Adaptive Control, Kalman Filter, Particle Filter, Sampling Algorithms, Formal Methods, etc.
- Machine learning techniques: ** SVM, Linear Regression, Logistic Regression, KNN, Bayesian Classification, K-means, EM Algorithm, Decision Trees, etc.
- Deep learning frameworks: ** MLP, CNN, RNN, LSTM; proficient in principles of backpropagation, knowledgeable about optimizers such as SGD; familiar with PyTorch framework
- Robotics full-stack competencies: Design and manufacturing (SolidWorks, CAXA, CAD), operation platform(Arduino, ROS, Moveit!), regulation algorithms (Hybrid A, RRT, MPC, ILQR)