A5085915589- Adaptive Control of Nonlinear Systems
- Tailings Management and Properties
- Distributed Control Multi-Agent Systems
- Mine drainage and remediation techniques
- Geotechnical Engineering and Soil Stabilization
- Rock Mechanics and Modeling
- Geotechnical Engineering and Underground Structures
- Advanced Computational Techniques and Applications
- Guidance and Control Systems
- Enhanced Oil Recovery Techniques
- Adaptive Dynamic Programming Control
- Advanced Control Systems Optimization
- Grouting, Rheology, and Soil Mechanics
- Structural Analysis and Optimization
- Concrete Corrosion and Durability
- Advanced Decision-Making Techniques
- Hydrocarbon exploration and reservoir analysis
- Bayesian Modeling and Causal Inference
- Petroleum Processing and Analysis
- Control and Dynamics of Mobile Robots
- Aerospace Engineering and Control Systems
China Minmetals (China)
2023
China University of Petroleum, Beijing
2021
Southwest Jiaotong University
2019-2020
Zhejiang Water Conservancy and Hydropower Survey and Design Institute
2010
In this paper, a robust adaptive sliding mode control scheme is developed for attitude and altitude tracking of quadrotor unmanned aerial vehicle (UAV) system under the simultaneous effect parametric uncertainties consistent external disturbance. The underactuated dynamic model UAV first built via Newton–Euler formalism. Considering nonlinear strongly coupled characteristics quadrotor, controller then designed using approach. Meanwhile, additional laws are proposed to further improve...
In the paper, a linear quadratic regulator is developed for control of quadrotor subject to external disturbance. The nonlinear mathematical model converted by using feedback linearization technique. inputs system are derived based on (LQR) theory. effectiveness proposed algorithm has been demonstrated via simulation and real experiment.
Target intention inference is an important aspect of situation assessment. The evidence system targets' discussed according to the independent relationship between and input evidence. probability model proposed based on static Bayesian network. In order expand application domain predigest parameter learning contents, decomposition mergence network' structure are disposed. process simplified condition relationships. Different network architecture state space their method carried on. result...