All Outputs (4)

Deep reinforcement learning-based non-causal control for wave energy conversion (2024)
Journal Article
Wang, H., Wijaya, V., Zeng, T., & Zhang, Y. (2024). Deep reinforcement learning-based non-causal control for wave energy conversion. Ocean Engineering, 311(Part 1), Article 118860. https://doi.org/10.1016/j.oceaneng.2024.118860

As one of the most promising renewable energy resources, ocean wave energy has not been widely commercialized compared to wind energy and solar energy due to its high Levelized Cost of Electricity (LCoE). It has been long recognized... Read More about Deep reinforcement learning-based non-causal control for wave energy conversion.

Non-Causal Control For Wave Energy Conversion Based on the Double Deep Q Network (2024)
Presentation / Conference Contribution
Wang, H., Wijaya, V. V., Zhang, Y., Zeng, T., & Dong, X. (2024, April). Non-Causal Control For Wave Energy Conversion Based on the Double Deep Q Network. Presented at CONTROL 2024: 14th United Kingdom Automatic Control Council (UKACC) International Conference on Control, Winchester, UK

To harness maximal wave energy, control and optimization for wave energy converters(WECs) have been investigated for decades. It has been long recognized that WEC control is essentially a non-causal control problem, in which future wave determines cu... Read More about Non-Causal Control For Wave Energy Conversion Based on the Double Deep Q Network.

Efficient and Scalable Inverse Kinematics for Continuum Robots (2023)
Journal Article
Wild, S., Zeng, T., Mohammad, A., Billingham, J., Axinte, D., & Dong, X. (2024). Efficient and Scalable Inverse Kinematics for Continuum Robots. IEEE Robotics and Automation Letters, 9(1), 375 - 381. https://doi.org/10.1109/lra.2023.3331291

With their flexible nature, continuum robots offer hyper-redundancy regarding their workspace; their backbone can take many shapes upon a single tip position and orientation. Deciphering which backbone shape to use under certain conditions is crucial... Read More about Efficient and Scalable Inverse Kinematics for Continuum Robots.

A Robust Human–Robot Collaborative Control Approach Based on Model Predictive Control (2023)
Journal Article
Zeng, T., Mohammad, A., Madrigal, A. G., Axinte, D., & Keedwell, M. (2024). A Robust Human–Robot Collaborative Control Approach Based on Model Predictive Control. IEEE Transactions on Industrial Electronics, 71(7), 7360-7369. https://doi.org/10.1109/TIE.2023.3299046

Human skill-based robotic control to perform critical manufacturing operations (e.g., repair and inspection for high-value assets) can reduce scrap rates and increase overall profitability in the industrial community. In this study, a human–robotic c... Read More about A Robust Human–Robot Collaborative Control Approach Based on Model Predictive Control.