Professor Xiaowei Zhao

Professor of Control Engineering

Xiaowei dot Zhao at warwick dot ac dot uk
+44 (0) 24 7652 3145

Biography

Professor Xiaowei Zhao is the Director of the EPSRC Supergen Network Plus in Artificial Intelligence for Renewable Energy (SuperAIRE) and a Co-Director of the EPSRC Supergen Offshore Renewable Energy Hub. From 2021 to 2025, he served on the Science Expert Group advising the UK Government on science and engineering aspects of national energy and net zero policy. His research integrates artificial intelligence, control engineering, and clean energy systems to accelerate the transition to net zero, with applications in offshore renewable energy systems, hydrogen systems, smart grids, and autonomous energy systems.

He has established a leading research programme in AI for wind energy, including reinforcement learning-driven wind farm control systems and physics-informed digital twins for wind farm flows, validated through wind tunnel experiments and currently undergoing validation at a large offshore wind farm in Belgium. He is ranked the world’s No. 1 Highly Ranked Scholar in Wind Farm research based on five-year academic impact by ScholarGPS, and was also named an inaugural Manchester Prize finalist in AI, with the finalists announced by the UK Prime Minister at the 2024 AI Seoul Summit, receiving £100k in prize funding and £90k in AI computing resources.

Since 2017, he has secured over 20 research grants from UKRI, European programmes, and NESO (the UK National Energy System Operator, formerly National Grid ESO), with a total project value over £50 million (over £9.5 million share). He has established long-term collaborations with more than 30 energy companies, including NESO, Vestas, GE Vernova, and PA Consulting. His research models have been integrated into the Great Britain power grid modelling framework to support renewable energy integration and grid stability.

At Warwick, he founded the Intelligent Control & Smart Energy (ICSE) research group, comprising around 20 PhD students and postdoctoral researchers, and established four major research laboratories in offshore renewable energy, smart grids, hydrogen technologies, and autonomous systems.

He received his PhD in Control Theory from Imperial College London in 2010 and subsequently worked as a postdoctoral researcher in the Control Engineering Group at the University of Oxford. He joined the University of Warwick in 2013 and was promoted to Professor of Control Engineering in 2018.

Research Interests

Advanced control, reinforcement learning and artificial intelligence
Power system dynamics, stability, optimisation and renewable energy integration
Offshore renewable energy systems: modelling, digital twins and intelligent control
Satellite- and UAV-based sensing and monitoring for energy infrastructure

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Projects and Grants

Current Grants

(His share: £4.65 million; total project value: £25.67 million)

2027 - 2029, AI-Driven Power System Analysis, PI
2027 - 2029, Horizon Europe, Twinning for Excellence in Smart Grid Cyber Security (TWIN-CYGRID), CoI
2026 - 2030, Horizon Europe, WindConnect - Wind farm control and integration in sector-coupled power systems, Coordinator
2024 - 2026, EPSRC: EPSRC Supergen Network Plus in Artificial Intelligence for Renewable Energy, PI
2024 - 2026, National Energy System Operator (NESO), Hydrogen Plant Dynamic Models, PI
2023 - 2027, EPSRC, EP/Y016297/1: EPSRC Supergen ORE (Offshore Renewable Energy) Impact Hub, co-director
2023 - 2027, UKRI/Innovate UK: Smart, Aware, Integrated Wind Farm Control Interacting with Digital Twins (ICONIC), PI
2023 - 2027, UKRI: Modelling and Control of Flexible Structures Interacting with Fluids (ModConFlex), PI

Past Grants

(His share: £5.04 million; total project value: £24.61 million)

2024 - 2025, UK Government Department for Science, Innovation and Technology, Manchester Prize (for Artificial Intelligence) finalist, PI
2024 - 2026, Horizon Europe (UKRI Horizon Europe Guarantee Scheme), Economic & Reliable DC Microgrids, Coordinator (PI)
2022 - 2025, EPSRC, EP/W003694/1: High efficiency reversible solid oxide cells for the integration of offshore renewable energy using hydrogen, PI
2020 - 2024, EPSRC, EP/T021713/1: Resilient Operation of Sustainable Energy Systems (ROSES), CoI (PI to Warwick).
2023 - 2024, National Grid ESO (now NESO – National Energy System Operator), Transient Stability Assessment of GB Power System based on Real-Time Phasor-EMT Simulations, PI
2019 - 2024, H2020, WinGrid: Wind farm - Grid interactions: exploration and development, Coordinator (PI)
2018 - 2023, EPSRC, EP/S000747/1: EPSRC Supergen ORE (Offshore Renewable Energy) Hub, co-director
2020 - 2023, EPSRC Supergen ORE Hub Strategic Fund, PI
2021 - 2023, EPSRC Supergen Cross Hub Seedcorn Fund, PI
2018 - 2022, EPSRC Fellowship: Data-driven Intelligent Energy Management System for a Micro Grid, PI.
2017-2022, H2020: Control of flexible structures and fluid structure interactions, Co-coordinator.
2017 - 2021, EPSRC: Farming the ENvironment into the Grid: Big data in Offshore Wind, CoI (PI to Warwick).
2018 - 2020, EPSRC First Grant (now called EPSRC New Investigator Award): Passive vibration control of a floating hydrostatic transmission wind turbine and theoretical extensions, PI
2017 - 2019, National Grid ESO (now NESO – National Energy System Operator): Assessment of power oscillation damping control on offshore wind turbine control performance, PI
2016 - 2017, Royal Society Research Grant: Design, control and implementation of a virtual infinite capacitor, PI

Editorial Role

Associate Editor, IEEE Transactions on Sustainable Energy

Journal Publications

136. Y. Su, H. Dong and X. Zhao*, Wind Farm Power Tracking via Reinforcement Learning with Autoencoded Wind Fields and Gated Causal Convolutions, IEEE Transactions on Sustainable Energy, 2026, to appear.

135. R. Li, J. Zhang and X. Zhao*, Long-range near-surface wake signatures of offshore wind farm clusters revealed by satellite observations, Communications Engineering (Nature Portfolio) DOI: 10.1038/s44172-026-00684-7, 2026.

134. J. Dai, J. Zhang and X. Zhao*, Spatiotemporal nonlinear ocean wave prediction with uncertainty quantification and universal predictable zone determination, Applied Energy 402, 2026.

133. M. Wang, H. Dong and X. Zhao, A Hybrid Interpretable Reinforcement Learning Framework for Robust Pitch Control of Large-Scale Wind Turbines, IEEE Transactions on Sustainable Energy DOI: 10.1109/TSTE.2026.3712960, 2026.

132. T. Fei, Y. Yang and X. Zhao, Command Filtered Adaptive Bipartite Synchronization for Heterogeneous Switched Multi-Agent Systems with State Delays and Input Nonlinearity, Journal of the Franklin Institute 363, 2026.

131. T. Fei, Y. Yang and X. Zhao, Robust Adaptive H∞ Tracking Control for Nonlinear Strict-Feedback System via Actor-Critic-Disturbance Learning: A Zero-Sum Game-Based Approach, International Journal of Robust and Nonlinear Control 36, 2026.

130. J. Fu, S. Lin, H. Dong and X. Zhao, Load mitigation in floating wind turbines via active tuned mass damper using a physics-informed neural network based controller, Ocean Engineering 351, 2026.

129. M. Kheshti, H. Yang, Y. Liang, W. Yue and X. Zhao*, Heterogeneous multi-agent proximal policy optimization based control of solid oxide electrolysis and wind turbine generator for fast frequency response, Applied Energy 409, 2026.

128. Y. Xu, J. Xie, H. Dong and X. Zhao, Hybrid Resilient and Fault-Tolerant Control of Wind Turbines via Actor–Critic Reinforcement Learning with Prescribed Performance, IEEE Transactions on Automation Science and Engineering 23, 2026.

127. Y. Yang, Q. He and X. Zhao*, Adaptive Resilient Output Feedback Control of Power Buffers in DC Microgrids, IEEE Transactions on Industrial Informatics 22, 2026.

126. R. Li, J. Zhang, Y. Huang and X. Zhao*, Flowformer: Toward a foundation model for full-flow-field wind farm wake modeling, Renewable Energy 256, 2026.

125. Q. Liu, M. Wang, M. Nick, C. Chen and X. Zhao*, Current-Limiting Control Design for Grid-Forming Capability Enhancement of IBRs Under Asymmetric Grid Disturbances, IEEE Transactions on Power Electronics 41, 2026.

124. Y. Huang and X. Zhao*, Multiagent Inductive Policy Optimization, IEEE Transactions on Neural Networks and Learning Systems 37, 2026.

123. Z. Wu and X. Zhao*, A Prediction-Correction Proximal Method for Convex Optimization with Linear Equality and Inequality Constraints, IEEE Transactions on Control of Network Systems 12, 2025.

122. Q. He, C. Liu and X. Zhao*, Adaptive online energy management considering lifespan decay synergy for fuel cell-battery system, International Journal of Hydrogen Energy 165, 2025.

121. J. Ye, X. Zhao, Y. Bian, M. Hu and H. Dong, Optimal control under safety constraints and disturbances: a multi-step, off-policy adaptive dynamic programming approach, Nonlinear Dynamics 113, 2025.

120. Y. Huang and X. Zhao*, Wind Farm Control via Offline Reinforcement Learning with Adversarial Training, IEEE Transactions on Automation Science and Engineering 22, 2025.

119. Q. Liu, Y. Liang, Z. Zhang, M. Wang and X. Zhao*, Small-Signal Stability of Sequence-Decomposed Grid-Forming IBRs with DC-Link Voltage Dynamics, IEEE Transactions on Power Electronics 40, 2025.

118. Z. Zhang and X. Zhao*, Startup control of grid-forming offshore wind turbines connected to the diode-rectifier-based HVDC Link, IEEE Transactions on Sustainable Energy 16, 2025.

117. Q. Liu, Y. Liang, Z. Zhang, M. Wang and X. Zhao*, Small-Signal Synchronization Stability of Sequence-Decomposed Grid-Forming IBRs, IEEE Transactions on Industrial Electronics 72, 2025.

116. H. Yang, H. Dong and X. Zhao*, Integration of prescribed performance with control barrier functions for attitude control and allocation with reaction wheels, IEEE Transactions on Aerospace and Electronic Systems 61, 2025.

115. Z. Wu and X. Zhao*, An algorithm design framework for linearly constrained convex optimization: proximal and contractive perspectives, IEEE Transactions on Automatic Control 70, 2025.

114. M. Heidari, L. Ding, M. Kheshti, X. Zhao and V. Terzija, Adaptive inertial control for wind turbine generators in fast frequency response based on the power reduction period assessment, IEEE Transactions on Sustainable Energy 16, 2025.

113. J. Xie, H. Dong, S. Lin and X. Zhao*, Wind turbine fault-tolerant control via incremental model-based reinforcement learning, IEEE Transactions on Automation Science and Engineering 22, 2025.

112. J. Ye, H. Dong, Y. Bian, H. Qin and X. Zhao*, ADP-based optimal control for discrete-time systems with safe constraints and disturbances, IEEE Transactions on Automation Science and Engineering 22, 2025.

111. Y. Lv, W. Zhang, J. Zhao and X. Zhao, Finite-horizon optimal control for nonlinear multi-input systems with online adaptive integral reinforcement learning, IEEE Transactions on Automation Science and Engineering 22, 2025.

110. R. Li and X. Zhao*, LSwinSR: UAV Imagery Super-Resolution based on Linear Swin Transformer, IEEE Transactions on Geoscience and Remote Sensing 62, 2024.

109. Y. Feng, Y. Zhou, H.W. Ho, H. Dong and X. Zhao, Online adaptive critic designs with tensor product B-splines and incremental model techniques, Journal of the Franklin Institute 361, 2024.

108. H. Yang, H. Dong and X. Zhao*, Safety-critical control allocation for obstacle avoidance of quadrotor aerial photography, IEEE Control Systems Letters 8, 2024.

107. Y. Fan, H. Dong, X. Zhao* and P. Denissenko, Path-following control of unmanned underwater vehicle based on an improved TD3 deep reinforcement learning, IEEE Transactions on Control Systems Technology 32, 2024.

106. Y. Huang and X. Zhao*, Reinforcement learning-based multi-objective control of grid-connected wind farms, IEEE Transactions on Industrial Informatics 20, 2024.

105. Q. He, J. Shen, Z. Dong, C. Liu, X. Guo and X. Zhao*, Online systemic energy management strategy of fuel cell system with efficiency enhancement, IEEE Transactions on Transportation Electrification 10, 2024.

104. G. Liu, Y. Yang, X. Zhao and C.K. Ahn, Adaptive fuzzy practical bipartite synchronization for multi-agent systems with intermittent feedback under multiple unknown control directions, IEEE Transactions on Fuzzy Systems 32, 2024.

103. Y. Lv, X. Zhao* and P. Shah, Robust optimal framework for doubly fed induction generator with uncertain dynamics, Protection and Control of Modern Power Systems 9, 2024.

102. M. Heidari, L. Ding, M. Kheshti, W. Bao, X. Zhao, M. Popov and V. Terzija, A Review on Application of Machine Learning-Based Methods for Power System Inertia Monitoring, International Journal of Electrical Power & Energy Systems 162, 2024.

101. C. Liu, J. Shen, Z. Dong, Q. He and X. Zhao*, Accuracy improvement of fuel cell prognostics based on voltage prediction, International Journal of Hydrogen Energy 58, 2024.

100. G. Liu, Y. Yang, X. Zhao and C.K. Ahn, Novel Nussbaum design for nonlinear systems with unknown switching control directions, IEEE Transactions on Circuits and Systems II: Express Briefs 71, 2024.

99. Z. Zhang, Y. Liang and X. Zhao*, Adaptive Inter-area power oscillation damping from offshore wind farm and MMC-HVDC using deep reinforcement learning, Renewable Energy 224, 2024.

98. C. Liu, P. Shah, Z. Dong and X. Zhao*, Distribution system identification using FISTA algorithm, International Journal of Electrical Power & Energy Systems 155, 2024.

97. Z. Wu and X. Zhao*, Parameter-separable prox-Lagrangian method for convex-concave saddle point problem, IEEE Control Systems Letters 8, 2024.

96. J. Xie, H. Dong and X. Zhao*, Power regulation and load mitigation of floating wind turbines via reinforcement learning, IEEE Transactions on Automation Science and Engineering 21, 2024.

95. J. Zhang and X. Zhao*, Digital twin of wind farms via physics-informed deep learning, Energy Conversion and Management 293, 2023.

94. R. Li, J. Zhang, X. Zhao*, D. Wang, M. Hann and D. Greaves, Phase-resolved real-time forecasting of three-dimensional ocean waves via machine learning and wave tank experiments, Applied Energy 348, 2023.

93. J. Zhang, X. Zhao*, D. Greaves and S. Jin, Modeling of a hinged-raft wave energy converter via deep operator learning and wave tank experiment, Applied Energy 341, 2023.

92. H. Dong and X. Zhao*, Reinforcement learning-based wind farm control: towards large farm applications via automatic grouping and transfer learning, IEEE Transactions on Industrial Informatics 19, 2023.

91. Y. Liang, X. Zhao* and L. Sun, A multiagent reinforcement learning approach for wind farm frequency control, IEEE Transactions on Industrial Informatics 19, 2023.

90. Z. Zhang and X. Zhao*, Coordinated power oscillation damping from a VSC-HVDC grid integrated offshore wind farms: using capacitors energy, IEEE Transactions on Sustainable Energy 14, 2023.

89. Y. Huang, S. Lin and X. Zhao*, Multi-agent reinforcement learning control of a hydrostatic wind turbine-based farm, IEEE Transactions on Sustainable Energy 14, 2023.

88. P. Shah and X. Zhao*, Leakage current mitigation technique in solar PV array system using passive filter, IEEE Transactions on Energy Conversion 38, 2023.

87. H. Dong and X. Zhao*, Data-driven wind farm control via multiplayer deep reinforcement learning, IEEE Transactions on Control Systems Technology 31, 2023.

86. Y. Lv, J. Na, X. Zhao*, Y. Huang and X. Ren, Multi-H∞ controls for unknown inputs-interference nonlinear system with reinforcement learning, IEEE Transactions on Neural Networks and Learning Systems 34, 2023.

85. H. Yang, Q. Hu, H. Dong, X. Zhao and D. Li, Optimized data-driven prescribed performance attitude control for actuator saturated spacecraft, IEEE/ASME Transactions on Mechatronics 28, 2023.

84. X. Guo, Z. Dong, J. Shen, Y. Xu, Q. He, X. Zhao and Z. Ding, Towards intelligent and integrated architecture for hydrogen fuel cell system: challenges and approaches, National Science Open 2, 2023.

83. J. Xie, H. Dong and X. Zhao*, Data-driven torque and pitch control of wind turbines via reinforcement learning, Renewable Energy 215, 2023.

82. Q. He, P. Shah and X. Zhao*, Resilient operation of dc microgrid against FDI attack: a GRU based framework, International Journal of Electrical Power & Energy Systems 145, 2023.

81. Y. Lv, Z. Wu and X. Zhao*, Data-based optimal microgrid management for energy trading with integral Q-learning scheme, IEEE Internet of Things Journal 10, 2023.

80. Y. Lv, X. Ren, J. Tian and X. Zhao*, Inverse-model-based iterative learning control for unknown MIMO nonlinear system with neural network, Neurocomputing 519, 2023.

79. P. Shah and X. Zhao*, Network identification using micro-PMU and smart meter measurements: an ADMM based approach, IEEE Transactions on Industrial Informatics 18, 2022.

78. M. Kheshti, S. Lin, X. Zhao*, L. Ding, M. Yin and V. Terzija, Gaussian distribution-based inertial control of wind turbine generators for fast frequency response in low inertia systems, IEEE Transactions on Sustainable Energy 13, 2022.

77. Y. Zhao, T. Zhang, L. Sun, X. Zhao, L. Tong, L. Wang, J. Ding and Y. Ding, Energy storage for black start services: a review, International Journal of Minerals, Metallurgy and Materials 29, 2022.

76. H. Dong, J. Xie and X. Zhao*, Wind farm control technologies: from classical control to reinforcement learning, Progress in Energy 4, 2022.

75. L. Sun and X. Zhao*, Stability analysis and enhancement of power sharing control in islanded microgrids, IEEE Transactions on Smart Grid 13, 2022.

74. J. Zhang, X. Zhao*, S. Jin and D. Greaves, Phase-resolved real-time ocean wave prediction with quantified uncertainty based on variational Bayesian machine learning, Applied Energy 324, 2022.

73. R. Li, J. Zhang and X. Zhao*, Dynamic wind farm wake modeling based on a bilateral convolutional neural network and high-fidelity LES data, Energy 258, 2022.

72. Z. Zhang, X. Zhao*, L. Fu and M. Edrah, Stability and dynamic analysis of the PMSG-based WECS with torsional oscillation and power oscillation damping capabilities, IEEE Transactions on Sustainable Energy 13, 2022.

71. X. Zhang, D. Lu, H. Dong, X. Zhao*, F. Brennan and Y. Liang, Vibration suppression of multi-component floating structures via passive TMDs and Bayesian ascent, Ocean Engineering 259, 2022.

70. R. Li, J. Zhang and X. Zhao*, Multi-fidelity modeling of wind farm wakes based on a novel super-fidelity network, Energy Conversion and Management 270, 2022.

69. M. Kheshti, X. Zhao*, T. Liang, B. Nie, Y. Ding and D. Greaves, Liquid air energy storage for ancillary services in an integrated hybrid renewable system, Renewable Energy 199, 2022.

68. Y. Wang, X. Zhao, J.M.R. Graham and J. Li, Vortex force map for multi-body flows with application to wing-flap configurations, Journal of Fluid Mechanics 953, 2022.

67. L. Sun and X. Zhao*, Impacts of phase-locked loop and reactive power control on inertia provision by DFIG wind turbine, IEEE Transactions on Energy Conversion 37, 2022.

66. J. Li, Y. Wang, S. Lin and X. Zhao*, Nonlinear modelling and adaptive control of smart rotor wind turbines, Renewable Energy 186, 2022.

65. H. Dong, X. Zhao*, Q. Hu, H. Yang and P. Qi, Learning-based attitude tracking control with high-performance parameter estimation, IEEE Transactions on Aerospace and Electronic Systems 58, 2022.

64. H. Dong and X. Zhao*, Wind-farm power tracking via preview-based robust reinforcement learning, IEEE Transactions on Industrial Informatics 18, 2022.

63. J. Xie, H. Dong, X. Zhao* and A. Karcanias, Wind farm power generation control via double-network-based deep reinforcement learning, IEEE Transactions on Industrial Informatics 18, 2022.

62. H. Dong and X. Zhao*, Composite experience replay-based deep reinforcement learning with application in wind farm control, IEEE Transactions on Control Systems Technology 30, 2022.

61. J. Zhang and X. Zhao*, Wind farm wake modeling based on deep convolutional conditional generative adversarial network, Energy 238, 2022.

60. Y. Wang, X. Zhao, R. Palacios and K. Otsuka, Aeroelastic simulation of high-aspect ratio wings with intermittent leading-edge separation, AIAA Journal 60, 2022.

59. M. Edrah, X. Zhao*, W. Hung, P. Qi, B. Marshall, S. Baloch and A. Karcanias, Electromechanical interactions of full scale converter wind turbine with power oscillation damping and inertia control, International Journal of Electrical Power & Energy Systems 135, 2022.

58. L. Sun and X. Zhao*, Modelling and analysis of frequency-responsive wind turbine involved in power system ultra-low frequency oscillation, IEEE Transactions on Sustainable Energy 13, 2022.

57. J. Zhang, X. Zhao* and X. Wei, Reinforcement learning-based structural control of floating wind turbines, IEEE Transactions on Systems, Man, and Cybernetics: Systems 52, 2022.

56. H. Yang, Q. Hu, H. Dong and X. Zhao, ADP-based spacecraft attitude control under actuator misalignment and pointing constraints, IEEE Transactions on Industrial Electronics 69, 2022.

55. H. Dong, X. Zhao* and B. Luo, Optimal tracking control for uncertain nonlinear systems with prescribed performance via critic-only ADP, IEEE Transactions on Systems, Man, and Cybernetics: Systems 52, 2022.

54. J. Zhang and X. Zhao*, Three-dimensional spatiotemporal wind field reconstruction based on physics-informed deep learning, Applied Energy 300, 2021.

53. H. Dong, J. Zhang and X. Zhao*, Intelligent wind farm control via deep reinforcement learning and high-fidelity simulations, Applied Energy 292, 2021.

52. X. Yin and X. Zhao*, Optimal power extraction of a two-stage tidal turbine system based on backstepping disturbance rejection Control, International Journal of Electrical Power & Energy Systems 132, 2021.

51. J. Xie, X. Zhao and H. Dong, Learning-based nonlinear model predictive control with accurate uncertainty compensation, Nonlinear Dynamics 104, 2021.

50. J. Li, Y. Wang, X. Zhao* and P. Qi, Model free adaptive control of large and flexible wind turbine rotors with controllable flaps, Renewable Energy 180, 2021.

49. Q. Hu, H. Yang, H. Dong and X. Zhao, Learning-based 6-DOF control for autonomous proximity operations under motion constraints, IEEE Transactions on Aerospace and Electronic Systems 57, 2021.

48. X. Yin and X. Zhao*, Data driven learning model predictive control of offshore wind farms, International Journal of Electrical Power & Energy Systems 127, 2021.

47. X. Tong and X. Zhao*, Vibration and power regulation control of a floating wind turbine with hydrostatic transmission, Renewable Energy 167, 2021.

46. J. Zhang and X. Zhao*, Spatiotemporal wind field prediction based on physics-informed deep learning and LIDAR measurements, Applied Energy 288, 2021.

45. J. Zhang and X. Zhao*, Machine-learning-based surrogate modeling of aerodynamic flow around distributed structures, AIAA Journal 59, 2021.

44. K. Chen, Y. Qiu, J. Lin, F. Liu, X. Zhao and Y. Song, Wake-effect aware optimal online control of wind farms: an explicit solution, IET Renewable Power Generation 15, 2021.

43. H. Dong, X. Zhao* and H. Yang, Reinforcement learning-based approximate optimal control for attitude reorientation under state constraints, IEEE Transactions on Control Systems Technology 29, 2021.

42. J. Li, Y. Wang, J.M.R. Graham and X. Zhao*, Evaluating unsteady fluid dynamic forces in viscous flows from the vorticity field, AIAA Journal 59, 2021.

41. X. Yin and X. Zhao*, Deep neural learning based distributed predictive control for offshore wind farm using high fidelity LES data, IEEE Transactions on Industrial Electronics 68, 2021.

40. J. Zhang and X. Zhao*, A novel dynamic wind farm wake model based on deep learning, Applied Energy 277, 2020.

39. X. Yin, X. Zhao*, J. Lin and A. Karcanias, Reliability aware multi-objective predictive control for wind farm based on machine learning and heuristic optimizations, Energy 202, 2020.

38. X. Wei and X. Zhao*, Vibration suppression of a floating hydrostatic wind turbine model using bidirectional tuned liquid column mass damper, Wind Energy 23, 2020.

37. Y. Zhang, X. Zhao* and X. Wei, Robust structural control of an underactuated floating wind turbine, Wind Energy 23, 2020.

36. M. Edrah, X. Zhao*, W. Hung, P. Qi, B. Marshall, A. Karcanias and S. Baloch, Effects of POD control on a DFIG wind turbine structural system, IEEE Transactions on Energy Conversion 35, 2020.

35. S. Lin, X. Zhao* and X. Tong, Feasibility studies of a converter-free grid-connected offshore hydrostatic wind turbine, IEEE Transactions on Sustainable Energy 11, 2020.

34. S. Lin, P. Qi and X. Zhao*, Power generation control of a hydrostatic wind turbine implemented by model-free adaptive control scheme, Wind Energy 23, 2020.

33. P. Qi and X. Zhao*, Flight control for very flexible aircraft using model-free adaptive control, Journal of Guidance, Control, and Dynamics 43, 2020.

32. A. Khosravi, M. Malekan, J.J.G. Pabon, X. Zhao and M.E.H. Assad, Design parameter modeling of solar power tower system using adaptive neuro-fuzzy inference system optimized with a combination of genetic algorithm and teaching learning-based optimization algorithm, Journal of Cleaner Production 244, 2020.

31. J. Zhang and X. Zhao*, Quantification of parameter uncertainty in wind farm wake modeling, Energy 196, 2020.

30. J. Li, Y. Wang, J.M.R. Graham and X. Zhao*, Vortex moment map for unsteady incompressible viscous flows, Journal of Fluid Mechanics 891, 2020.

29. J. Li, X. Zhao* and J.M.R. Graham, Vortex force maps for three-dimensional viscous unsteady flows with application to a delta wing, Journal of Fluid Mechanics 900, 2020.

28. X. Yin and X. Zhao*, Sensor-less maximum power extraction control of a hydrostatic tidal turbine based on adaptive extreme learning machine, IEEE Transactions on Sustainable Energy 11, 2020.

27. X. Yin, X. Tong, X. Zhao* and A. Karcanias, Maximum power generation control of a hybrid wind turbine transmission system based on H∞ loop shaping approach, IEEE Transactions on Sustainable Energy 11, 2020.

26. X. Yin and X. Zhao*, Composite hierarchical pitch angle control for a tidal turbine based on the uncertainty and disturbance estimator, IEEE Transactions on Industrial Electronics 67, 2020.

25. X. Yin and X. Zhao*, ADV Preview Based Nonlinear Predictive Control for Maximizing Power Generation of a Tidal Turbine with Hydrostatic Transmission, IEEE Transactions on Energy Conversion 34, 2019.

24. X. Yin and X. Zhao, Big data driven multi-objective predictions for offshore wind farm based on machine learning algorithms, Energy 186, 2019.

23. P. Qi, X. Zhao* and R. Palacios, Autonomous Landing Control of Highly Flexible Aircraft Based on Lidar Preview in the Presence of Wind Turbulence, IEEE Transactions on Aerospace and Electronic Systems 55, 2019.

22. X. Wei, B.F. Ng and X. Zhao*, Aeroelastic Load Control of Large and Flexible Wind Turbines through Mechanically Driven Flaps, Journal of the Franklin Institute 356, 2019.

21. X. Yin, W. Zhang and X. Zhao, Current status and future prospects of continuously variable speed wind turbines: a systematic review, Mechanical Systems and Signal Processing 120, 2019.

20. M. Malekan, A. Khosravi and X. Zhao, The influence of magnetic field on heat transfer of magnetic nanofluid in a double pipe heat exchanger proposed in a small-scale CAES system, Applied Thermal Engineering 146, 2019.

19. A. Khosravi, S. Syri, X. Zhao and M.E.H. Assad, An AI approach for thermodynamic modeling of geothermal based-organic rankine cycle equipped with solar system, Geothermics 80, 2019.

18. P. Qi, X. Zhao*, Y. Wang, R. Palacios and A. Wynn, Aeroelastic and Trajectory Control of High Altitude Long Endurance Aircraft, IEEE Transactions on Aerospace and Electronic Systems 54, 2018.

17. X. Tong and X. Zhao*, Passive Vibration Control of the SCOLE Beam System, Structural Control and Health Monitoring 25, 2018.

16. X. Tong, X. Zhao* and A. Karcanias, Passive vibration control of an offshore floating hydrostatic wind turbine, Wind Energy 21, 2018.

15. S. Lin, X. Tong, X. Zhao* and G. Weiss, The parallel virtual infinite capacitor applied to DC-link voltage filtering for wind turbines, Energies 11, 2018.

14. X. Yin, X. Zhao and W. Zhang, A novel hydro-kite like energy converter for harnessing both ocean wave and current energy, Energy 158, 2018.

13. X. Tong and X. Zhao*, Power generation control of a monopile hydrostatic wind turbine using an H∞ loop-shaping torque controller and an LPV pitch controller, IEEE Transactions on Control Systems Technology 26, 2018.

12. X. Zhao* and G. Weiss, Stability properties of coupled impedance-passive LTI systems, IEEE Transactions on Automatic Control 62, 2017.

11. X. Tong, X. Zhao* and S. Zhao, Load reduction of monopile wind turbine towers using optimal tuned mass dampers, International Journal of Control 90, 2017.

10. X. Zhao, K. Gouder, J.M.R. Graham and D.J.N. Limebeer, Buffet response and control of a suspension bridge section in a turbulent wind, Journal of Fluids and Structures 62, 2016.

9. K. Gouder, X. Zhao, D.J.N. Limebeer and J.M.R. Graham, Experimental aerodynamic control of a long-span suspension bridge section using leading- and trailing-edge control surfaces, IEEE Transactions on Control Systems Technology 24, 2016.

8. X. Zhao* and G. Weiss, Stabilization of a wind turbine tower model in the plane of the turbine blades, International Journal of Control 87, 2014.

7. X. Zhao* and G. Weiss, Controllability and observability of a well-posed system coupled with a finite-dimensional system, IEEE Transactions on Automatic Control 56, 2011.

6. X. Zhao* and G. Weiss, Suppression of the vibrations of wind turbine towers, IMA Journal of Mathematical Control and Information 28, 2011.

5. J.M.R. Graham, D.J.N. Limebeer and X. Zhao, Aeroelastic control of long-span suspension bridges, Journal of Applied Mechanics - Transactions of the ASME 78, 2011.

4. X. Zhao* and G. Weiss, Well-posedness and controllability of a wind turbine tower model, IMA Journal of Mathematical Control and Information 28, 2011.

3. D.J.N. Limebeer, J.M.R. Graham and X. Zhao, Buffet suppression in long-span suspension bridges, IFAC Annual Reviews in Control 35, 2011.

2. X. Zhao* and G. Weiss, Well-posedness, regularity and exact controllability of the SCOLE model, Mathematics of Control, Signals, and Systems 22, 2010.

1. G. Weiss and X. Zhao, Well-posedness and controllability of a class of coupled linear systems, SIAM Journal on Control and Optimization 48, 2009.

* denotes corresponding author

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School of Engineering

Professor Xiaowei Zhao