HKPFS Ph.D. Fellow PolyU AAE
I am an HKPFS Ph.D. Fellow in the Department of Aeronautical and Aviation Engineering at The Hong Kong Polytechnic University (PolyU), advised by Prof. Wen-Hua Chen and affiliated with RCLAE.
I am exploring how Prof. Chen’s dual control for exploration and exploitation (DCEE) connects with active inference, studying how robots gather useful information while pursuing a task. My longer-term interests are world models and the links between autonomous control and cognitive neuroscience.
Policy–safety separation under polygonal constraints: accepted by Science China Technological Sciences.
Stackelberg attack–defense control: accepted by IEEE/CAA JAS as a regular paper.
Resilient critic-learning control: available in IEEE TII Early Access.
XJTU Graduate with Honor (2025–2026).
Best Student Paper Award, IEEE ICAIS & ISAS · XJTU Qihang Role Model Nominee.
Earlier focus: safe reinforcement learning, prescribed-time control, and differential games, with applications to UAV–UGV coordination and human–UAV interaction.
7 selected papers · Topics overlap
Separates nominal policy learning from geometry-based safety enforcement for systems operating among polygonal obstacles.
Science China Technological Sciences, 2026.
Assigns separate deadlines to actor–critic learning and state response while accounting for actuator limits.
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 56(10): 5952–5965, 2026. IEEE Xplore
Combines actor–critic optimal control with adaptive state–input constraint bounds and a prescribed response time.
IEEE Transactions on Neural Networks and Learning Systems, 37(11): 6412–6425, 2026. IEEE Xplore
Studies resilient critic-learning control under hybrid FDI–DoS attacks and asymmetric input–state constraints.
IEEE Transactions on Industrial Informatics, Early Access, pp. 1–12, 2026. IEEE Xplore
Learns from human–UAV interaction while handling state and input constraints.
IEEE Transactions on Industrial Electronics, 73(2): 3071–3082, 2026. IEEE Xplore
Coordinates UAV–UGV docking through a hierarchical game-based control scheme.
IEEE/CAA Journal of Automatica Sinica, 13(5): 1242–1244, 2026. IEEE Xplore
Pairs obstacle-aware leader planning with prescribed-performance follower tracking in an interconnected UAV–vehicle system.
IEEE Transactions on Automation Science and Engineering, 22: 19568–19581, 2025. IEEE Xplore
Research software
From data to feedback.
200 critic featuresFixed tanh basis · learned readout
Click a curve to inspect it, or choose a rollout and scrub through time.
Interactive data could not load. The recorded figure and project links remain available.
The normalized pendulum uses a data-identified Koopman model and a value critic with 3 quadratic + 197 anchored tanh features. Policy iteration fits the critic’s output weights; the resulting feedback is frozen for these 50 rollouts.
V̂(x) = βᵀφ(x) u(x) = −ĝ(x)ᵀ∇V̂(x) / (2R)
The pulses illustrate signal flow, not measured neuron activations. The plot replays stored states from the 7 September 2026 run, sampled every 0.05 s here (every fifth original sample); no new trajectories or control values are generated.
Including IEEE TAC, IEEE TCNS, IEEE TASE, IEEE TSMC: Systems, and IEEE L-CSS.
Open to collaboration on safe learning, autonomous control, and low-altitude robotics.
junkai.tan@connect.polyu.hk Department of Aeronautical and Aviation Engineering