潘志超，男，江苏扬州人，1995年6月出生。2017年6月获江南大学电子信息工程学士学位，2024年1月获江南大学控制科学与工程博士学位，2021年3月至2023年3月受国家留学基金委（CSC）资助赴加拿大阿尔伯塔大学联合培养。现为浙江师范大学计算机学院讲师，智能科学系副主任，硕士生导师。主持国家自然科学基金青年基金一项。

欢迎数理基础扎实或对科学研究充满好奇与热情的学生加入团队！

研究方向：

    状态估计：Kalman滤波，Transformer滤波，FIR滤波，MHE，变分贝叶斯推理，Set-membership

    无人系统路径规划：粒子群优化，强化学习

    非线性动态系统建模：Koopman算子，深度学习

    脑神经动力学：抑郁、焦虑症的建模与分类

纵向课题：

    基于Koopman算子的非线性FIR状态估计          国家自然科学基金青年科学基金项目       主持

    面向新发突发传染病的可解释深度学习溯源理论与方法    国家自然科学基金面上项目        参与

横向课题：

    铁路轨道状态检测智能小车惯导系统算法研究

    多机器人协同的列车巡检系统路径规划

    农田草垛自动捡拾机图像识别、路径规划及控制算法研究

主要论文：

[1] Pan, Z., Zhao, S., Huang, B., & Liu, F. (2023). Confidence set-membership FIR filter for discrete time-variant systems. Automatica, 157, 111231. (Regular paper)

[2] Pan, Z., Zhou,.C., & Chen, X. (2026). Robust nonlinear FIR filtering via Koopman operator framework with combined bounded-Gaussian noise characterization. IEEE Transactions on Automation Science and Engineering, 23, 3699-3710.

[3] Pan, Z., Liu, S., Huang, B., & Liu, F. (2024). Zonotopic set-membership state estimation for nonlinear systems based on the deep Koopman operator. Neurocomputing, 129004.

[4] Pan, Z., Luan, X., & Liu, F. (2022). Confidence set-membership state estimation for LPV systems with inexact scheduling variables. ISA Transactions, 122, 38-48.

[5] Pan, Z., Huang, B., & Liu, F. (2022). Moving horizon estimation for bounded noises based on the set-membership approach. Journal of Process Control, 119, 25-33.

[6] Pan, Z., & Liu, F. (2023). Nonlinear set-membership state estimation based on the Koopman operator. International Journal of Robust and Nonlinear Control, 33(4), 2703-2721.

[7] Pan, Z., Luan, X., & Liu, F. (2022). Set-membership state and parameter estimation for discrete time-varying systems based on the constrained zonotope. International Journal of Control, 96(12):3226-3238. 

[8] Pan, Z., Huang, B., & Liu, F. (2023, December). A Koopman operator-based finite impulse response filter for nonlinear systems. In 62nd IEEE Conference on Decision and Control (IEEE-CDC)（pp:2159-2165）. 

[9] Liu, S., Pan, Z., Chen, J., Liu J, (2025). Efficient state estimation for post-combustion CO2 capture plants using PODAE-based reduced-order modeling, Chemical Engineering Science,122891.

[10] Liu, S., Yin, X., Pan, Z., & Liu, J. (2023). A sensitivity-based approach to optimal sensor selection for complex processes. Chemical Engineering Science, 118901. 

[11] Zhang, H., Pan, Z., & Liu, F. (2022, August). Set-membership estimation for industrial processes with uncertain scheduling parameters. In 2022 IEEE International Symposium on Advanced Control of Industrial Processes (AdCONIP) (pp. 325-330). IEEE.

[12] Chen, X., Fan, J., Pan, Z., Zhao, S., & Liu, F. (2026). Robust online parameter estimation of linear ARX models based on variational Bayesian inference. IEEE Transactions on Instrumentation and Measurement, doi: 10.1109/TIM.2026.3670563.

讲授课程：

本科生：Computer Organization and Architecture，最优化理论与方法，控制理论与方法（合作），模式识别与机器学习（合作），人工智能通识（合作）

博士生：现代数学基础：矩阵论、随机过程、最优化