Publications by Lei Feng

Peer reviewed

Articles

[1]

M. Bodaghi, L. Feng and A. Zolfagharian, "4D printing roadmap," Smart materials and structures, vol. 33, no. 11, 2024.

[2]

T. Liu et al., "Computationally Efficient Energy Management for a Parallel Hybrid Electric Vehicle Using Adaptive Dynamic Programming," IEEE Transactions on Intelligent Vehicles, vol. 9, no. 2, pp. 4085-4099, 2024.

[3]

L. Tang et al., "A deep learning based sensor fusion method to diagnose tightening errors," Journal of manufacturing systems, vol. 71, pp. 59-69, 2023.

[4]

J. Yang et al., "A model-based deep reinforcement learning approach to the nonblocking coordination of modular supervisors of discrete event systems," Information Sciences, vol. 630, pp. 305-321, 2023.

[5]

Q. Ji et al., "Design and calibration of 3D printed soft deformation sensors for soft actuator control," Mechatronics (Oxford), vol. 92, pp. 102980-102980, 2023.

[6]

K. Tan et al., "Edge-enabled Adaptive Shape Estimation of 3D Printed Soft Actuators with Gaussian Processes and Unscented Kalman Filters," IEEE Transactions on Industrial Electronics, pp. 1-10, 2023.

[7]

L. Cheng and L. Feng, "Model abstraction for discrete-event systems using a SAT solver," IEEE Access, vol. 11, pp. 17334-17347, 2023.

[8]

J. Yang et al., "Reducing the Learning Time of Reinforcement Learning for the Supervisory Control of Discrete Event Systems," IEEE Access, vol. 11, pp. 59840-59853, 2023.

[9]

Q. Ji et al., "Customized protective visors enabled by closed loop controlled 4D printing," Scientific Reports, vol. 12, no. 1, 2022.

[10]

K. Tan et al., "Decentralized Convex Optimization for Joint Task Offloading and Resource Allocation of Vehicular Edge Computing Systems," IEEE Transactions on Vehicular Technology, pp. 1-15, 2022.

[11]

J. M. Gaspar Sánchez et al., "Edge computing for cyber-physical systems : A Systematic Mapping Study Emphasizing Trustworthiness," ACM Transactions on Cyber-Physical Systems, vol. 6, no. 3, pp. 1-28, 2022.

[12]

Q. Ji et al., "Online reinforcement learning for the shape morphing adaptive control of 4D printed shape memory polymer," Control Engineering Practice, vol. 126, pp. 105257-105257, 2022.

[13]

Q. Ji et al., "Optimal shape morphing control of 4D printed shape memory polymer based on reinforcement learning," Robotics and Computer-Integrated Manufacturing, vol. 73, 2022.

[14]

K. Tan et al., "Shape Estimation of a 3D Printed Soft Sensor Using Multi-Hypothesis Extended Kalman Filter," IEEE Robotics and Automation Letters, vol. 7, no. 3, pp. 8383-8390, 2022.

[15]

Q. Ji et al., "Synthesizing the optimal gait of a quadruped robot with soft actuators using deep reinforcement learning," Robotics and Computer-Integrated Manufacturing, vol. 78, pp. 102382-102382, 2022.

[16]

Y. Wang, L. Feng and K. Andersson, "A Joint-space Position Control-based Approach to Haptic Rendering of Stiff Objects using Gain Scheduling," Journal of Intelligent and Robotic Systems, vol. 103, no. 3, 2021.

[17]

Y. Wang, L. Feng and K. Andersson, "A Position-Control based Approach to Haptic Rendering of Stiff Objects," IEEE Transactions on Haptics, vol. 14, no. 3, pp. 646-659, 2021.

[18]

Y. Wang, L. Feng and K. Andersson, "A position control-based approach to haptic rendering of stiff objects using piece-wise linear model," Advances in Mechanical Engineering, vol. 13, no. 12, 2021.

[19]

G. Zhu et al., "An Efficient Fault Diagnosis Approach Based on Integer Linear Programming for Labeled Petri Nets," IEEE Transactions on Automatic Control, vol. 66, no. 5, pp. 2393-2398, 2021.

[20]

C. Xu et al., "Application research of master-slave cranio-maxillofacial surgical robot based on force feedback," Proceedings of the Institution of mechanical engineers. Part H, journal of engineering in medicine, 2021.

[21]

Q. Ji et al., "Feedback control for the precise shape morphing of 4D printed shape memory polymer," IEEE Transactions on Industrial Electronics, pp. 12698-12707, 2021.

[22]

T. Liu, L. Feng and W. Zhu, "Fuel Minimization of a Hybrid Electric Racing Carby Quasi-Pontryagin’s Minimum Principle," IEEE Transactions on Vehicular Technology, 2021.

[23]

Y. Wang, L. Feng and K. Andersson, "Haptic force rendering of rigid-body interactions : A systematic review," Advances in Mechanical Engineering, vol. 13, no. 9, 2021.

[24]

L. Cheng, L. Feng and Z. Li, "Model abstraction for discrete-event systems by binary linear programming with applications to manufacturing systems," Science Progress, vol. 104, no. 3, 2021.

[25]

J. Liu, L. Feng and Z. Li, "Optimal road grade design based on stochastic speed trajectories for minimising transportation energy consumption," IET Intelligent Transport Systems, vol. 15, no. 11, pp. 1414-1428, 2021.

[26]

L. Feng, J. Wikander and Z. Li, "Fuel Minimization of the Electric Engine CoolingSystem with Active Grille Shutter by IterativeQuadratic Programming," IEEE Transactions on Vehicular Technology, vol. 69, no. 3, pp. 2621-2635, 2020.

[27]

M. Li et al., "Hierarchical predictive energy management of hybrid electric buses based on driver information," Journal of Cleaner Production, vol. 269, 2020.

[28]

Y. Li, L. Feng and Y. Wang, "A cascade control approach to active suspension using pneumatic actuators," Asian Journal of Control, pp. 1-19, 2019.

[29]

H. Zhang, L. Feng and Z. Li, "Control of Black-Box Embedded Systems by Integrating Automaton Learning and Supervisory Control Theory of Discrete-Event Systems," IEEE Transactions on Automation Science and Engineering, pp. 1-14, 2019.

[30]

S. Tao et al., "Elasto-dynamicoptimization of a 5-DoF parallel kinematic machine considering parameteruncertainty," IEEE/ASME transactions on mechatronics, no. 1, pp. 315-325, 2019.

[31]

H. Zhang, L. Feng and Z. Li, "A learning-based synthesis approach to the supremal nonblocking supervisor of discrete-event systems," IEEE Transactions on Automatic Control, vol. 63, no. 10, pp. 3345-3360, 2018.

[32]

H. Zhang et al., "Integration of Learning-Based Testing and Supervisory Control for Requirements Conformance of Black-Box Reactive Systems," IEEE Transactions on Automation Science and Engineering, vol. 15, no. 1, pp. 2-15, 2018.

[33]

A. Rashidinejad, M. Reniers and L. Feng, "Supervisory Control of Timed Discrete-Event Systems Subject to Communication Delays and Non-FIFO Observations," IFAC-PapersOnLine, vol. 51, no. 7, pp. 456-463, 2018.

[34]

M. Khodabakhshian et al., "Reducing Auxiliary Energy Consumption of Heavy Trucks by Onboard Prediction and Real-time Optimization," Applied Energy, vol. 188, pp. 652-671, 2017.

[35]

J. Liu, L. Feng and Z. Li, "The Optimal Road Grade Design for Minimizing Ground Vehicle Energy Consumption," Energies, vol. 10, no. 5, 2017.

[36]

O. Lindgärde et al., "Optimal Vehicle Control for Fuel Efficiency," SAE International Journal of Commercial Vehicles, vol. 8, no. 2, pp. 682-694, 2015.

[37]

M. Khodabakhshian, L. Feng and J. Wikander, "One-step prediction for improving gear changing control of HEVs," Journal of Robotics and Mechatronics, vol. 26, no. 6, pp. 799-807, 2014.

[38]

D. Chen et al., "An architectural approach to the analysis, verification and validation of software intensive embedded systems," Computing, vol. 95, no. 8, pp. 649-688, 2013.

[39]

L. Feng and W. M. Wonham, "On the Computation of Natural Observers in Discrete-Event Systems," Discrete event dynamic systems, vol. 20, no. 1, pp. 63-102, 2010.

[40]

L. Feng, K. Cai and W. M. Wonham, "A structural approach to the non-blocking supervisory control of discrete-event systems," The International Journal of Advanced Manufacturing Technology, vol. 41, no. 11-12, pp. 1152-1168, 2009.

[41]

L. Feng and W. M. Wonham, "Supervisory control architecture for discrete-event systems," IEEE Transactions on Automatic Control, vol. 53, no. 6, pp. 1449-1461, 2008.

[42]

L. Feng, W. M. Wonham and P. S. Thiagarajan, "Designing communicating transaction processes by supervisory control theory," Formal methods in system design, vol. 30, no. 2, pp. 117-141, 2007.

[43]

L. Feng and L. Chen, "Achieving online coordination in real-time collaborative assembly modeling : A supervisory control approach," Journal of Computing and Information Science in Engineering, vol. 6, no. 3, pp. 252-262, 2006.

[44]

L. Chen, Z. Song and L. Feng, "Internet-Enabled Real-Time Collaborative Assembly Modeling via An e-Assembly System: Status and Promise," Computer-Aided Design, vol. 36, no. 9, pp. 835-847, 2004.

Conference papers

[45]

R. Gu et al., "CommonUppRoad: A Framework of Formal Modelling, Verifying, Learning, and Visualisation of Autonomous Vehicles," in Leveraging Applications of Formal Methods, Verification and Validation. Specification and Verification - 12th International Symposium, ISoLA 2024, Proceedings, 2025, pp. 385-404.

[46]

P. Hammer et al., "Non-Axiomatic Reasoning for an Autonomous Mobile Robot," in 2024 IEEE International Conference on Robotics and Automation, ICRA 2024, 2024, pp. 17079-17085.

[47]

S. Thorapalli Muralidharan, G. Andrikopoulos and L. Feng, "A Survey on the Current Trends and Applications of Design Optimization for Compliant and Soft Robotics," in 2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2023, 2023, pp. 47-53.

[48]

K. Tan, L. Feng and M. Törngren, "Collaborative Collision Avoidance of Connected Vehicles Using ADMM with PI-Regulated Lagrangian Multipliers," in 2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023, 2023.

[49]

T. Liu et al., "Optimal and Adaptive Engine Switch Control for a Parallel Hybrid Electric Vehicle Using a Computationally Efficient Actor-Critic Method," in IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM, 2023, pp. 416-423.

[50]

T. Liu et al., "A Low-Complexity and High-Performance Energy Management Strategy of a Hybrid Electric Vehicle by Model Approximation," in 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE), 2022, pp. 455-462.

[51]

J. Chen et al., "A Semantics Modeling Approach Supporting Property Verification based on Satisfiability Modulo Theories," in Syscon 2022 : The 16Th Annual Ieee International Systems Conference (Syscon), 2022.

[52]

A. Duan et al., "Balancing Control of Wheeled-Legged Hexapedal Robots for Traversing Rough Terrains," in 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022, 2022, pp. 1905-1910.

[53]

Q. Ji et al., "Omnidirectional walking of a quadruped robot enabled by compressible tendon-driven soft actuators," in 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022), Kyoto, October 23–27, 2022, 2022, pp. 11015-11022.

[54]

Z. Li et al., "A Bibliometric Analysis on Model-based Systems Engineering," in ISSE 2021 - 7th IEEE International Symposium on Systems Engineering, Proceedings, 2021.

[55]

P. Yang et al., "A Knowledge Management Approach Supporting Model-Based Systems Engineering," in Advances in Intelligent Systems and Computing, 2021, pp. 581-590.

[56]

G. Sten, L. Feng and B. Möller, "A Reconfigurable Test Platform For Developing Autonomous articulated Pendulum-Arm Suspension Forest Machines," in Proceedings of the 20th International and 9th Americas Conference of the ISTVS, 2021.

[57]

S. Thorapalli Muralidharan et al., "A soft quadruped robot enabled by continuum actuators," in 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE), 2021, pp. 834-840.

[58]

T. Liu, L. Feng and S. Fu, "Computationally Efficient Energy Management for a Hybrid Electric Racing Car by Binary Model Predictive Control and Pontryagin’s Minimum Principle," in 34th International Electric Vehicle Symposium and Exhibition (EVS34), 2021.

[59]

J. Ding et al., "Integration of modeling and verification for system model based on KARMA language," in DSM 2021 - Proceedings of the 18th ACM SIGPLAN International Workshop on Domain-Specific Modeling, co-located with SPLASH 2021, 2021, pp. 41-50.

[60]

Q. Ji et al., "A Flexible 4D Printing Service Platform for Smart Manufacturing," in Swedish Production Symposium, 2020.

[61]

H. Zhang et al., "An Approach for Supervisor Reduction of Discrete-Event Systems," in 14th International Conference on Veriﬁcation and Evaluation of Computer and Communication Systems, VECoS 2020, 2020, pp. 3-14.

[62]

Q. Ji et al., "Design and closed loop control of a 3D printed soft actuator," in 2020 16th IEEE International Conference on Automation Science and Engineering (CASE), 2020, pp. 842-848.

[63]

D. Chen et al., "Optimization based path planning for a two-body articulated vehicle," in Optimization based path planning for a two-body articulated vehicle, 2020.

[64]

K. Zhang and L. Feng, "Revisiting strong detectability of networked discrete-event systems," in 15th IFAC Workshop on Discrete Event Systems WODES2020 : 15th IFAC Workshop on Discrete Event Systems WODES2020, 2020, pp. 21-27.

[65]

M. Chen et al., "Study on Efficient Fused Deposition Modelling of Thermoplastic Polyurethane Inflatable Wall Features for Airtightness," in Swedish Production Symposium 2020, 2020.

[66]

T. Liu et al., "A Binary Controller to Ensure Engine Peak Efficiency for a Parallel Hybrid Electric Car," in Proceedings 2019 IEEE Intelligent Transportation Systems Conference, 2019, pp. 726-732.

[67]

Y. Wang, L. Feng and K. Andersson, "A New Approach to Haptic Rendering by Position Control," in 2019 IEEE 15th International Conference on Control and Automation (ICCA), 2019, pp. 148-153.

[68]

J. Krook et al., "Design and Formal Verification of a Safe Stop Supervisor for an Automated Vehicle," in 2019 International Conference on Robotics and Automation, (ICRA), 2019, pp. 5607-5613.

[69]

P. M. Vahdati, L. Feng and M. Törngren, "Design Optimization of Cyber-Physical Systems by Partitioning and Coordination : A Study on Mechatronic Systems," in Proceedings - 21st Euromicro Conference on Digital System Design, DSD 2018, 2018, pp. 304-311.

[70]

T. Liu et al., "Increasing Fuel Efficiency of a Hybrid Electric Competition Car by a Binary Equivalent Consumption Minimization Strategy," in 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE), 2018.

[71]

L. Svensson et al., "Safe Stop Trajectory Planning for Highly Automated Vehicles:An Optimal Control Problem Formulation," in 2018 IEEE Intelligent Vehicles Symposium (IV), 2018, pp. 517-522.

[72]

X. Zhang et al., "A Case Study on Achieving Fair Data Age Distribution in Vehicular Communications," in PROCEEDINGS OF THE 23RD IEEE REAL-TIME AND EMBEDDED TECHNOLOGY AND APPLICATIONS SYMPOSIUM (RTAS 2017), 2017, pp. 307-317.

[73]

F. Rahimi et al., "Early phase design-optimization of mechatronic systems," in ICCMA 2017 Proceedings of the 2017 The 5th International Conference on Control, Mechatronics and Automation, 2017, pp. 42-49.

[74]

Y. Li et al., "A Geometric Programming Approach to the Optimization of Mechatronic Systems in Early Design Stages," in 2016 IEEE INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS (AIM), 2016, pp. 1351-1356.

[75]

X. Zhang et al., "Formulating Customized Specifications for Resource Allocation Problem of Distributed Embedded Systems," in 2016 IEEE/ACM INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN (ICCAD), 2016.

[76]

O. Lindgärde et al., "Optimal Complete Vehicle Control for Fuel Efficiency," in Transportation Research Procedia, 2016, pp. 1087-1096.

[77]

X. Zhang et al., "Design-Space Reduction for Architectural Optimization of Automotive Embedded Systems," in High Performance Computing and Communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conferen on Embedded Software and Systems (ICESS), 2015 IEEE 17th International Conference on, 2015, pp. 1103-1109.

[78]

M. Khodabakhshian, L. Feng and J. Wikander, "Fuel Saving Potential of Optimal Engine Cooling System," in AVEC 2014 International symposium on advanced vehicle control, September 22-26, 2014, 2014.

[79]

M. R. Shoaei, L. Feng and B. Lennartson, "On the computation of natural observers for extended finite automata," in IFAC Proceedings Volumes (IFAC-PapersOnline), 2014, pp. 2448-2455.

[80]

M. Khodabakhshian, L. Feng and J. Wikander, "Predictive control of the engine cooling system for fuel efficiency improvement," in Automation Science and Engineering (CASE), 2014 IEEE International Conference on, 2014, pp. 61-66.

[81]

L. Feng et al., "Case studies in learning-based testing," in Testing Software and Systems : 25th IFIP WG 6.1 International Conference, ICTSS 2013, Istanbul, Turkey, November 13-15, 2013, Proceedings, 2013, pp. 164-179.

[82]

M. Khodabakhshian, J. Wikander and L. Feng, "Fuel efficiency improvement in HEVs using electromechanical brake system," in 2013 IEEE Intelligent Vehicles Symposium (IV), 2013, pp. 322-327.

[83]

M. Khodabakhshian, L. Feng and J. Wikander, "Improvement of fuel efficiency and drivability using simple prediction for gear changing," in IFAC Proceedings Volumes (IFAC-PapersOnline), 2013, pp. 518-523.

[84]

M. Khodabakhshian, L. Feng and J. Wikander, "Improving Fuel Economy and Robustness of an Improved ECMS Method," in 2013 10th IEEE International Conference on Control and Automation (ICCA), 2013, pp. 598-603.

[85]

M. Khodabakhshian, L. Feng and J. Wikander, "Optimization of gear shifting and torque split for improved fuel efficiency and drivability of HEVs," in SAE Technical Papers : Volume 2, 2013, 2013, p. 2013-01-1461.

[86]

D. Chen et al., "Systems Modeling with EAST-ADL for Fault Tree Analysis through HiP-HOPS," in IFAC Proceedings Volumes : (IFAC-PapersOnline), 2013, pp. 91-96.

[87]

M. R. Shoaei, L. Feng and B. Lennartson, "Abstractions for nonblocking supervisory control of Extended Finite Automata," in Automation Science and Engineering (CASE), 2012 IEEE International Conference on, 2012, pp. 364-370.

[88]

M. R. Shoaei, L. Feng and B. Lennartson, "Supervisory control of extended finite automata using transition projection," in Decision and Control (CDC), 2012 IEEE 51st Annual Conference on, 2012, pp. 7259-7266.

[89]

A. Sandberg et al., "Model-Based Safety Engineering of Interdependent Functions in Automotive Vehicles Using EAST-ADL2," in COMPUTER SAFETY, RELIABILITY, AND SECURITY, 2010.

[90]

D. Chen et al., "Towards Model-Based Engineering of Self-Configuring Embedded Systems," in Model-based engineering of embedded real-time systems, 2010, pp. 345-353.

[91]

L. Feng et al., "Verifying System Behaviors in EAST-ADL2 with the SPIN ModelChecker," in IEEE International Conference on Mechatronics and Automation, 2010.

[92]

T. N. Qureshi et al., "Model-Based Development of Middleware forSelf-Configurable Embedded Real Time Systems : Experiences from the DySCAS Project," in Work-in-Progress session at Model-Driven Development for Distributed Real-Time Embedded Systems Summer School (MDD4DRES), Aussois (France), 20-24 April 2009, 2009.

[93]

L. Feng, D. Chen and M. Törngren, "Self Configuration of Dependent Tasks for Dynamically Reconfigurable Automotive Embedded Systems," in Proceedings of the IEEE Conference on Decision and Control, 2008, pp. 3737-3742.

Chapters in books

[94]

R. Anthony et al., "Autonomic Middleware for Automotive Embedded Systems," in Autonomic Communication, Vasilakos, Athanasios V.; Parashar, Manish; Karnouskos, Stamatis; Pedrycz, Witold Ed., : Springer US, 2009, pp. 169-210.

Non-peer reviewed

Articles

[95]

D. Chen et al., "Advances in Automotive System Modeling: EAST-ADL," EETimes Europe Automotive, 2013.

Chapters in books

[96]

Q. Ji et al., "Closed-loop 4D printing of autonomous soft robots," in Smart materials in additive manufacturing : 4d-printed robotic materials, sensors, and actuators, volume 3, : Elsevier BV, 2024, pp. 203-233.

[97]

Q. Ji et al., "Development of a 3D Printed Multi-Axial Force Sensor," in Advances in Transdisciplinary Engineering, : IOS Press, 2022.