Publications

2024

• Coursey, Austin, Marcos Quinones-Grueiro, and Gautam Biswas. “An Experimental Framework for Evaluating the Safety and Robustness of UAV Controllers.” AIAA AVIATION FORUM AND ASCEND 2024. 2024.
• Coursey, A., Zhang, A., Quinones-Grueiro, M., and Biswas, G., “Hybrid Control Framework of UAVs Under Varying Wind and Payload Conditions,” 2024 American Control Conference (ACC), 2024.

2023

• Austin Coursey, Abel Diaz Gonzalez, Marcos Quinones-Grueiro, and Gautam Biswas. Enhancing Prognostics with Self-Supervised Imputation. 34th International Workshop on Principle of Diagnosis – DX 2023 Workshop in Loma Mar, CA, USA, September 11th – 14th, 2023.
• Austin Coursey, Marcos Quinones-Grueiro, and Gautam Biswas. Anomaly Detection for Multi-Zone Buildings using Cluster-Trained LSTM Autoencoders, IEEE CODIT Conference, Rome, Italy, 2023.
• Ibrahim Ahmed, Marcos Quinones-Grueiro, and Gautam Biswas. Model-based adaptation for sample efficient transfer in reinforcement learning control of parameter-varying systems, IEEE CODIT Conference, Rome, Italy, 2023.
• Austin Coursey, Marcos Quinones-Grueiro, and Gautam Biswas. On Learning Data-Driven Models For In-Flight Drone Battery Discharge Estimation From Real Data, IEEE Smartcomp Conference, Nashville, TN, USA, 2023.
• Ibrahim Ahmed, Marcos Quinones-Grueiro, and Gautam Biswas. Robust trajectory planning for multi-rotor aerial vehicles subject to saturation faults and wind disturbances, AIAA AVIATION Conference, San Diego, CA, USA, 2023.
• Ibrahim Ahmed, Marcos Quinones-Grueiro, and Gautam Biswas. Adaptive fault-tolerant control of octo-rotor UAV under motor faults in adverse wind conditions, AIAA SciTech Conference, National Harbor, MD, USA, 2023.
• Ellis Thompson, Abenezer Taye, James Ashby, Gerald Fattah, Peng Wei, Timothy Bonin, James Jones, Marcos Quinones-Grueiro, Gautam Biswas. Probabilistic Evaluation for Flight Mission Feasibility of a Small Octocopter in the Presence of Wind, AIAA AVIATION, San Diego, CA, USA, 2023.

2022

• Avisek Naug, Marcos Quinones-Grueiro, and Gautam Biswas. Deep Reinforcement Learning Control for Non-stationary Building Energy Management. Energy & Buildings, Vol. 277, Elsevier, pp. 112584, 2022.
• Ibrahim Ahmed, Marcos Quinones-Grueiro, and Gautam Biswas. A high-fidelity simulation test-bed for fault-tolerant octorotor control using reinforcement learning. Digital Avionics Systems Conference, Portsmouth, Virginia, 2022. (Best paper of the Session Swarms)
• Timothy Darrah, M. Quinones-Grueiro, Gautam Biswas, and Andreas Lovberg. Developing Deep Learning Models for System-Level Remaining Useful Life Predictions: Application to Aircraft Engines. Annual Conference of the PHM Society, Nashville, USA 2022. (Accepted)
• Avisek Naug, Marcos Quinones-Grueiro, and Gautam Biswas. Reinforcement learning-based HVAC supervisory control of a multi-zone building- A real case study. IEEE Conference on Control Technology and Applications, Trieste, Italy, 2022. (Accepted)
• Avisek Naug, Marcos Quinones-Grueiro, and Gautam Biswas. Data-Driven Learning Control for Building Energy Management. IEEE American Control Conference, Atlanta, USA, 2022. (Accepted)
• L. Bhan, M. Quinones-Grueiro & G. Biswas. Concurrent policy blending and system identification for generalized assistive control. IEEE International Conference of Robotics and Control (ICRA), Philadephia, 2022.
• Ellis Thompson, Abenezer Taye, Wei Guo, Peng Wei, Marcos Quinones-Grueiro, Ibrahim Ahmed, Gautam Biswas, Jesse Quattrociocchi, Steven Carr, Ufuk Topcu, James Jones, & Marc Brittain. A Survey of eVTOL Aircraft and AAM Operation Hazards, AIAA Forum, Chicago, USA, 2022.
• Timothy Darrah, Gautam Biswas, Jeremy Frank, Marcos Quinones-Grueiro, and Christopher Teubert. A data-centric approach to the study of system-level prognostics for cyber-physical systems: application to safe UAV operations. Journal of Surveillance, Security and Safety, 3(2), 2022, pp.55-87.

2021

• Ibrahim Ahmed, Marcos Quinones-Grueiro, and Gautam Biswas. Transfer reinforcement learning for fault-tolerant control by re-using optimal policies. 2021 5th International Conference on Control and Fault-Tolerant Systems (SysTol), Saint-Raphael, France.
• Luke Bhan, Marcos Quinones-Grueiro, and Gautam Biswas. Fault-Tolerant Control combining Reinforcement Learning and Model-based Control. 2021 5th International Conference on Control and Fault-Tolerant Systems (SysTol), Saint-Raphael, France.
• Marcos Quinones-Grueiro, Gautam Biswas, Ibrahim Ahmed, Timothy Darrah,  Chetan Kulkarni. (2021). Online decision making and path planning framework for safe operation of unmanned aerial vehicles in urban scenarios. International Journal of Prognostics and Health Management.
• Timothy Darrah, Jeremy Frank, Marcos Quiñones-Grueiro, Gautam Biswas. (2021). A Data Management Framework & UAV Simulation Testbed for the Study for System-level Prognostics Technologies. Annual Conference of the Prognostics & Health Management (PHM) Society (to appear).
• Timothy Darrah, Marcos Quiñones-Grueiro, Gautam Biswas, Chetan Kulkarni. (2021). Prognostics Based Decision Making for Safe and Optimal UAV Operations. AIAA Scitech Forum.
• Ibrahim Ahmed, Marcos Quinones-Grueiro, and Gautam Biswas, Policy reuse for transfer reinforcement learning in fault-tolerant control. 32nd International Workshop on Principles of Diagnosis (DX-2021), Hamburg, Germany.
• Luke Bhan, Marcos Quinones-Grueiro and Gautam Biswas, Adaptive Model-Based Control with Reinforcement Learning for Fault Tolerance. 32nd International Workshop on Principles of Diagnosis (DX-2021), Hamburg, Germany. (winner of Best Student Paper Award).

2020

• Marcos Quiñones-Grueiro, Timothy Darrah, Gautam Biswas, Chetan Kulkarni (2020) “A decision-making framework for safe operations of unmanned aerial vehicles in urban scenarios”. Annual Conference of the Prognostics & Health Management (PHM) Society.
• Avisek Naug, Marcos Quiñones-Grueiro, Gautam Biswas (2020) “Continual adaptation in deep reinforcement learning-based control applied to non-stationary building environments”, Proceedings of the 1st International Workshop on Reinforcement Learning for Energy Management in Buildings & Cities.
• Avisek Naug, Marcos Quiñones-Grueiro, Gautam Biswas (2020) “A Relearning Approach to Reinforcement Learning for Control of Smart Buildings”, 2020, arXiv:2008.01879
• Darrah, T., Kulkarni, C., Biswas, G. (2020). The Effects of Component Degradation on System-Level Prognostics for the Electric Powertrain System of UAVs. AIAA Scitech Forum.
• Jung, D., Dong, Y., Frisk, E., Krysander, M., & Biswas, G. (2020). Sensor selection for fault diagnosis in uncertain systems. International Journal of Control, 93(3), 629-639.
• Zhang, W., Biswas, G., Zhao, Q., Zhao, H., & Feng, W. (2020). Knowledge distilling based model compression and feature learning in fault diagnosis. Applied Soft Computing, 88, 105958.
• Sajan, K. S., Bariya, M., Basak, S., Srivastava, A., Dubey, A., von Meier, A., & Biswas, G. (2020, April). Realistic Synchrophasor Data Generation for Anomaly Detection and Event Classification. In 2020 8th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (pp. 1-6).
• Ibrahim Ahmed, Marcos Quinones-Grueiro, Gautam Biswas (2020). Fault-Tolerant Control of Degrading Systems with On-Policy Reinforcement Learning“. IFAC-PapersOnLine.
• Ibrahim Ahmed, Marcos Quinones-Grueiro, Gautam Biswas (2020). Complementary Meta-Reinforcement Learning for Fault-Adaptive Control“. PHM.

2019

• A. Naug, I. Ahmed, and G. Biswas (2019). “Online Energy Management in Commercial Buildings using Deep Reinforcement Learning,” 2019 IEEE International Conference on Smart Computing (SMARTCOMP).
• Jha, M. S., Theilliol, D., Biswas, G., & Weber, P. (2019, September). Approximate Q-learning approach for Health Aware Control Design. In 2019 4th Conference on Control and Fault Tolerant Systems (SysTol) (pp. 418-423). IEEE.
• Khorasgani, H., & Biswas, G. (2019). Mode Detection and Fault Diagnosis in Hybrid Systems. In Fault Diagnosis of Dynamic Systems (pp. 319-345). Springer, Cham.
• Khorasgani, H., Biswas, G., & Jung, D. (2019). Structural methodologies for distributed fault detection and isolation. Applied Sciences, 9(7), 1286.

2018

• I. Ahmed, H. Khorasgani, and G. Biswas, “Comparison of Model Predictive and Reinforcement Learning Methods for Fault-Tolerant Control,” IFAC-PapersOnLine, vol. 51, no. 24, pp. 233–240, 2018.
• Naug, Avisek, and Gautam Biswas. “Data driven methods for energy reduction in large buildings.” 2018 IEEE International Conference on Smart Computing (SMARTCOMP). IEEE, 2018.
• Naug, Avisek, and Gautam Biswas. “A Data Driven Method for Prediction of Energy Demand in Commercial Buildings.” 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE). IEEE, 2018.
• Khorasgani, H., & Biswas, G. (2018). A methodology for monitoring smart buildings with incomplete models. Applied Soft Computing, 71, 396-406.
• Khorasgani, H., Farahat, A., Ristovski, K., Gupta, C., & Biswas, G. (2018, September). A framework for unifying model-based and data-driven fault diagnosis. In PHM society conference (Vol. 10, No. 1).
• Mack, D. L., Biswas, G., Khorasgani, H., Mylaraswamy, D., & Bharadwaj, R. (2018). Combining expert knowledge and unsupervised learning techniques for anomaly detection in aircraft flight data. at-Automatisierungstechnik, 66(4), 291-307.

2017

• Khorasgani, H., & Biswas, G. (2017). A combined model-based and data-driven approach for monitoring smart buildings. In Principles of Diagnosis Workshop DX -2017 (pp. 21-36).
• Khorasgani, H., & Biswas, G. (2017). Structural fault detection and isolation in hybrid systems. IEEE Transactions on Automation Science and Engineering, 15(4), 1585-1599.
• Pettet, G., Nannapaneni, S., Stadnick, B., Dubey, A., & Biswas, G. (2017, August). Incident analysis and prediction using clustering and bayesian network. In 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) (pp. 1-8). IEEE.
• Niggemann, O., Biswas, G., Kinnebrew, JS, Khorasgani, H., Volgmann, S., & Bunte, A. (2017). Data analysis in the intelligent factory. In manual Industrie 4.0 Vol. 2 (pp. 471-490). Springer Vieweg, Berlin, Heidelberg.
• Mukhopadhyay, A.,  Vorobeychik, Y., Dubey, A., & Biswas, G. (2017, January). Prioritized allocation of emergency responders based on a continuous-time incident prediction model. In International Conference on Autonomous Agents and MultiAgent Systems.

2016

• Daniel LC Mack, Gautam Biswas, Xenofon Koutsoukos, and Dinkar Mylaraswamy, “Learning Bayesian Network Structures to Augment Aircraft Diagnostic Reference Models,”  IEEE Transactions on Automation Science and Engineering, DOI:  10.1109/TASE.2016.2542186

• Gautam Biswas, Hamed Khorasgani, Gerald Stanje, Abhishek Dubey, Somnath Deb, and Sudipto Ghoshal, “An Approach To Mode and Anomaly Detection with Spacecraft Telemetry Data,” International Journal of Prognostics and Health Management, vol. 7 (Special Issue on Big Data Anallytics)

• Hamed Khorasgani, Gautam Biswas, and Shankar Sankararaman, “Methodologies for System-level Remaining Useful Life Prediction,” Reliability Engineering and System Safety, vol. 154, pp. 8-18.

•  Joshua D. Carl and Gautam  Biswas,  “An Approach to Parallel Simulation of Ordinary Differential Equtions,” Journal of Software Engineering Applications, vol. 9, pp. 250-290.

• G. Zhou, G. Biswas, W. Zhang, Q. Zhao, W. Feng,  “Comparison of State Estimation Techniques for Nonlinear Hybrid Systems,” Simulation, vol. 92, no. 4, pp. 357-376.

• Daniel LC Mack, Gautam Biswas, Dinkar Mylaraswamy, and Raj Bharadwaj, “An Unsupervised Approach to Anomaly Detection from Aircraft Flight Data,”   27^th International Workshop on Principles of Diagnosis: DX-2016, Denver, Colorado, October 4-7,.

• M.J. Daigle, A. Bregon, X. Koutsoukos, G. Biswas, and B. Pulido,  “A qualitative event-based approach to multiple fault diagnosis in continuous systems using structural model decomposition,” Engineering Applications of Artificial Intelligence, vol. 53, pp. 190-206, 2016.

Selected Papers (2015 and earlier)

• Niggemann, O., Biswas, G., Kinnebrew, J. S., Khorasgani, H., Volgmann, S., & Bunte, A. (2015, August). Data-Driven Monitoring of Cyber-Physical Systems Leveraging on Big Data and the Internet-of-Things for Diagnosis and Control. In DX@ Safeprocess (pp. 185-192).
• Khorasgani, H., Jung, D. E., Biswas, G., Frisk, E., & Krysander, M. (2014, December). Robust residual selection for fault detection. In 53rd IEEE Conference on Decision and Control (pp. 5764-5769). IEEE.
• Bregon, A., Daigle, M., Roychoudhury, I., Biswas, G., Koutsoukos, X., & Pulido, B. (2014). An event-based distributed diagnosis framework using structural model decomposition. Artificial Intelligence, 210, 1-35.
• Bouamama, B. O., Biswas, G., Loureiro, R., & Merzouki, R. (2014). Graphical methods for diagnosis of dynamic systems. Annual reviews in control, 38(2), 199-219.
• Bregon, A., Biswas, G., Pulido, B., Alonso-Gonzalez, C., & Khorasgani, H. (2013). A common framework for compilation techniques applied to diagnosis of linear dynamic systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 44(7), 863-876.
• Khorasgani, H., Kulkarni, C., Biswas, G., Celaya, J. R., & Goebel, K. (2013). Degradation modeling and remaining useful life prediction of electrolytic capacitors under thermal overstress conditions using particle filters. In Annual Conference of the Prognostics and Health Management Society (PHM’13).
• Kulkarni, C. S., Celaya, J. R., Biswas, G., & Goebel, K. (2012, September). Accelerated aging experiments for capacitor health monitoring and prognostics. In 2012 IEEE AUTOTESTCON Proceedings (pp. 356-361). IEEE.
• Kulkarni, C. S., Celaya, J. R., Goebel, K., & Biswas, G. (2012). Physics-based electrolytic capacitor degradation models for prognostic studies under thermal overstress. European Conference of the Prognostics and Health Management Society.
• Frisk, E., Bregon, A., Aslund, J., Krysander, M., Pulido, B., & Biswas, G. (2012). Diagnosability analysis considering causal interpretations for differential constraints. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 42(5), 1216-1229.
• Tantawy, A., Koutsoukos, X., & Biswas, G. (2012). Aircraft power generators: hybrid modeling and simulation for fault detection. IEEE Transactions on Aerospace and Electronic Systems, 48(1), 552-571.
• Celaya, J., Kulkarni, C., Biswas, G., Saha, S., & Goebel, K. (2011). A model-based prognostics methodology for electrolytic capacitors based on electrical overstress accelerated aging.
• Roychoudhury, I., Daigle, M. J., Biswas, G., & Koutsoukos, X. (2011). Efficient simulation of hybrid systems: A hybrid bond graph approach. Simulation, 87(6), 467-498.
• Daigle, M. J., Koutsoukos, X. D., & Biswas, G. (2010). An event-based approach to integrated parametric and discrete fault diagnosis in hybrid systems. Transactions of the Institute of Measurement and Control, 32(5), 487-510.
• Kulkarni, C., Biswas, G., Koutsoukos, X., Celaya, J., & Goebel, K. (2010, September). Integrated diagnostic/prognostic experimental setup for capacitor degradation and health monitoring. In 2010 IEEE AUTOTESTCON (pp. 1-7). IEEE.
• Daigle, M. J., Roychoudhury, I., Biswas, G., Koutsoukos, X. D., Patterson-Hine, A., & Poll, S. (2010). A comprehensive diagnosis methodology for complex hybrid systems: A case study on spacecraft power distribution systems. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 40(5), 917-931.
• Kulkarni, C., Biswas, G., & Koutsoukos, X. (2009, October). A prognosis case study for electrolytic capacitor degradation in DC-DC converters. In PHM Conference.
• Roychoudhury, I., Biswas, G., & Koutsoukos, X. (2009). Designing distributed diagnosers for complex continuous systems. IEEE Transactions on Automation Science and Engineering, 6(2), 277-290.
• Roychoudhury, I., Biswas, G., & Koutsoukos, X. (2008, September). Comprehensive diagnosis of continuous systems using dynamic bayes nets. In Proc. of the 19th International Workshop on Principles of Diagnosis (pp. 151-158).
• Poll, S., Patterson-Hine, A., Camisa, J., Garcia, D., Hall, D., Lee, C., … & Sweet, A. (2007, May). Advanced diagnostics and prognostics testbed. In Proceedings of the 18th International Workshop on Principles of Diagnosis (DX-07) (pp. 178-185).
• Daigle, M. J., Koutsoukos, X. D., & Biswas, G. (2007). Distributed diagnosis in formations of mobile robots. IEEE Transactions on Robotics, 23(2), 353-369.
• Narasimhan, S., & Biswas, G. (2007). Model-based diagnosis of hybrid systems. IEEE Transactions on systems, man, and cybernetics-Part A: Systems and humans, 37(3), 348-361.
• Roychoudhury, I., Biswas, G., & Koutsoukos, X. (2006, June). A Bayesian approach to efficient diagnosis of incipient faults. In Proceedings of the 17th International Workshop on Principles of Diagnosis (DX-06) (pp. 243-250).
• Ji, M., Zhang, Z., Biswas, G., & Sarkar, N. (2003). Hybrid fault adaptive control of a wheeled mobile robot. IEEE/ASME transactions on mechatronics, 8(2), 226-233.
• Biswas, G., Simon, G., Mahadevan, N., Narasimhan, S., Ramirez, J., & Karsai, G. (2003). A robust method for hybrid diagnosis of complex systems. IFAC Proceedings Volumes, 36(5), 1023-1028.
• Feenstra, P. J., Mosterman, P. J., Biswas, G., & Breedveld, P. C. (2001). Bond graph modeling procedures for fault detection and isolation of complex flow processes.
• Lerner, U., Parr, R., Koller, D., & Biswas, G. (2000, July). Bayesian fault detection and diagnosis in dynamic systems. In Aaai/iaai (pp. 531-537).
• Manders, E. J., Narasimhan, S., Biswas, G., & Mosterman, P. J. (2000). A combined qualitative/quantitative approach for fault isolation in continuous dynamic systems. IFAC Proceedings Volumes, 33(11), 505-510.
• McIlraith, S., Biswas, G., Clancy, D., & Gupta, V. (2000, March). Hybrid systems diagnosis. In International Workshop on Hybrid Systems: Computation and Control (pp. 282-295). Springer, Berlin, Heidelberg.
• Mosterman, P. J., & Biswas, G. (1999). Diagnosis of continuous valued systems in transient operating regions. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 29(6), 554-565.
• Manders, E. J., Mosterman, P. J., & Biswas, G. (1999, June). Signal to symbol transformation techniques for robust diagnosis in TRANSCEND. In Tenth International Workshop on Principles of Diagnosis (pp. 155-165).
• Mosterman, P. J., & Biswas, G. (1998). A theory of discontinuities in physical system models. Journal of the Franklin Institute, 335(3), 401-439.
• Mosterman, P. J., Biswas, G., & Sztipanovits, J. (1998). A hybrid modeling and verification paradigm for embedded control systems. Control Engineering Practice, 6(4), 511-521.
• Mosterman, P. J., & Biswas, G. (1997, August). Formal specifications for hybrid dynamical systems. In IJCAI (1) (pp. 568-577).
• Mosterman, P. J., & Biswas, G. (1997, July). Monitoring, prediction, and fault isolation in dynamic physical systems. In AAAI/IAAI (pp. 100-105).