Publications

[16] G. Vennam and A. Sahoo, “Learning-based faulty state estimation using SOH-coupled model under internal thermal faults in lithium-ion batteries,” IEEE Transactions on Transportation Electrification, Accepted,  May 03, 2023.

[15]  G. Vennam and A. Sahoo, “A dynamic SOH-coupled lithium-ion cell model for state and parameter estimation,” IEEE Transactions on Energy Conversion, Accepted, Oct. 2022.

[14] G. Vennam, A. Sahoo, and S. Ahmed, “A survey on lithium-ion battery internal and external degradation modeling and state of health estimation,” Journal of Energy Storage, vol.52, part A, Aug. 22.

[13] A Sahoo, V. Narayanan, and S Jagannathan, “Resource aware learning-based optimal control of cyber-physical systems,” IEEE Technical Committee on Cyber-Physical Systems, vol.6, no.1, pp.24-34, Mar. 2021.

[12] L. Li, G. Yen, A Sahoo, L Chang, and T Gu, “On the estimation of Pareto front and dimensional similarity in many-objective evolutionary algorithm,” Information Sciences, Elsevier, vol. 563, pp.375-400 Jul. 2021.

[11] A. Sahoo and V. Narayanan, “Differential-game for resource-aware approximate optimal control of large-scale nonlinear systems with multiple players,” Neural Network, vol. 124, pp. 95-108, 2020.

[10]  H. Niu, A. Sahoo, C. Bhowmick, and S. Jagannathan, “An optimal hybrid learning approach for attack detection in linear networked control systems,” IEEE/CAA Journal of Automatica Sinica, vol. 6, no. 6, pp. 1404-1416, 2019.

[9] A. Sahoo and V. Narayanan, “Optimization of sampling intervals for tracking control of nonlinear systems: A game theoretic approach,” Neural Networks, vol. 114, pp. 78-90, 2019.

[8] V. Narayanan, A. Sahoo, S. Jagannathan, and K. George, “Approximate optimal distributed control of nonlinear interconnected systems using event-triggered nonzero-sum games,” IEEE Transaction of Neural Network and Learning Systems, vol. 30, no. 5, pp. 1512- 1522, 2018.

[7]  A. Sahoo, V. Narayanan, and S. Jagannathan, “A min-max approach to event and self-triggered sampling and regulation of linear systems,” IEEE Transaction on Industrial Electronics, vol. 66, no. 7, pp. 5433- 5440, 2018.

[6] A. Sahoo, Hao Xu, and S. Jagannathan, “Approximate optimal control of affine nonlinear continuous-time systems by using event-sampled neuro-dynamic programming,” IEEE Transaction of Neural Network and Learning Systems, vol. 28, no. 3, pp. 639- 652, 2017.

[5]  A. Sahoo, Hao Xu, and S. Jagannathan, “Stochastic optimal regulation of nonlinear networked control systems by using event-driven adaptive dynamic programming,” IEEE Transaction on Cybernetics, vol. 47, no. 2, pp. 425-438, 2017.

[4]  A. Sahoo, Hao Xu, and S. Jagannathan, “Adaptive neural network-based event-triggered control of single-input single-output nonlinear discrete-time systems,” IEEE Transaction on Neural Networks and Learning Systems, vol. 27, no. 1, pp. 151-164, 2016.

[3]  A. Sahoo, Hao Xu, and S. Jagannathan, “Near-optimal event-triggered control of nonlinear discrete-time systems using neuro-dynamic programming,” IEEE Transaction on Neural Networks and Learning Systems, vol. 27, no. 9, pp. 1801-1815, 2016.

[2] A. Sahoo, Hao Xu, and S. Jagannathan, “Neural network–based event-triggered state feedback control of nonlinear continuous-time systems,” IEEE Transaction on Neural Networks and Learning Systems, vol. 27, no. 3, pp. 497-509, 2016.

[1] Hao Xu, A. Sahoo, and S. Jagannathan, “Stochastic adaptive event-triggered control and network scheduling protocol co-design for distributed networked systems,” IET Control Theory & Applications, vol. 8, no. 18, pp. 2253-2262, 2014.

[3] H. Xu, A. Sahoo, and S. Jagannathan, “Joint scheduling and optimal event-triggered control of distributed cyber-physical systems,” Principles of Cyber-Physical Systems (Cambridge University Press), p. 104, 2020.

[2] A. Sahoo b and S. Jagannathan, “Adaptive optimal regulation of a class of uncertain nonlinear systems using event sampled neural network approximators,” Control of Complex Systems: Theory and Applications (Elsevier), 2016.

[1] H. Xu, A. Sahoo, and S. Jagannathan, “Neural network control of nonlinear discrete-time systems in affine form in the presence of communication network,” Frontiers of Intelligent Control and Information Processing (World Scientific Publishing), pp. 1510-0191, 2014.

31. Sazzad Hossen, Avimanyu Sahoo, and Huaxia Wang, "Multi-label Defect Classification of Large Concrete Structures Using Vision Graph Neural Network with Edge Convolution," Submitted to International Joint Conference on Neural Networks (IJCNN), 2024

30. Avimanyu Sahoo, Xiangyu Meng, Vignesh Narayanan, "Aperiodic Discrete-time Control: Optimizing Trade-off Between Communication and Control," Submitted to  American Control Conference, 2023.

29. Geetika Vennam and A. Sahoo, “Core temperature estimation of lithium-ion batteries under internal thermal faults using neural networks,”  Accepted for presentation at  7th IEEE Conference on Control Technology and Applications, 2023. 

28. Geetika Vennam and A. Sahoo, “A novel coupled electro-thermal-aging Model for simultaneous SOC, SOH, and parameter estimation of lithium-ion batteries,” in Proceedings of the c American Control Conference,  Atlanta, GA, USA, Jun. 2022, pp. 5259-5264. 

27.  A. Sahoo, C. Yang, and Y. Chang, “Graduate curriculum in mechatronics and robotics: Development and implementation challenges for engineering technology,” in Virtual ASEE Annual Conference and Exposition, Virtual Online, Jul. 2021. 

26. A. Sahoo, V. Narayanan, and Q. Zhao, “Adaptive gain observers for distributed state estimation of linear systems,” in Proceedings of the American Control Conference, New Orleans, USA, May. 2021. 

25. A. Sahoo, V. Narayanan, and Q. Zhao, “Finite-time adaptive optimal output feedback control of linear systems with intermittent feedback,” in Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), Virtual, Sydney, Australia, Dec. 2020. 

24. L. Li, A. Sahoo, Liang Chang, “A multi-objective evolutionary algorithm based on R2 indicator for pickup and delivery problem with time windows,” in Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), Virtual, Sydney, Australia, Dec. 2020. 

23. H. Vora, Y. Chang, C. Yang, A. Alexander, I. Park, and A. Sahoo a , “Roll-The-Roller 3D printing design contest: The experience-based summer bridge program to improve the success of incoming engineering freshmen students. (Work in Progress),” in Proceedings of the ASEE Annual Conference and Exposition, Virtual Online, Apr. 2020, pp. 1-14. 

22. A. Sahoo, A. Alexander, and J. Hahn, “Exposure of engineering technology students to cutting-edge technology: A multi-major senior design experience,” in Proceedings of the ASEE Annual Conference and Exposition, Virtual Online, Mar. 2020, pp. 1-23. 

21. L. Li, A. Sahoo, and L. Chang, “A novel evolutionary algorithm with Pareto front adaption for many-objective optimization,” in Proceedings of the American Control Conference (ACC), Virtual, Jul. 2020, pp. 3607-3612. 

20. V. Kumar, A. Sahoo, and F W Liou, “Cyber-enabled product life-cycle management: a Multiagent framework,” in Procedia Manufacturing, Chicago, IL, USA, Aug. 12-14, 2019, vol. 39,  pp.123-131. 

19. A. Sahoo and Y. Chang, “Laboratory activities of fundamentals of mechatronics course for undergraduate technology students,” in Proceedings of the ASEE Annual Conference and Exposition, Tampa, FL, June 15-19, 2019, pp. 1-17. 

18. H. Niu, A. Sahoo, C. Bhowmick and S. Jagannathan, “Attack detection in linear networked control systems by using learning methodology,” in Proceedings of the IEEE Conference on Control Technology and Applications, Hong Kong, China, Dec. 2019, pp. 148-153.

17. G. Vennam and A. Sahoo, “Simultaneous state and parameter estimation of lithium-ion battery: An observer based approach,” in Proceedings of the American Control Conference (ACC), 2019, Philadelphia, PA, USA, 2019, pp. 4485-4490.

16. A. Sahoo and V. Narayanan, and S. Jagannathan, “Event-triggered control of N-player nonlinear systems using nonzero-sum games,” in Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), Bengaluru, India, Nov. 20, 2018, pp. 1-6. 

15. V. Narayanan, A. Sahoo, and S. Jagannathan, “Adaptive optimal distributed control of Linear interconnected systems,” in Proceedings of the IEEE Symposium Series on Computational  Intelligence (SSCI), Bengaluru, India, Nov. 20, 2018, pp. 1-6. ab, 

14. V. Narayanan, A. Sahoo and S. Jagannathan, “Approximate optimal distributed control of nonlinear interconnected systems using nonzero-sum games,” in Proceedings of the IEEE Conference on Decision and Control (CDC), Miami, FL, USA, Dec. 18, 2018, pp. 2872-2877. 

13. A. Sahoo and V. Narayanan, “Event-based near-optimal sampling and tracking control of nonlinear systems,” in Proceedings of the IEEE Conference on Decision and Control (CDC), Miami, FL, USA, Dec. 18, 2018, pp. 55-60. 

12. V. Narayanan, A. Sahoo, and S. Jagannathan, “Optimal event-triggered control of nonlinear systems: A min-max approach,” in Proceedings of the American Control Conference (ACC), Milwaukee, WI, 2018, pp. 3441-3446. 

11. A. Sahoo, V. Narayanan, and S. Jagannathan, “Optimal event-triggered control of uncertain linear networked control systems: A co-design approach,” in Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), Honolulu, HI, 2017, pp. 1-6. 

10. A. Sahoo, V. Narayanan, and S. Jagannathan, “Optimal sampling and regulation of uncertain interconnected linear continuous-time systems,” in Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), Honolulu, HI, 2017, pp. 1-6. 

9. A. Sahoo, H. Xu, and S. Jagannathan, “Event-based neural network approximation and control of uncertain nonlinear continuous-time systems,” in Proceedings of the American b Control Conference (ACC), Chicago, IL, 2015, pp. 1567-1572. 

8. A. Sahoo, H. Xu, and S. Jagannathan, “Event-triggered optimal regulation of uncertain linear discrete-time systems by using Q-learning scheme,” in Proceedings of the IEEE Conference on Decision and Control (CDC), Los Angeles, CA, 2014, pp. 1227- 1232. 

7. A. Sahoo and S. Jagannathan, “Event-triggered optimal control of nonlinear continuous-time systems in affine form by using neural network,” in Proceedings of the IEEE Conference on Decision and Control (CDC), Los Angeles, CA, 2014, pp. 1233- 1238. 

6. A. Sahoo, H. Xu, and S. Jagannathan, “Event-based optimal regulator design for nonlinear networked control systems,” in Proceedings of the IEEE Symposium Series on Computational  Intelligence (SSCI), Orlando, FL, 2014, pp. 1-8. 

5. A. Sahoo, H. Xu, and S. Jagannathan, “Near-optimal event-based control of nonlinear discrete-time systems in affine form with measured input-output data,” in Proceedings of the International Joint Conference on Neural Networks (IJCNN), Beijing, China, 2014, pp. 36713676. 

4. A. Sahoo, H. Xu, and S. Jagannathan, “Neural network approximation-based event-triggered control of uncertain MIMO nonlinear discrete-time systems,” in Proceedings of the American b Control Conference (ACC), Portland, OR, 2014, pp. 2017- 2022. 

3. A. Sahoo, H. Xu, and S. Jagannathan, “Neural network-based adaptive event-trigger control of affine nonlinear continuous-time systems,” in Proceedings of the IEEE International Symposium on Intelligent Control (ISIC), Hyderabad, India, 2013, pp. 35-40.

2. A. Sahoo, Hao Xu, S. Jagannathan, "Neural network based adaptive event-triggered control of affine nonlinear discrete-time systems with unknown internal dynamics,” in Proceedings of b the American Control Conference (ACC), Washington, DC, 2013, pp. 6418-6423. 

1. A. Sahoo, H. Xu, and S. Jagannathan, “Adaptive event-triggered control of an uncertain linear discrete-time system using measured input and output data,” in Proceedings of the American Control Conference (ACC), Washington, DC, 2013, pp. 5672-5677.

7.  G. Vennam, A Sahoo, and Vignesh Narayanan, Neural network-base state estimation of lithium-ion batteries under internal faults, SIAM Conference of Applications of Dynamical Systems, May 2023

6. G. Vennam and A Sahoo, State of health inclusive aging model of lithium-ion batteries, Virtual International Mechatronics Conference and Exhibition, Oct. 01, 2021. 

5. G. Vennam and A Sahoo, State of health estimation of lithium-ion batteries for electric vehicles: The state of the art, Virtual International Mechatronics Conference and Exhibition, Oct. 21, 2020. 

4. G. Vennam, A Sahoo, and  Vignesh Narayana, Neural network control of inter-connected inverted pendulum with uncertain dynamics: A Survey, Virtual Society of Open Innovation (SOI) and Oklahoma State University 2020 Conference, Daegu, Korea, July 10-13, 2020. 

3. L. Li, and A Sahoo, Multi-objective optimization and its applications: The state of the art, Virtual Society of Open Innovation (SOI) and Oklahoma State University 2020 Conference, Daegu, Korea, July 10-13, 2020. 

2. G. Vennam, and A Sahoo, Self-learning battery management systems for lithium-ion battery, Virtual Society of Open Innovation (SOI) and Oklahoma State University 2020 Conference, Daegu, Korea, July 10-13, 2020. 

1. G. Vennam and A. Sahoo, “SOC and parameter estimation of lithium-ion battery for fault diagnostics,” in Proceedings of the Frontier in Power, Stillwater, Oct. 29, 2018.