Publications in Reverse Chronological Order

Book Chapter

D. Goswami and D. A. Paley, “Global Bilinearization and Reachability Analysis of Control-Affine Nonlinear Systems”, The Koopman Operator in Systems and Control: Concepts, Methodologies, and Applications, Springer International Publishing, 2020. [link]

D. Maity, D. Goswami, “On the effect of quantization on extended dynamic mode decomposition”, submitted.
S. M. Rajkumar, S. Cheng, N. Hovakimyan, D. Goswami, “Linear model predictive control for quadrotors with an analytically derived Koopman model”, submitted. [link]
I. Nayak, D. Goswami, M. Kumar, F. Texeira, “Temporally-consistent Koopman autoencoders for forecasting dynamical systems”, submitted. [link]

D. Goswami, A. Riggins, and D. A. Paley, “Data-driven prediction of urban micromobility: A study of dockless electric scooters”, IEEE Control Systems Magazine, vol. 42, no. 5, pp. 18-31, October 2022. [link]

D. Goswami and D. A. Paley, “Bilinearization, reachability, and optimal control of control-affine nonlinear systems: A Koopman Spectral Approach”, IEEE Transactions on Automatic Control, vol. 67, no. 6, pp. 2715 - 2728, June 2022. [link]
J. Lidard, D. Goswami, D. Snyder, G. Sedky, A. Jones, and D. A. Paley, “Feedback Control and Parameter Estimation for Lift Maximization of a Pitching Airfoil”, AIAA Journal of Guidance, Control, and Dynamics, vol. 44, no. 3, pp. 587-594, March, 2021. [link]
D. Goswami and D. A. Paley, “Non-Gaussian estimation and output feedback using the Gaussian Mixture Kalman Filter”, AIAA Journal of Guidance, Control, and Dynamics, vol. 44, no. 1, pp. 15-24, January, 2021. [link]

A. Wolek, S. Cheng, D. Goswami, and D. A. Paley, “Cooperative mapping and target search over an unknown occupancy graph using mutual information”, IEEE Robotics and Automation Letters, vol. 5, issue. 2, pp. 1071–1078, January 2020. [link]

D. Goswami , Emma Thackray, and D. A. Paley, “Constrained Ulam Dynamic Mode Decomposition: Approximation of the Perron-Frobenius Operator for Deterministic and Stochastic Systems”, IEEE Control Systems Letters, vol. 2, pp. 809-814, October 2018. [link]

D. Maity, D. Goswami, “On the effect of quantization on dynamic mode decomposition”, accepted for presentation at IEEE Conference on Decision and Control 2024.

D. Goswami, “Sequential learning from noisy data: Data-assimilation meets echo-state network”, IEEE Conference on Decision and Control, pp. 7675-7680, Singapore, December 2023. [link]
D. Goswami, “Delay embedded Echo-State Network: A predictor for partially observed systems”, IFAC World Congress, Yokohama, July 2023. [link]

D. Gurevich, D. Goswami, C. L. Fefferman, C. W. Rowley, “Optimal control with learning on the fly: System with unknown drift”, Proceedings of Machine Learning Research, vol. 168, pp. 870-880, presented in 4th Conference on Learning for Dynamics and Control, L4DC 2022, Stanford University. [link]

D. Goswami, A. Wolek, and D. A. Paley, “Data-driven estimation using an Echo-State Neural Network equipped with an Ensemble Kalman Filter”, American Control Conference, pp. 2543–2548, New Orleans, Louisiana, May 2021. [link]

J. Lidard, D. Goswami, D. Snyder, G. Sedky, A. Jones, and D. A. Paley, “Output feedback control for lift maximization of a pitching airfoil”, AIAA Scitech Forum, pp. 1-13, Orlando, Florida, January 2020. [link]

D. Goswami and D. A. Paley, “Global bilinearization and controllability of control-affine nonlinear systems: A Koopman spectral approach”, IEEE Conference on Decision and Control, pp. 6107-6112, Melbourne, Australia, December 2017. [link]
D. Goswami and D. A. Paley, “Non-Gaussian estimation and observer-based feedback using the Gaussian Mixture Kalman and Extended Kalman Filters”, American Control Conference, pp. 4550–4555, Seattle, Washington, May 2017. [link]