Technische Universität München
Hybrid Control Systems
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Bio: Pushpak Jagtap is a PhD student in the Hybrid Control Systems group (HCS), Department of Electrical Engineering and Information Technology at the Technical University of Munich (TUM) since January 2016. He received a M.Tech degree in electrical engineering with specialization in systems and control form Indian Institute of Technology (IIT), Roorkee, India in 2014. From September 2014 to September 2015, He was a Senior Research Fellow (SRF) at Center of Excellence in Complex and Nonlinear Dynamical Systems (CoE-CNDS), VJTI, Mumbai, India.
P. Jagtap and M. Zamani. Automated synthesis of infinite dimensional stochastic hybrid systems. Submitted for publication.
P. Jagtap and M. Zamani. Backstepping design for incremental stability of stochastic Hamiltonian systems with jumps. IEEE Transactions on Automatic Control, (forthcoming).
S. Thomas, G.N. Pillai, K. Pal, and P. Jagtap. Prediction of ground motion parameters using randomized ANFIS (RANFIS). Applied Soft Computing, 40, pp.624-634, March 2016.
P. Jagtap and M. Zamani. QUEST: A tool for state-space quantization-free synthesis of symbolic controllers. 14th International Conference on Quantitative Evaluation of SysTems (QEST), Lecture Notes in Computer Science 10503, pp 309-313, Springer. September 2017.
P. Jagtap and M. Zamani. On incremental stability of time-delayed stochastic control systems. The 54th Annual Allerton Conference on Communication, Control, and Computing. pp. 577-581, September 2016.
P. Jagtap and M. Zamani. Backstepping design for incremental stability of stochastic Hamiltonian systems. The 55th IEEE Conference on Decision and Control. pp. 5367-5372, December 2016.
P. Jagtap, P. Raut, P. , Kumar, A. Gupta, N. M. Singh, and F. Kazi. Control of autonomous underwater vehicle using reduced order model predictive control in three dimensional space. IFAC-PapersOnLine, pp.772-777, January 2016.
S. Mane, P. Jagtap, F. Kazi and N. M. Singh. Model predictive control of complex switched mode FC-UC hybrid structure. Indian Control Conference (ICC). pp. 66-71, January 2016.
P. Jagtap, A. Deshpande, N. M. Singh and F. Kazi. Complex Laplacian based algorithm for output synchronization of multi-agent systems using internal model principle. IEEE Conference on Control Applications (CCA). pp. 1811-1816, September 2015.
P. Jagtap, P. Raut, G. N. Pillai, F. Kazi and N. M. Singh. Extreme-ANFIS: A novel learning approach for inverse model control of Nonlinear Dynamical Systems. International Conference on Industrial Instrumentation and Control (ICIC). pp. 718-723, May 2015.
G. N. Pillai, P. Jagtap and M. G. Nisha. Extreme learning ANFIS for control applications. IEEE Symposium on Computational Intelligence in Control and Automation (CICA). pp. 1-8, December 2014.
P. Jagtap and G. N. Pillai. Comparison of extreme-ANFIS and ANFIS networks for regression problems. IEEE International Advance Computing Conference (IACC). pp. 1190-1194, February 2014.