Pushpak Jagtap

Pushpak Jagtap 

Pushpak Jagtap
Ph.D. Candidate

Department of Electrical and Computer Engineering
Technical University of Munich
Room: 3963 in building 0509
Arcisstr. 21
80333 München

Tel: +
E-Mail: pushpak.jagtap@tum.de
Personal Webpage | Detailed CV

Bio and Research

Pushpak Jagtap is a PhD student at the Hybrid Control Systems lab, Department of Electrical and Computer Engineering in the Technical University of Munich (TUM) since January 2016. During PhD, he visited L2S-CNRS, France; School of Computing at Newcastle University, UK; and University of Pennsylvania, Philadelphia, USA for some collaborative works. He received Master of Technology (M.Tech.) in Electrical Engineering with specialization in Systems and Control from Indian Institute of Technology (IIT), Roorkee, India in 2014. From September 2014 to September 2015, He worked as a Senior Research Fellow (SRF) at Center of Excellence in Complex and Nonlinear Dynamical Systems, VJTI, Mumbai, India. His research primarily focuses on various aspects of nonlinear control theory and its applications. In particular, his research interests include:

  • Formal Methods, Incremental Stability, Stochastic Systems, Verification and Synthesis of Cyber-Physical Systems.


  • QUEST: A Tool for State-Space Quantization-Free Synthesis of Symbolic Controllers.


  • P. Jagtap, S. Soudjani, and M. Zamani. Formal Synthesis of Stochastic Systems via Control Barrier Certificates, submitted for publication.

  • P. Jagtap, F. Abdi, M. Rungger, M. Zamani, and M. Caccamo. Software Fault Tolerance for Cyber-Physical Systems via Full System Restart, submitted for publication.

  • P. Jagtap and M. Zamani. Symbolic Models for Retarded Jump-Diffusion System, provisionally accepted in Automatica.

Journal Papers

  • P. Jagtap and M. Zamani. Backstepping Design for Incremental Stability of Stochastic Hamiltonian Systems with Jumps, IEEE Transactions on Automatic Control, vol. 63, no. 1, pp. 255-261, 2018.

  • A. Deshpande, P. Jagtap, P. Bansode, A. Mahindrakar, and N. M. Singh. Complex Laplacian-based Distributed Control for Multi-Agent Network, Advances in Complex Systems, vol. 21, no. 5, 2018.

  • 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, 2016.

Book chapter:

  • P. Jagtap, S. Soudjani, and M. Zamani, Temporal Logic Verification of Stochastic Systems Using Barrier Certificates. Automated Technology for Verification and Analysis (ATVA), Los Angeles, CA, Lecture Notes in Computer Science 11138, pp 177-193, Springer, 2018.

  • 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, 2017.

Conference Papers

  • A. Saoud, P. Jagtap*, M. Zamani, and A. Girard. Compositional Abstraction-Based Synthesis for Cascade Discrete-Time Control Systems, IFAC Conference on Analysis and Design of Hybrid Systems (ADHS), Oxford, UK, pp. 13-18, 2018.

  • P. Jagtap and M. Zamani. On Incremental Stability of Time-Delayed Stochastic Control Systems, The 54th Annual Allerton Conference on Communication, Control, and Computing, Monticello, IL, USA, pp. 577-581, 2016.

  • P. Jagtap and M. Zamani. Back-stepping Design for Incremental Stability of Stochastic Hamiltonian Systems, The 55th IEEE Conference on Decision and Control (CDC), Las Vegas, USA, pp. 5367-5372, 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, 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), Hyderabad, India, pp. 66-71, 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), Sydney, NSW, pp. 1811-1816, 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), Pune, pp. 718-723, 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), Orlando, FL, pp. 1-8, 2014.

  • P. Jagtap and G. N. Pillai. Comparison of Extreme-ANFIS and ANFIS Networks for Regression Problems, IEEE International Advance Computing Conference (IACC), Gurgaon, pp. 1190-1194, 2014.

Awards and Honors

  • First place in M. Tech. System and Controls, IIT Roorkee, September 2014.

  • Recipient of MHRD fellowship during M.Tech, at IIT Roorkee, July 2012−July 2014.

  • All India Rank - 86 (99.6%) in GATE 2012, Instrumentation Engineering