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Ajay Kumar Sampathirao

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Ajay Kumar Sampathirao

Technische Universität Berlin
Fachgebiet Regelungssysteme
Sekretariat EN11
Einsteinufer 17
D-10587 Berlin

Office: EN 240 (Elektrotechnik Neubau)
Phone: +49 (0)30 314-23573
Fax: +49 (0)30 314-21137
Email: Sampathirao@control.TU-berlin.de

Biography Hey, I'm Ajay. I received my bachelors in electrical and electronics engineering from NIT Warangal, 2010. In 2012, I received my masters from IIT Delhi with specialisation in control and automation. I worked as a software engineer for a brief period in WESEE. In 2013, I enrolled in the doctoral program in IMT, Lucca, Italy. My supervisors are Alberto Bemporad and Pantelis Sopasakis. I discussed my thesis in December 2016.

Research My research focus on Model Predictive Control (MPC), parallel optimisation methods and GPUs. My PhD title is "Parallel methods of solving stochastic optimal control: control for drinking water networks". This work discussed about algorithms that are suitably parallised to solve stochastic optimal control in real-time. These algorithms are implemented on parallel computation hardware like GPU. These algorithms are employed for economic management of water networks.

Current work Currently, I am working on centralised and distributed energy management system (EMS) in isolated and interconnected microgrid. The objective of the EMS solutions is to maximise the renewable infeed and minimise the operation of the thermal/diesel generators.



A. K. Sampathirao, P. Sopasakis, A. Bemporad, P. Patrinos. GPU-Accelerated Stochastic Predictive Control of Drinking Water Networks. IEEE Transactions on Control Systems Technology, PP (99):1-12, 2017.
P. Sopasakis, A.K. Sampathirao, A. Bemporad, P. Patrinos. Uncertainty-aware demand management of water distribution networks in deregulated energy markets. Environmental Modelling & Software, 101 pages 10 - 22, 2018.
S. Hofmann, A. K. Sampathirao, C. A. Hans, J. Raisch, A. Heidt, E. Bosch. Saturation-Aware Model Predictive Energy Management for Droop-Controlled Islanded Microgrids. 2019. Submitted.
A. K. Sampathirao, C. A. Hans, J. Raisch. Two-Stage Consensus-Based Distributed MPC for Interconnected Microgrids. 2018. Submitted.


Ajay Kumar Sampathirao, Grosso, Juan Manuel, Pantelis Sopasakis, Ocampo-Martinez, Carlos, Alberto Bemporad, Vicenc Puig. Water demand forecasting for the optimal operation of large-scale drinking water networks: The Barcelona Case Study. In 19th IFAC World Congress, Cape Town, South Africa, 2014.
Sampathirao, A.K., Sopasakis, P., Bemporad, A.. Decentralised hierarchical multi-rate control of large-scale drinking water networks. In 9th Int. Conf. Critical Information Infrastructures Security, volume 8985 of Lecture Notes in Computer Science (LNCS), Limassol, Cyprus, October 2014.
Sampathirao, A.K., Sopasakis, P., Bemporad, A., Patrinos, P.. Distributed solution of stochastic optimal control problems on GPUs. In 54 IEEE Conf. Decision and Control, Osaka, Japan, Dec 2015.
Sampathirao, A.K., Sopasakis, P., Bemporad, A., Patrinos, P.. Fast parallelizable scenario-based stochastic optimization. In 4th European Conference on Computational Optimization, Leuven, Belgium, September 2016.
Ajay Kumar Sampathirao, Pantelis Sopasakis, Alberto Bemporad, Panagiotis Patrinos. Proximal Limited-Memory Quasi-Newton Methods for Scenario-based Stochastic Optimal Control. In volume 50 pages 11865 - 11870, 2017. 20th IFAC World Congress.
I. Loeser, A.K. Sampathirao, S. Hofmann, J. Raisch. Fallback Strategies in Operation Control of Microgrids with Communication Failures. In accepted for IEEE Conf. Decision and Control, 2019.

Working paper

  • A.K. Sampathirao, P. Sopasakis, A. Bemporad and P. Patrinos, “Quasi-Newton scenario-based stochastic optimal control problems”
  • A. Schödl, C.A. Hans, A.K. Sampathirao, J. Raisch, “Distributed Model Predictive Secondary Voltage Control of Islanded Microgrids”


Ajay Kumar Sampathirao. Parallel methods for solving stochastic optimal control : control of drinking water networks. IMT, Dec 2016.

Open thesis

Master thesis: "Distributed Energy Management system for operational control of Microgrid."
A microgrid (MG) is a small-scale power system that clusters and manages renewable energy resources and loads within a defined geographical boundary. Microgrid has emerged as a viable architecture to tackle the challenges with high infeed of renewable energy in the future power systems. Energy management system (EMS) in the MG manages the operation control and balancing the demand with the generation. Typical EMS designs are centralised with a single unit in-charge of decision making. This approach lacks scalability, privacy and sensitive to single-point failures. This objective of this thesis is to design of a distributed EMS for operation of MG. [1]

Interested students can send an email or come to the office to discuss more about this project.

Supervised thesis

B.Yavor. Comparison of AC and Dc power flow model in microgrid. Bachelor thesis TU Berlin, Germany, 2017.


The optimisation problem resulting from scenario-based MPC is large-scale but highly structured. The objective is to develop an open-source software that can exploit the structure and suitably parallelisable for hardware like GPU that support parallel computations. In this process, we have developed an ope-source software for water management in drinking water networks.

A.K.Sampathirao, P.Sopasakis. RapidNet: open-source software for water-management.

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