Research Activities
I aim to design safe control strategies for systems in the presence of uncertainties while guaranteeing desired performance.
Adaptive Model Predictive Control
I focus on control of constrained systems in the presence of uncertainty and aim to explore and combine the domains of Adaptive Control/Learning based Control with Model Predictive Control.
My main objective is to develop theory as well as control algorithms for safety critical applications, that can address the practically relevant problems (such as presence of model uncertainty and operational constraints) associated with real-time systems.
Robust Motion Planning
I am currently working on robust motion planning where I am developing improved algorithms for motion planning under uncertainty for autonomous systems. The aim is to develop algorithms that better maintains safety and performance also in cases when non-negligible disturbances and model errors are present.
My objective is to investigate parameterized robust primitives, real-time optimization as an integrated part of the planning, learning from previously visited environments and from other agents, and to use high-performance computations on clusters to solve more advanced problem formulations.
Publications
Journals
1. A. Dhar and S. Bhasin, ‘Indirect Adaptive MPC for Discrete-time LTI system with Parametric Uncertainty,” IEEE Transactions on Automatic Control, 2021, DOI-10.1109/TAC.2021.3050446.
Conferences
1. A. Dhar and S. Bhasin, “Multi-model Indirect Adaptive MPC,” 59th IEEE Conference on Decision on Control (CDC), Jeju Island, South Korea, 2020, pp. 1460–1465.
2. A. Dhar and S. Bhasin, “Indirect Adaptive MPC for Discrete-time LTI system with Robust Constraint Satisfaction,” American Control Conference (ACC), Denver, USA, 2020, pp. 2407–2412.
3. A. Dhar and S. Bhasin, “Tube based Adaptive Model Predictive Control,” 58th IEEE Conference on Decision on Control (CDC), Nice, France, 2019, pp. 451–456.
4. A. Dhar and S. Bhasin, “Novel Adaptive MPC Design for Uncertain MIMO Discrete-time LTI Systems with Input Constraints,” European Control Conference (ECC), Limassol, Cyprus, 2018, pp. 319–324.
5. A. Dhar and S. Bhasin, “Adaptive MPC for Uncertain DiscreteTime LTI MIMO Systems with Incremental Input Constraints,” International Federation of Automatic Control-PapersOnLine, vol. - 51, issue - 1, 2018, pp. 329–334.
6. S. Sen, S. Chakraborty, A. Dhar, A. Shutradhar, “Two-stage adaptive sliding-mode controller for vehicle yaw stability using differential ABS”, IEEE Conference on Control, Measurement and Instrumentation (CMI), Calcutta, India, 2016, pp. 31–35.
7. A. Dhar, A. Sengupta, “Sliding mode control algorithm with adaptive gain and implementation on inverted pendulum system”, IET Digital Library, 2015, pp. 2 (6.)-2 (6.).
