This article proposes a discrete-time design for the robust control technique of uncertainty and disturbance estimator (UDE), with studies on applications to real-world systems. Despite the ease of implementation of discrete-time strategies, almost all prior work on UDE is for designing continuous-time control laws, with no general, complete research for discrete-time design. To design an appropriate discrete-time control law, a novel digital filter similar to the original analog filter for disturbance estimation is designed, a discrete-time error-based control law is derived, and a detailed stability analysis is provided. However, most real-world, physical systems are nonlinear and continuous-time in nature. Thus, the techniques of sampling and digital-analog (D/A) conversion are used, enabling the control of linear, time-invariant as well as a class of nonlinear, continuous-time systems using discrete-time UDE. The considered nonlinear system is for the phenomenon of wing-rock motion. Simulations are performed for the proposed techniques, and results indicate highly accurate stabilization and tracking performance, with excellent disturbance rejection. In particular, it is seen that the proposed control law is less sensitive to initial values of the error when compared to the original continuous-time UDE law.
\@article{padmanabhan2021discrete,title={Discrete-time design and applications of uncertainty and disturbance estimator},author={Padmanabhan, Ram and Shetty, Maithili and Chandar, TS},journal={International Journal of Robust and Nonlinear Control},year={2021},publisher={Wiley Online Library}
ICC - Oral
Continuous Control of a Robot Manipulator Using Deep Deterministic Policy Gradient
Maithili Shetty, Brunda Vishishta, Shrinidhi Choragi, Karpagavalli Subramanian and Koshy George
Deep reinforcement learning (DRL) addresses the problems that previously limited the performance of RL algorithms while working with high-dimensional state and action spaces. In this paper, we explore the deep deterministic policy gradient (DDPG) algorithm that operates over continuous action spaces. The application of reference tracking for a two-link robot manipulator (TLRM) in uncertain environments is considered. The TLRM is subjected to uncertainties such as frictional forces and external torque disturbances. In the simulation study, we compare the performance of our RL-based controller with the well-known proportional-derivative (PD) controller. Results indicate a considerable improvement in the mean square error (MSE) and variance accounted for (VAF) parameters when the RL-based controller is utilized.
\@inproceedings{ShettyDDPG,title = {Continuous Control of a Robot Manipulator Using Deep Deterministic Policy Gradient},author = {Shetty,Maithili and Vishishta, Brunda and Choragi, Shrinidhi and Subramanian, Karpagavalli and George, Koshy},booktitle = {2021 Indian Control Conference (ICC)},year={2021}}
2020
MoSICom - Oral
A Novel Approach to Design Single-Phase Cycloconverter using
SiC MOSFET and its Performance Analysis over IGBT
Maithili Shetty, Karthik K Bhat, Anoop Narayana and Melisa Miranda
Silicon Carbide (SiC) MOSFET devices exhibiting several advantages, including high blocking voltage, lower conduction losses, and lower switching losses, when compared to silicon-based devices have become commercially available, enabling their adoption into power supply products. This paper presents a novel approach to designing a cycloconverter using SiC MOSFETs as opposed to the conventional usage of IGBT. A comparative study is attempted between the two with respect to distortion and system efficiency. MATLAB/Simulink models and simulations are used to analyze the results for the above.
\@incollection{Shetty2020,title = {A novel approach to design single-phase cycloconverter using{SiC} {MOSFET} and its performance analysis over {IGBT}},booktitle = {Lecture Notes in Electrical Engineering},author = {Shetty, Maithili and Bhat, Karthik K and Narayana, Anoop andMiranda, Melisa},publisher = {Springer},pages = {285–296},series = {Lecture Notes in Electrical Engineering},year = {2020},address = {Singapore}