Education
Ph.D. - Indian Institute of Technology (IIT) Palakkad, Kerala (2025) [9.75 CGPA].
M.Tech. - National Institute of Technology (NIT), Warangal, Telangana (2019) [8.83 CGPA].
B.Tech. - University of Calicut, Kerala (2016) [9.30 CGPA].
Invited Reviewer
Reviewer of research papers:
Paper Reviewer for reputed conferences - Indian Control Conference (ICC), American Control Conference (ACC), Conference on Decision and Control (CDC).
Paper Reviewer for reputed journals - IEEE Transactions on Control Systems Technology, Nonlinear dynamics, ISA transactions, IEEE Transactions on Intelligent Transportation.
Work Experience
IIT Palakkad Technology IHub Foundation (IPTIF) [Feb 2025- present]
Currently, I am working as a Project Engineer at the IIT Palakkad Technology iHub Foundation, funded by the Institute's ICSR program. In this role, I am actively leading and contributing to several control-focused projects, including designing controller for an aerial manipulator to land on a dynamic target, the hardware implementation of control strategies for a Mecanum-wheeled mobile robot for warehouse application, and the Fields2Cover project involving precision control of a tractor vehicle for agricultural automation.
Indian Institute of Technology Palakkad [Jan 2020 - Jan 2025]
Teaching assistantship for the following courses:
EE5515 - Control of Nonlinear Dynamical Systems (PG, even semester).
ME1160 - Workshop practice II (UG, 2022 and 2023 batches).
EE3140 - Measurements and Instrumentation Laboratory (UG January 2021 batch).
EE4150 - Control Systems Laboratory (UG - For August 2020, 2021, and 2022 batches).
ME1160 - Electrical and Electronics Workshop (UG, 2021, 2022 and 2023 batches).
EE5060A - Control Engineering. (UG, 2023 and 2024 batches).
National Institute of Technology Warangal [July 2017 - July 2019]
Research and Teaching assistant:
I have played a pivotal role in establishing and enhancing laboratory infrastructure, designing experimental setups, and implementing advanced control techniques in the process control instrumentation Laboratory. My contributions include:
Design and Implementation of Control Systems: Developed and implemented control strategies for both SISO (Single-Input-Single-Output) and MIMO (Multiple-Input-Multiple-Output) systems, including feedforward control for temperature processes, ratio control systems, interaction analysis in a coupled tank system, PID control and system identification for level processes in coupled tanks, cascade control design for level/flow processes.
Advanced Control Applications: Data-driven model development and control implementation for spherical and conical tank processes, control of unstable systems such as an inverted pendulum, application of LQR (Linear Quadratic Regulator) and MPC (Model Predictive Control) to a coupled four-tank system.
PLC-Based Automation: Implemented programmable logic controller (PLC) solutions for bottle filling units, conveyor belt systems and level control processes.
Experimental System Identification and Control: Designed and controlled level systems for non-interacting cylindrical tanks, interacting cylindrical tanks and three-tank processes.
Data Acquisition and Integration: Leveraged standard add-on cards and remote I/O modules for real-time data acquisition and system integration.
This diverse experience has honed my expertise in designing robust control strategies, conducting system identification, and integrating cutting-edge technologies into laboratory experiments to enhance learning and research outcomes.
Research Experience
Doctoral Thesis 'Optimal Control of Robotic Systems with Mechanical and Environmental Constraints'. [Jan 2020 - Jan 2025]
In the real world, systems - be they mechanical or electrical, operate under constraints that govern their behavior. These constraints can arise from the inherent physical properties of the system or external environmental factors. Furthermore, at the dynamic level, nonholonomic systems often exhibit underactuation, where the available control inputs are insufficient to directly control all degrees of freedom. Managing such constraints, particularly in robotic systems, presents a significant challenge, as it requires the development of advanced control strategies capable of ensuring stability,precision, and constraint satisfaction. This research addresses the control of robotic systems influenced by constraints arising both from their mechanical nature and external environments. To explore the diverse characteristics and challenges of constrained robotic systems, we focus on three distinct nonlinear systems: the Autonomous Underwater Vehicle (AUV), the Wheeled Inverted Pendulum (WIP), and the Spherical Mobile Robot (SMR). Each of these systems represents a unique category of robotic systems with specific constraints and control requirements.
The first system, the AUV, operates in environments influenced by external dissipative forces. For a 2D surface vessel, underactuation introduces nonholonomic constraints. Additionally, we examined a 6 Degrees of Freedom (DoF) AUV, accounting for external forces and moments. within a coordinate framework. For these 3 DoF and 6 DoF framework, we addressed an optimal tracking problem using PMP approach in coordinate setting considering the trade-off between performance and control effort. For the 6 DoF AUV, we also employed the Lie group Pontryagin Minimum Principle (PMP) approach to develop a singularity-free control law (coordinate free setting), leveraging a technique known as left trivialization of the Hamiltonian. This addresses point stabilization and tracking control objectives.
The second system, the Wheeled Inverted Pendulum (WIP), represents a mixed constraint system with both holonomic and nonholonomic constraints. The WIP also exhibits underactuation in its shape space due to dynamic coupling between its heading and pitch dynamics. For this system, we developed a motion planning strategy combined with PMP and we also investigated an optimal trajectory tracking objective. This approach effectively addressed both mixed constraints and external environmental constraints.
The third system, the Spherical Mobile Robot (SMR), is a rolling robot with internal actuation, subjected to mechanical (nonholonomic) constraints. The configuration space for this system is SO(3) $\times \mathbb{R}^2$, which is not a Lie group, making the computation of left trivialization is particularly challenging. Thus, for this system, we employ a variational approach to derive optimal trajectories and control laws in coordinate-free setting. Here, we address the point stabilization on $\mathbb{S}^2$ using variational approach where, the process of left trivialization is not straight-forward due to the non Lie-group configuration structure of SMR system.
For the closed loop setting, we also developed and implemented through simulations a geometric adaptive tracking and stabilizing control laws in SE(3) for two cases, i.e., asymptotic as well as finite time cases through Lyapunov function control synthesis approach. We also looked at the effect of external disturbances on the dynamics of the system. The control law is validated through simulations for both cases using spiral and a more complicated trajectory (docking maneuver) for the tracking objective of a AUV system.
M.Tech Thesis 'Design of Predictive Controllers for Unstable Systems with Time Delay' [May 2018 - May 2019]
Controlling non-minimum phase systems possessing transportation lag presents a challenging problem. In this research, a novel generalized predictor control structure is proposed for controlling unstable time delay systems.
As part of the research objective, the proposed generalized predictor control structure is applied to unstable first order and second order time delay systems, unstable series cascade processes, unstable parallel cascade processes, simulation application on an unstable nonlinear Jacketed CSTR and experimental application on an inverted pendulum.
The closed loop control performances are measured quantitatively using IAE and TV measures from which enhanced performances were obtained in comparison with the recently reported methods in the literature.
B.Tech Project 'An algorithm for two class motor imagery based Brain Computer Interface (BCI)'. [Sep 2015 - April 2016]
In this work, a two-class BCI manipulated through imagination of left hand, right hand movements is implemented, inducing different spatial patterns of Event-Related Desynchronization (ERD) on mu rhythms over the sensory-motor cortex.
We made machine learning techniques to implement the algorithm. The optimized parameters and classifiers can be utilized for online control.
This paradigm facilitated two directional movement controls which could be easily applied to help the motion-disabled to operate a wheelchair, which may be extended as a future scope of this work.