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Mr. Anil B
Research Scholar
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Phd Supervisor

Educational Qualification:

  • Master of Technology (M.Tech) from National Institute of Technology, Warangal.

          - Thesis title : Design of predictive controllers for unstable time delay systems.

          -  Description : Controlling non-minimum phase systems with measurement noise possessing transportation lag presents a challenging problem. In this research, a novel generalized predictor control structure is proposed for controlling unstable time delay systems affected by measurement noise. 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 for both nominal as well as perturbed models, from which enhanced performances were obtained in comparison with the recently reported methods in the literature. With our proposed control scheme, response of controller under the influence of measurement noise also showed significant performances compared with recent literature results.

  • Bachelor of Technology (B.Tech)  from  University of Calicut (NSS College of Engineering, Palakkad).

          - Project Title : An algorithm for two class motor imagery based Brain Computer Interface (BCI).

         -  Description : A motor imagery based brain-computer interface (BCI) translates the subject’s motor intention into a control signal through real-time detection of characteristic EEG spatial distributions corresponding to motor imagination of different body parts. 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 use of various 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.

Work Experience:

  • Svaya Robotics PVT Limited, Hyderabad, Telangana.

Course works completed:

  1. EE5513  - Control of Nonlinear Dynamical Systems.
  2. ME5613 - Wheeled Mobile Robots.
  3. CS5512 - Machine Learning.
  4. EE5007 - Linear Algebra for Engineers.
  5. EE5022 - Synthesis of Control.
  6. EE5521 - Optimal Control.

External Courses and webinars undertaken:

  1. Constrained Discrete Optimal Control on Lie Groups (IGSC2021-M09) - Organized by European Embedded Control Institute.
  2. Sparsity Methods for System and Control - Organized by IIT Bombay SysCon group.
  3. Geometric Optimal Control  course - As a part of Lecture Series on Learning and Control by Prof. Ravi Banavar.
  4. Lung Ultrasound Imaging for COVID-19:From Physics to Neural Network - Organized by IEEE Student Branch of NITT.
  5. Marine Robotics courseOrganized by IIT Palakkad.

Control design strategies for constrained systems.


Teaching Assistantship:

EE5515: Control of Nonlinear Dynamical Systems (PG, even semester).

ME1160: Workshop practice II (UG).

EE3140: Measurements and Instrumentation Laboratory (UG).

EE4150: Control Systems Laboratory (UG - August 2020 batch &  August 2021 batch).

ME1160: Electrical and Electronics Workshop (UG).



Research Area
Nonlinear and Geometric optimal control
Additional Information
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