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Intelligent Cruise Controller

  • Developed a velocity and headway controller using LQR (PID) with SIMULINK and state observer to maintain the speed and a headway distance for bumpless transfer, and maintained 2% settling time in 22 sec

  • Modelled a safety system using a Discrete controller with a Stateflow model 2021 for a vehicle – seamless switches between the two controllers and ensures a safe stopping distance from the lead vehicle, conforming to the 3-second rule.

2D LiDAR-based goal-to-goal navigation of a scaled autonomous vehicle |HIL, ROS/Python

  • Developed and implemented a mini-project concept to support a graduate-level course deployment using ROS.

  • Deployed ROS-based autonomous navigation technology using computer vision to detect signs, A* algorithm for path planning, and PID control on an approaching goal position collision avoidance.

  • Created a 2D space map for scaled vehicle navigation using the Potential field method with an adaptive pure pursuit controller with Dynamic window approach collision avoidance for vehicle local planning

Path Planning and Navigation using Map-based localization | Monte Carlo localization

  •  Implemented Potential field–based path planning algorithm (Dijkstra’s) by developing Python script for turtlebot3 to travel from starting point to the goal point by avoiding the cylindrical obstacle.

  • A robot is assumed at (0,0) for which a map is generated of the environment using Adaptive Monte Carlo localization and travels in the environment on the defined path by avoiding the cylindrical obstacle.

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Develop of Active Suspension System | MATLAB Simulation / LQR                                                                           

  • Designed an Active and Passive suspension controller to yield a zero steady-state error under 1.65 sec for four inputs i.e., Ramp, Random, Sinusoidal waveform, and Rectified sine.

  • Implemented LQG (Observer + LQR) for estimating state and feedback estimated states by LQG to state feedback controller for generating control input force for active suspension and validated using different test cases

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Simulated Performance Validation of Hybrid Electric Vehicles | HEV Powertrain                                                    

  • Modified the model to perform tests on various EVs such as the Ford F150 hybrid, Tesla Model 3, and Tesla Model S Plaid.

  • Validated a Hybrid Electric Vehicle using Simscape/Simulation with a battery and IC engine coupled to the drivetrain.

  • Developed and configured the RP controls software for vehicle propulsion systems.

Close Loop Feedback System design

  • Design a Matlab model with specific PID gains to read oscillometer 

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