The Centre for Staff Development, KPR Institute of Engineering and Technology, organized a hands-on training programme titled “MATLAB for Collaborative Research” on 1 August 2026 at the HPC Laboratory. The session was facilitated by Dr. M. Prakash, Assistant Professor, Engineering Mathematics. The programme was designed to strengthen participants’ practical knowledge of MATLAB and Simulink and demonstrate their applications in solving interdisciplinary engineering and research problems.
Dr. M. Prakash conducted the programme in a highly interactive and participant-centred manner. Rather than limiting the session to theoretical explanations or software demonstrations, he encouraged active involvement through collaborative, problem-based learning. The participants were divided into two major groups based on their disciplinary background and research interests. Each group was provided with a structured workbook containing the problem statement, mathematical equations, team responsibilities, simulation steps, and expected outcomes. The session was fully laboratory-based and integrated MATLAB programming with Simulink modelling, followed by group-wise demonstrations and discussions.
Our group worked on the planar quadrotor stabilization and trajectory-tracking project. The activity introduced us to the fundamental challenge of controlling a drone, which is naturally unstable without an active feedback mechanism. The project required us to understand the equations governing the horizontal motion, vertical motion, and angular rotation of the quadrotor. Using these mathematical relations, we developed a simplified two-dimensional drone model in Simulink. The model included thrust inputs, integrator blocks, feedback loops, scopes, and controller elements to represent and monitor the dynamic response of the drone.
A major learning component of the project was the implementation of a feedback controller to stabilize the drone after an initial disturbance. We observed the simulated response, adjusted the controller parameters, and examined how the drone returned to a stable hovering position. The next stage involved providing a trajectory command and tuning the controller so that the drone could follow the assigned path. MATLAB coding was also used to extract the simulation data and generate a visual representation of the drone’s motion, thrust direction, orientation, and trajectory. Thus, the activity provided valuable exposure to both programming and graphical modelling environments.
The collaborative nature of the activity encouraged participants from different disciplines to contribute their expertise in mathematical modelling, physical interpretation, Simulink development, coding, visualization, and result analysis. It improved our understanding of how complex engineering systems can be converted into mathematical models, simulated under different conditions, and controlled using suitable feedback mechanisms. The final demonstration and discussion also helped participants interpret the results and communicate their observations effectively.
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