Projects

The rapid advancement of artificial intelligence (AI) and machine learning (ML) has significantly transformed various fields, particularly process control. Traditionally reliant on human capabilities, these areas now benefit from technologies enabling machines to perform tasks autonomously, thereby enhancing the efficiency and effectiveness of control systems. This study explores the feasibility Read more…

In today’s rapidly advancing technological landscape, home automation has become more accessible than ever before. An increasing number of devices are designed to automate, protect, and monitor homes and offices, making it possible for many people to implement a smart home system. These systems can remotely control HVAC systems, integrate Read more…

In this semestral project, we delved into the world of Model Predictive Control (MPC). MPC is used in various applications such as robotics and process control, due to its ability to handle multi-variable control problems with constraints. This semester, we specifically looked at two possible ways the MPC can be Read more…

We’re excited to announce our collaboration with the University of Edinburgh on an innovative project called Remote Laboratories. This initiative promises to revolutionize the way students engage with laboratory experiments and learning. Remote Labs allow students to connect to real devices from the comfort of their homes using just a Read more…

In modern medicine and pharmaceutical research, molecular docking plays a key role in the identification of potential drugs. This process allows scientists to simulate interactions between small molecules (ligands) and target proteins, which helps predict how effective these molecules might be as drugs. Traditional docking methods often involve complicated and Read more…

In the realm of modern agriculture, ensuring optimal growing conditions is crucial for maximizing yield and quality. This challenge is particularly pronounced in greenhouse environments where factors such as temperature, humidity, and CO2 levels must be meticulously controlled. Traditional control systems like Proportional-Integral-Derivative (PID) controllers have been the go-to for Read more…

In this semestral project, we identified and controlled a device named Flexy, which represents a simple dynamical single-input single-output (SISO) system. The control input is a fan speed and the controlled output is a flex bend sensor. (An increase in a fan speed correlates with a greater degree of flex Read more…

In today’s data-driven world, precise decision-making hinges on accurate data analysis. However, anomalies—unusual data points that differ significantly from the rest of the dataset—can still arise, posing challenges to this process. Anomaly detection, which identifies these outliers, and root cause analysis, which investigates their origins, are essential for maintaining data Read more…

Model Predictive Control (MPC) is a sophisticated technique that optimizes complex processes to achieve optimal performance, taking into account economic, environmental, and energy efficiency factors. To program an MPC controller, we require a mathematical model that describes the system’s behavior, an objective function, and constraints. While the MPT Toolbox offers Read more…