PLC-based control of robots for high-performance applications

This thesis investigates open Programmable Logic Controller (PLC)-based robot control as a solution to the limitations of proprietary controllers in high-performance industrial applications. Traditional controllers restrict customization, flexibility, and real-time integration with sensors, axes, and AI. This research details the design, implementation, and quantitative performance assessment of an open PLC-based robot control architecture, demonstrating enhanced capabilities. An experimental platform was established, directly controlling a SCARA robot's motors via a PLC. This allows full customization, real-time performance via the EtherCAT protocol, advanced motion control, multi-axis synchronization, and sensor/AI integration. The dynamic parameters of the SCARA robot were identified and used for developing a digital twin for simulations, a safety layer for collision detection, and implementing low-level control strategies for accurate trajectory tracking. Experimental evaluations of model-free PID and model-based torque control were performed across various paths, trajectories, and PLC frequencies, quantifying performance improvements with model-based control and increased frequency in PLC-based controllers. The thesis also explores advanced motion planning (for anti-sloshing in liquid handling) and real-time synchronization (with a conveyor belt) within the PLC framework, demonstrating superiority over proprietary controllers- Finally, a real-world high-performance application was implemented: robotic waste sorting from a moving conveyor. This task required integration with an external camera, ResNet neural network execution directly within the PLC, and real-time conveyor synchronization. This showcases the seamless integration necessary for intelligent robotic applications achievable with PLC-based robot control. The findings confirm the transformative potential of PLC-based open control architectures for industrial robots, offering enhanced accuracy, flexibility, real-time synchronization, and seamless AI integration, unlocking new possibilities for demanding industrial applications.