Photo: Noor Alsayed / Pixelonic Studio
In his doctoral dissertation, MSc (Tech) Essam Elsaed developed a high-flow digital flow control unit with performance comparable to commercially available high-flow control valves, while maintaining fast response and requiring lower control pressure. The second major contribution was a learning-based valve-timing approach that adapts valve switching to operating conditions to mitigate pressure spikes, with the work progressing from modeling and simulation to online training and testing directly on a hydraulic test rig. The results can benefit manufacturers and users of industrial, construction, mining, and autonomous mobile machines by improving performance, reliability, and energy efficiency.
The doctoral dissertation of MSc (Tech) Essam Elsaed in the field of Automation Technology and Mechanical Engineering titled Using a Neural Network Controller to Minimize the Pressure Peaks in Binary Coded Digital Valve Systems will be publicly examined at the Faculty of Engineering and Natural Sciences at Tampere University on Friday 18 September 2026.
The Opponent will be Professor Liselott Ericson from Linköping University, Sweden. The Custos will be Professor Matti Linjama from Tampere University.