20th IMEKO TC10 Conference on "Measurement for Diagnostics, Optimization and Control to Support Competitiveness and Innovation"

Session

Session 5: Intelligent and Data-Driven Diagnostics, Optimization and Control

Session 5

29 Sept 2026, 14:00

Lisbon

Conveners

Session 5: Intelligent and Data-Driven Diagnostics, Optimization and Control: Sessions Chair: Dr. Piotr Bilski

• Piotr Bilski (Warsaw University of Technology)

Description

Sessions Chair: Dr. Piotr Bilski

14. Data-driven feedforward iterative tuning for MLPM with position-dependent nonlinearities

Li Li (Harbin Institute of Technology)

29/09/2026, 14:00

Oral presentation

To address spatial nonlinear coupling and position-dependent additive and multiplicative disturbances in Magnetically Levitated Planar Motor (MLPM) caused by decoupling mismatch, this paper proposes a data-driven position-dependent nonlinear feedforward iterative tuning method. Unlike conventional polynomial feedforward approaches, the proposed rational feedforward controller uses its...

24. Advanced Validation Methodology for KPI-Based Robotic Condition Monitoring in an Industry 4.0 Framework

Prof. Giulio D'Emilia (University of L'Aquila), antonella gaspari (Polythecnic University of Bari)

29/09/2026, 14:20

T3 - Condition monitoring and maintenance of industrial processes, plants and complex systems.

Oral presentation

In this work, a methodology is presented for the advanced validation of KPI-based condition monitoring systems applied to industrial robotics. The proposed approach is demonstrated through a test case involving an industrial robotic arm equipped with ICP accelerometers for high-fidelity vibration measurements. The acquired signals are collected by a high-speed DAQ system and processed in real...

12. Feature Selection for EDM Process Optimization in Manufacturing

Anh Tuan Hoang, Dr Zsolt Janos Viharos (Institute for Computer Science and Control (SZTAKI))

29/09/2026, 14:40

T5 - Artificial intelligence, machine learning and data science for Diagnostics, Optimization & Control.

Oral presentation

Electrical Discharge Machining (EDM) is a widely applied manufacturing process where performance is strongly influenced by multiple interacting technological parameters. This study presents a data-driven approach for analysing and reducing the dimensionality of EDM process parameters using feature selection methods. An industrial dataset containing six input parameters and time-related outputs...

29. Testing a Low Processing Methodology for Intermittent Fault Detection in Power Distribution Grids with Low Impedance Neutral

António José Arsénio Costa (LNEC)

29/09/2026, 15:00

T4 - Failure & fault detection and prognosis.

Oral presentation

The massive integration of new power
generation plants using decentralised renewable
energy resources (DER) implies an expansion of the
electrical distribution power grid with the construction
of more transmission lines and substations. With this
expansion, the probability of the occurrence of
permanent and intermittent faults will increase.
The time interval and duration of...

11. LPV Feedforward Iterative Tuning for a Cam-Driven Precision Motion Stage

Li Li (Harbin Institute of Technology)

29/09/2026, 15:20

T7 - Methods and algorithms for real-time Diagnostics, Optimization & Control.

Oral presentation

This paper proposes a data-based Linear Parameter-Varying (LPV) feedforward iterative tuning method for a cam-driven precision motion stage with position-dependent nonlinear gain. To overcome the limitations of standard Linear Time-Invariant (LTI) control method, the proposed feedforward controller is parameterized using position-velocity coupled polynomial basis functions. Embedding...