PhD – Fault Diagnosis and Fault-Tolerant Control of LPV Systems Université de Lorraine in France

This PhD position at Université de Lorraine focuses on advanced research in fault diagnosis and fault-tolerant control (FTC) for linear parameter varying (LPV) systems. The project addresses the critical challenge of extending diagnostic and FTC tools from the linear to the nonlinear framework, which is essential for accurately modeling and controlling complex engineering processes. LPV, polytopic, and Takagi-Sugeno (TS) models are central to this research, enabling the representation of a wide range of nonlinear systems using structures similar to linear models or sets of linear submodels.

The research will explore the influence of different types of faults—additive and parametric—on system performance and control strategies. Faults may arise from measurement corruption, transmission defects, actuator saturation, and other sources. The project aims to develop new methods for fault detection and isolation, particularly in the presence of actuator saturations and state constraints, using advanced mathematical tools such as linear matrix inequalities (LMI) and optimization techniques.

A key research direction is to move beyond traditional observer-based diagnostic structures, investigating alternative approaches based on available input and output signals. The use of coprime factorization for diagnosis and FTC in nonlinear systems will be considered, building on techniques previously applied in linear frameworks. The project will also integrate constraints on state variables to ensure the validity of model representations and improve the robustness of diagnostic and control modules.

The PhD will be conducted within the CRAN laboratory at Université de Lorraine, offering access to a vibrant research environment and expertise in control systems engineering and applied mathematics. The position is funded through a doctoral contract, with competitive selection, and provides a salary for the duration of the PhD. Applicants should have a strong background in automatic control, applied mathematics, and optimization, with experience in nonlinear systems and fault diagnosis techniques considered an asset.

The application deadline is March 21, 2026. Interested candidates should apply online via the ABG portal, submitting their CV, academic transcripts, and a motivation letter. The PhD is expected to start on October 1, 2026. For further information about the research group, visit the CRAN website.