PECASE : Prognosis / Diagnosis and Control: Health and Energy
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The research activities of the team are organized around work on the control of non-linear systems and on the prognosis / diagnosis based on data or techniques based on the use of dynamic models. A specificity of the team in the context of the diagnosis, is the development of activities on the prognosis systems. The applications considered are in the field of energy and health.
We will continue to develop methodologies for the reconstruction of non-measurable state variables of dynamical systems. We will also continue to focus on the class of non-linear systems at an unknown input. The objective is to generalize results of the literature in order to exploit this type of models to answer problems related to Prognosis / Diagnosis.
As part of system analysis and control, we will continue to focus on system analysis, feedback stabilization, and fault tolerant control (FTC) issues. The purpose of this type of control is to maintain the operation of the system in degraded mode despite the presence of faults and automatically adapt to the new context of the faulty process. The models considered will be nonlinear dynamic systems in the form of differential equations.
Within the PECASE team, we address issues related to processes based on renewable energy sources. For example, we consider the problem of heat pump control, tidal turbines and wind turbines. We will also focus on controlling the exchanger and compressor to improve the coefficient of performance. Also, we developed the vector fault tolerant control (FTC) with and without mechanical sensor of asynchronous and synchronous electric actuators. The objective is to establish results that are experimentally validated on the electrical systems with the platforms available in the laboratory and managed by the members of the team.
Concerning the fault tolerant control (FTC), our works are dedicated mainly to applications related to the strategic axes that are energy and health.
We address the issue of Prognosis / Diagnosis by exploring data-based methods and techniques based on dynamic models. A first theme is that of the analysis of the deteriorations in view of the prognosis of the systems. Moreover, and as part of the prognosis based on data, health index generation is a fundamental aspect. Thus, we approach this theme and our approach is based on the following three steps: reducing the size of the data, the treatment of the raw health index, then, the prognosis. Currently this approach has been used successfully by team members in an industrial project. This approach will be improved and adapted for exploitation in the field of health. It involves developing strategies for the prognosis for certain diseases, for example, diabetes.
About electrical systems, we develop diagnostic / prognostic strategies. Three types of faults will be considered: actuator faults (electrical faults, mechanical faults, etc.), power converter faults (power component faults, control signal faults, etc.) and sensor faults (electrical sensors, mechanical sensors, etc.).
In addition, we have developed fault diagnosis strategies for fuel cell systems (ie flooding, dewatering, contamination, etc.). Our current goal is to synthesize control laws that adapt to the presence of these types of faults.
The skills are homogeneous, complementary and characterize both by the use of dynamic systems and by the exploitation of data analysis techniques. In addition, all members develop methodologies and focus on various applications from energy, manufacturing and health systems.
The team is involved in a very important industrial collaboration on the topic of Diagnosis / Prognosis of production systems. As examples with STMicroelectronics group is carried out, in particular, through the MAGE investment project and the European INTEGRATE project. This collaboration is carried out through a series of theses that deal with the problematic of Diagnosis / Prognosis using real data from production
chains of STMicroelectronics.
PECASE has several platforms:
- The SUPER platform on the management of multi-source renewable energy systems.
- Two experimental platforms dedicated to electric actuators. The first platform is dedicated to the fault-tolerant control (FTC) of three-phase permanent magnet synchronous machine (PMSM) and the second platform is dedicated to FTC of the three-phase induction machine (IM) with or without mechanical sensor in the presence of single or multiple opening of switch power components of the inverter.
- An experimental platform on the drone motorization with a remote power supply.
The members of the PECASE team are in collaboration with a large number of national and international researchers. For example, collaborations are established through co-supervision of theses or national and international projects with the following universities: University of Marrakech (Morocco), Lebanese University (Lebanon), University of Rosario (Argentina), University of Washington (USA), ONERA (Salon, France), ENSIT, ENIS (Tunisia), FCLab Institute (Belfort, France), etc.
Year of production
Article dans une revue
- Zhongliang Li, Rachid Outbib, Stefan Giurgea, Daniel Hissel. Fault diagnosis for PEMFC systems in consideration of dynamic behaviors and spatial inhomogeneity. IEEE Transactions on Energy Conversion, Institute of Electrical and Electronics Engineers, 2019, pp.1-1. ⟨hal-02004082⟩
- Chen Liu, Rui Ma, Hao Bai, Zhongliang Li, Franck Gechter, et al.. FPGA-Based Real-time Simulation of High-Power Electronic System with Nonlinear IGBT Characteristics. IEEE Journal of Emerging and Selected Topics in Power Electronics, Institute of Electrical and Electronics Engineers, 2018, 7 (1), pp.41-51. ⟨10.1109/JESTPE.2018.2873157⟩. ⟨hal-02004142⟩
- Chen Liu, Rui Ma, Hao Bai, Zhongliang Li, Franck Gechter, et al.. Hybrid modeling of power electronic system for hardware-in-the-loop application. Electric Power Systems Research, Elsevier, 2018, 163, pp.502-512. ⟨10.1016/j.epsr.2018.06.018⟩. ⟨hal-02004133⟩
Communication dans un congrès
- Bruno Lawson, Khalifa Aguir, Zouhair Haddi, Tomas Fiorido, Rachid Bouchakour, et al.. Toward a Selective Detection of Ethanol by Perspiration. 2018 IEEE Sensors, Oct 2018, New Delhi, France. pp.1-4, ⟨10.1109/ICSENS.2018.8589599⟩. ⟨hal-02065763⟩
- Samia Mellah, Guillaume Graton, El Mostafa El Adel, Mustapha Ouladsine, Alain Planchais. On fault detection and isolation applied on unicycle mobile robot sensors and actuators. 2018 7th International conference on Systems and Control (ICSC), Oct 2018, Valencia, Spain. pp.148-153. ⟨hal-02003348⟩
- Zouhair Haddi, Bouchra Ananou, Youssef Trardi, Jean-François Pons, Stephane Delliaux, et al.. An Efficient Pattern Recognition Kernel-Based Method for Atrial Fibrillation Diagnosis. 2018 Computing in Cardiology Conference, Sep 2018, MAASTRICHT, Netherlands. ⟨10.22489/CinC.2018.090⟩. ⟨hal-02065765⟩
- Taki Eddine Korabi, Guillaume Graton, El Mostafa El Adel, Mustapha Ouladsine, Jacques Pinaton. A Bayesian indicator for Run-to-Run performance assessment in semiconductor manufacturing. 2018 14th Conference on Ph.D. Research in Microelectronics and Electronics (PRIME), Jul 2018, Prague, France. ⟨10.1109/PRIME.2018.8430365⟩. ⟨hal-01893409⟩
- Y. Trardi, B. Ananou, Z. Haddi, M. Ouladsine. A Novel Method to Identify Relevant Features for Automatic Detection of Atrial Fibrillation. 2018 26th Mediterranean Conference on Control and Automation (MED), Jun 2018, Zadar, France. ⟨10.1109/MED.2018.8442479⟩. ⟨hal-01893136⟩
- Nk M'Sirdi, K Frifita, E Baghaz, A Naamane, M Boussak. State Space Models for Power SiC MOSFET. International Conference on Electronic Engineering and Renewable Energy (ICEERE’2018), Apr 2018, Oujda, Morocco. ⟨hal-01779823⟩
- K Frifita, Nk M'Sirdi, A Baghaz, M Naamane, M Boussak. Electro-thermal Model of a Silicon Carbide Power MOSFET. International Conference on Electronic Engineering and Renewable Energy (ICEERE’2018), Apr 2018, Oujda, Morocco. ⟨hal-01779825⟩
- Y. Trardi, B. Ananou, Z. Haddi, M. Ouladsine. Multi-Dynamics Analysis of QRS Complex for Atrial Fibrillation Diagnosis. 2018 5th International Conference on Control, Decision and Information Technologies (CoDIT), Apr 2018, Thessaloniki, France. ⟨10.1109/CoDIT.2018.8394935⟩. ⟨hal-01893141⟩