2023 |
Ounis, Walid; Chetoui, Manel; Najar, Salheddine; Aoun, Mohamed Programmable analogue fractional controller realization Conférence 2023. Résumé | Liens | BibTeX | Étiquettes: Analog circuits, Continuous time systems, Controllers, Digital potentiometer, First order, First order low-pass filter, Fractional integrators, Fractional-order controllers, Higher order dynamics systems, Low pass filters, Low-pass filters, Operational amplifiers, Potentiometers (electric measuring instruments), Programmable analog circuit, Programmable analogs, Real- time, Signal processing, Timing circuits @conference{Ounis2023b,A fractional-order controller is an infinite-memory system. It is described by a continuous time irrational transfer function. Its realization is a delicate problem especially when its parameters are real time tunable. This paper presents a real-time programmable analogue fractional controller implementation. The controller is based on a sum of a novel real-time programmable analogue first-order low-pass filter. The signal within the circuit remains analogue and is not converted into discrete values. Real-time adjustments are made using digital potentiometers and operational amplifiers. The proposed first-order low-pass filter offers several advantages. In particular, the time constant and DC gain are independently adjusted without relying on the ohmic value of digital potentiometers. The time constant and DC gain depend on the resolution of the digital potentiometers. The high resolution of the digital potentiometer enables the circuit to achieve a wide bandwidth and allows for the use of small capacitors at lower frequencies. The proposed real-time programmable analogue fractional controller is experimented to achieve a fractional integrator. The circuit yields good similarity between theoretical simulations and experimental measurements. © 2023 IEEE. |
2019 |
Achnib, Asma; Airimitoaie, Tudor-Bogdan; Lanusse, Patrick; Abrashov, Sergey; Aoun, Mohamed; Chetoui, Manel Discrete-time robust control with an anticipative action for preview systems Article de journal Dans: Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, vol. 141, no. 3, 2019, (Cited by: 8; All Open Access, Green Open Access). Résumé | Liens | BibTeX | Étiquettes: Closed loop systems, Control methodology, Controllers, Digital control systems, Discrete – time systems, Discrete time control systems, Feedback control, Feedback controller, Feedforward filters, Leveling (machinery), Model uncertainties, Motion control, Reference signals, Robust control, Robust controller design, Robust feedback controllers, Robustness (control systems), Signal processing, Uncertainty analysis, Water tanks @article{Achnib2019c,A discrete-time robust controller design method is proposed for optimal tracking of future references in preview systems. In the context of preview systems, it is supposed that future values of the reference signal are available a number of time steps ahead. The objective is to design a control algorithm that minimizes a quadratic error between the reference and the output of the system and at the same time achieves a good level of the control signal. The proposed solution combines a robust feedback controller with a feedforward anticipative filter. The feedback controller’s purpose is to assure robustness of the closed-loop system to model uncertainties. Any robust control methodology can be used (such as μ-synthesis, qft, or crone control). The focus of this paper will be on the design of the feedforward action in order to introduce the anticipative effect with respect to known future values of the reference signal without hindering the robustness achieved through the feedback controller. As such, the model uncertainties are taken into account also in the design of the feedforward anticipative filter. The proposed solution is validated in simulation and on an experimental water tank level control system. © 2019 American Society of Mechanical Engineers (ASME). All rights reserved. |
2014 |
Chetoui, Manel; Thomassin, Magalie; Malti, Rachid; Aoun, Mohamed; Abdelkrim, Mohamed Naceur 2014, (Cited by: 0). Résumé | Liens | BibTeX | Étiquettes: Additive noise, Additives, commensurate order, Continuous time systems, Continuous-time, Differential equations, Electronic systems, Errors in variables, Fourth-order cumulants, Fractional differentiation, Higher order statistics, Identification (control systems), Nonlinear programming, Religious buildings, Signal processing @conference{Chetoui2014b,This paper considers the problem of identifying continuous-time fractional systems from noisy input/output measurements. Firstly, the differentiation orders are fixed and the differential equation coefficients are estimated using an estimator based on Higher-Order Statistics: fractional fourth-order cumulants based least squares (ffocls). Then, the commensurate order is estimated along with the differential equation coefficients using a non linear optimization technique combined to the ffocls algorithm (co-ffocls). Under some assumptions on the distributional properties of additive noises and the noise-free input signals, the developed estimators give consistent results. Hence, the noise-free input signal is assumed to be non gaussian, whereas the additive noises are assumed to be gaussian. The performances of the developed algorithms are assessed through a practical application for modeling a real electronic system. © 2014 IEEE. |
Chetoui, Manel; Thomassin, Magalie; Malti, Rachid; Aoun, Mohamed; Abdelkrim, Mohamed Naceur 2014, (Cited by: 0). Résumé | Liens | BibTeX | Étiquettes: Additive noise, Additives, commensurate order, Continuous time systems, Continuous-time, Differential equations, Electronic systems, Errors in variables, Fourth-order cumulants, Fractional differentiation, Higher order statistics, Identification (control systems), Nonlinear programming, Religious buildings, Signal processing @conference{Chetoui2014,This paper considers the problem of identifying continuous-time fractional systems from noisy input/output measurements. Firstly, the differentiation orders are fixed and the differential equation coefficients are estimated using an estimator based on Higher-Order Statistics: fractional fourth-order cumulants based least squares (ffocls). Then, the commensurate order is estimated along with the differential equation coefficients using a non linear optimization technique combined to the ffocls algorithm (co-ffocls). Under some assumptions on the distributional properties of additive noises and the noise-free input signals, the developed estimators give consistent results. Hence, the noise-free input signal is assumed to be non gaussian, whereas the additive noises are assumed to be gaussian. The performances of the developed algorithms are assessed through a practical application for modeling a real electronic system. © 2014 IEEE. |
2009 |
Abdelhamid, Moufida; Aoun, Mohamed; Najar, Slaheddine; Abdelhamid, Mohamed Naceur Discrete fractional Kalman filter Conférence vol. 2, no. PART 1, 2009, (Cited by: 20; All Open Access, Bronze Open Access). Résumé | Liens | BibTeX | Étiquettes: Algorithms, Discrete time control systems, Discrete-time Kalman filters, Fractional differentiation, Fractional Kalman filter, Fractional kalman filters, Fractional systems, Intelligent control, Kalman filters, Linear state estimation, Numerical example, Signal processing, State estimation @conference{Abdelhamid2009b,This paper presents a generalization of the classical discrete time Kalman filter algorithm to the case of the fractional systems. Motivations for the use of this filter are given and the algorithm is detailed. The document also shows a simple numerical example of linear state estimation. Copyright © 2007 International Federation of Automatic Control. |
Abdelhamid, Moufida; Aoun, Mohamed; Najar, Slaheddine; Abdelhamid, Mohamed Naceur Discrete fractional Kalman filter Conférence vol. 2, no. PART 1, 2009, (Cited by: 20; All Open Access, Bronze Open Access). Résumé | Liens | BibTeX | Étiquettes: Algorithms, Discrete time control systems, Discrete-time Kalman filters, Fractional differentiation, Fractional Kalman filter, Fractional kalman filters, Fractional systems, Intelligent control, Kalman filters, Linear state estimation, Numerical example, Signal processing, State estimation @conference{Abdelhamid2009,This paper presents a generalization of the classical discrete time Kalman filter algorithm to the case of the fractional systems. Motivations for the use of this filter are given and the algorithm is detailed. The document also shows a simple numerical example of linear state estimation. Copyright © 2007 International Federation of Automatic Control. |
Publications
2023 |
Programmable analogue fractional controller realization Conférence 2023. |
2019 |
Discrete-time robust control with an anticipative action for preview systems Article de journal Dans: Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, vol. 141, no. 3, 2019, (Cited by: 8; All Open Access, Green Open Access). |
2014 |
2014, (Cited by: 0). |
2014, (Cited by: 0). |
2009 |
Discrete fractional Kalman filter Conférence vol. 2, no. PART 1, 2009, (Cited by: 20; All Open Access, Bronze Open Access). |
Discrete fractional Kalman filter Conférence vol. 2, no. PART 1, 2009, (Cited by: 20; All Open Access, Bronze Open Access). |