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Introduction:: In this paper, a robust sliding mode controller is developed to control an orthosis used for rehabilitation of lower limb. Materials and Methods:: The orthosis is defined as a mechanical device intended to physically assist a human subject for the realization of his movements. It should be adapted to the human morphology, interacting in harmony with its movements, and providing the necessary efforts along the limbs to which it is attached. Results:: The application of the sliding mode control to the Shank-orthosis system shows satisfactory dynamic response and tracking performances. Conclusion:: In fact, position tracking and speed tracking errors are very small. The sliding mode controller effectively absorbs disturbance and parametric variations, hence the efficiency and robustness of our applied control.

The increasing of penetration of wind energy conversion system to produce electricity lead to improve the choice of the operational control strategies. This paper deals with the modeling and control design of wind turbine using Takagi-Sugeno techniques. Due to the uncertainty wind speed measured through the anemometer, a Takagi-Sugeno observer is designed to estimate the effective wind speed. The nonlinear behavior of the wind turbine is driven through the Takagi-Sugeno fuzzy model approach based on Taylor linearized model. In order to maximize the extracted energy from the wind turbine conversion system, T-S observer combined with H-infinity performance is considered. The controller design based on Linear Matrix Inequalities (LMI) is used to ensure the stability and the robustness of the model. The effectiveness of the proposed control is tested in terms of wind turbine rotational speed relative to the estimated wind speed.

In wind conversion system, Doubly Fed Induction Generator is widely used. The main objective of the control of the wind system in partial load power production is to require the maximum efficiency power flow transfer to the grid. Vector control strategy is well used to achieve this purpose where the conventional control design employs PI regulators for the adjusting of the currents loops. However these regulators are sensitive to parameters variations that results the degradation in the performance of the controlling system. This paper deals with an alternative controller for the DFIG generator based on internal model control strategy which the controller selected is an approximate inverse of the model. The design control was done with 5MW NREL DFIG using SimWindFarm toolbox Matlab/Simulink and compared with the classical proportional integral control to discuss the performance in terms of tracking references and sensitivity to parameters variations.

With a large increase in wind power generation, the direct driven Permanent Magnet Synchronous Generator is the most promising technology for variable speed operation and it also fulfills the grid requirements with high efficiency. This paper studies and compares conventional based on PI controller and proposed control technique for a direct driven PMSG wind turbine. The generator model is established in the Park synchronous rotating d-q reference frame. To achieve maximum power capture, the aeroturbine is controlled through Maximum Power Point Tracking (MPPT) while the PMSG control is treated through field orientation where the two currents control loops are regulated. A proposed direct-current based d-q vector control design is designed by the integration of the Internal Model Controller. Then an optimal control is developed for integrated control of PMSG power optimization and Voltage Source Converter control. The design system was done using SimWindFarm Matlab/Simulink toolbox to evaluate the performance of conventional and proposed technique control of PMSG wind turbine. The analysis, simulation results prove the effectiveness and robustness of the proposed control strategy.

International audience; Background. Olive oils (OOs) show high chemical variability due to several factors of genetic, environmental and anthropic types. Genetic and environmental factors are responsible for natural compositions and polymorphic diversification resulting in different varietal patterns and phenotypes. Anthropic factors, however, are at the origin of different blends' preparation leading to normative, labelled or adulterated commercial products. Control of complex OO samples requires their (i) characterization by specific markers; (ii) authentication by fingerprint patterns; and (iii) monitoring by traceability analysis.Methods. These quality control and management aims require the use of several multivariate statistical tools: specificity highlighting requires ordination methods; authentication checking calls for classification and pattern recognition methods; traceability analysis implies the use of network-based approaches able to separate or extract mixed information and memorized signals from complex matrices. Results. This chapter presents a review of different chemometrics methods applied for the control of OO variability from metabolic and physical-chemical measured characteristics. The different chemometrics methods are illustrated by different study cases on monovarietal and blended OO originated from different countries.Conclusion. Chemometrics tools offer multiple ways for quantitative evaluations and qualitative control of complex chemical variability of OO in relation to several intrinsic and extrinsic factors.