Nida Sheibat-Othman

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Support Vector Machines (SVM) are used for fault detection and isolation in a variable speed horizontal-axis wind turbine composed of three blades and a full converter. The SVM approach is data based and is therefore robust to process knowledge. Moreover, it is based on structural risk minimization which enhances generalization and it allows accounting for(More)
In this work, the benchmark FAST that simulates a closed-loop three-bladed wind turbine is used for fault detection and isolation. Two methods were employed to isolate faults of different types at different locations: Support vector machines (SVM) and a Kalman-like observer. SVM could isolate most faults with the used data and characteristic vectors, except(More)
A new inferential 2-step multiple input/multiple output (MIMO) model predictive control (MPC) of the particle size distribution (PSD) in emulsion polymerization processes is proposed. The bulk-like model describing the PSD is used with the material balances of initiator, radicals, monomer and surfactant. The inferential 2-step control strategy uses two(More)
In this brief, a new constrained nonlinear predictive control scheme is proposed for maximizing the production in polymerization processes. The key features of the proposed feedback strategy are its ability to rigorously handle the process constraints (input saturation, maximum allowed heat production, maximal temperature values, and rate of change) as well(More)
In this paper fault tolerant control is performed to counterbalance actuators' faults in wind turbines using model predictive control (MPC). Laguerre MPC parameterization is used in order to improve the numerical conditioning of the MPC optimization problem. Faults in the actuators for blade pitching and generator torque control are considered. For each(More)
Wind energy represents a promising renewable resource of electricity. Due to the higher complexity of modern wind turbines, advanced control becomes necessary. Multi input multi output control is known to be a good tool to account for coupling between the input and output variables, and is thus preferred in this work over decoupled single input single(More)
The difficulties encountered in chemical engineering arise from the lack of reliable and robust sensors. Several works deal with the design of software sensors in order to estimate the unavailable/non-measured variables. However the theoretical convergence of these state estimators is not often proven. This paper concerns nonlinear state estimation in a(More)
The in vivo effectiveness of biomolecules may be limited by their rapid diffusion in the body and short half-life time. Encapsulation of these biomolecules allows protecting them against degradation and ensuring a controlled release over time. In this work, the production of polyhydroxybutyrate-co-hydroxyvalerate/polyethylene glycol-based microspheres(More)
A cascade high gain observer is designed to estimate the first four leading moments of the crystal size distribution (CSD) and the mean crystal size in batch crystallization processes. The proposed observer is based on a well-known transformation of the partial differential equation describing the CSD to a set of ordinary differential equations (the method(More)