A high-gain observer was designed to estimate the crystal-size distribution (CSD) in batch crystallization processes. The observer is based on the discretization of population balance equations describing the evolution of the CSD using finite difference method. Due to process impurities and other batch-to-batch variations, the kinetic parameters involved in the dynamic model of the crystallization, relating primary and secondary nucleation in particular, are subject to significant variations. In order to avoid any estimation divergence, an on-line parameter identification algorithm was added to the observer.Assuming that measurements of the nuclei particles are available, the observer is shown to provide a discretized reconstruction of the entire CSD which can be used for control purposes or process supervision.

The aims of this study are to investigate muscular fatigue and to propose a new fatigue index based on the continuous wavelet transform (CWT) which is compared to the standard fatigue indexes from literature. Fatigue indexes are all based on the electrical activity of muscles (electromyogram) acquired during an electrically stimulated contraction thanks to two modules (electromyostimulation + electromyography recording) that can analyze EMG signals in real time during electromyostimulation. The extracted parameters are compared with each other and their sensitivity to noise is studied. The effect of truncation of M waves is then investigated, enlightening the robustness of the index obtained using CWT.