Weighted linearization for Increased Safety

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Concerns about trust, safety, and fault tolerance are becoming more prevalent in safety-critical systems such as autonomous robots and vehicles due to their use to accomplish specific tasks or missions under challenging conditions. Therefore, research into fault diagnosis and fault-tolerant control (FTC) is essential for enhancing the resilient autonomy and operability of robots and autonomous vehicles required by these conditions. Additionally, the nonlinearities inherent to the dynamical model of such systems contribute to the complexity of the control system, necessitating the development of new advanced analysis and design tools capable of dealing with them. In light of these demands, the Weighted linearization for Increased Safety (WINSAFE) is an innovative research project with the ambitious aim of integrating the novel weighted linearization technique into fault diagnosis and FTC algorithms. This will be the foundation and inspiration for a new generation of techniques that can significantly enhance performance and improve the stability properties of highly nonlinear systems. IDE at UiS will provide the means for developing high-quality research, which will have a strong impact on both state-of-the-art control system engineering and my future career opportunities. In this context, the Marie Skłodowska-Curie Actions (MSCA) postdoctoral fellowship will allow me to obtain invaluable knowledge about weighted linearization and modern control theory. The dissemination, exploitation, and communication activities will reach different communities, e.g., the academic and the industry ones, garnering interest for future collaborations based on positive project outcomes. In particular, the main research objectives of the project are: - Integration of the weighted linearization technique into active FTC algorithms; - Enhancement of the weighted linearization-based algorithms; - Experimental evaluation of the designed algorithms;