no code implementations • 31 Oct 2023 • Farhad Ghanipoor, Carlos Murguia, Peyman Mohajerin Esfahani, Nathan van de Wouw
We propose a methodology to extend the dynamics of an LTI (without uncertainty) with an uncertainty model, based on measured data, to improve the predictive capacity of the model in the input-output sense.
no code implementations • 23 May 2023 • Farhad Ghanipoor, Carlos Murguia, Peyman Mohajerin Esfahani, Nathan van de Wouw
We provide sufficient conditions that guarantee stability of the estimation error dynamics: firstly, asymptotic stability (i. e., perfect fault estimation) in the absence of perturbations induced by fault model mismatch (mismatch between internal, ultralocal model for the fault and the actual fault characteristics), uncertainty, external disturbances, and measurement noise and, secondly, Input-to-State Stability (ISS) of the estimation error dynamics is guaranteed in the presence of these perturbations.
no code implementations • 11 Nov 2022 • Farhad Ghanipoor, Carlos Murguia, Peyman Mohajerin Esfahani, Nathan van de Wouw
The proposed method augments the system dynamics with an approximated internal linear model of the combined contribution of known nonlinearities and unknown faults -- leading to an approximated linear model in the augmented state.
no code implementations • 4 Apr 2022 • Farhad Ghanipoor, Carlos Murguia, Peyman Mohajerin Esfahani, Nathan van de Wouw
In this paper, we present a methodology for actuator and sensor fault estimation in nonlinear systems.
