This paper presents an observer-based fault reconstruction method for PEM fuel cells. This method extends the results of a class of nonlinear uncertain systems with Lipschitz nonlinearities. An adaptive-gain second-order sliding mode (SOSM) observer is developed for observing the system states, where the adaptive law estimates the uncertain parameters. The inherent equivalent output error injection feature of SOSM algorithm is then used to reconstruct the fault signal. The performance of the proposed observer is validated through a hardware-in-loop emulator. The experimental results illustrate the feasibility and effectiveness of the proposed approach for application to fuel cell air-feed systems.
In this paper, a novel adaptive-gain, Second Order Sliding Mode (SOSM) observer for multi-cell converters is designed by considering it as a type of hybrid system. The objective is to reduce the number of voltage sensors by estimating the capacitor voltages from only measurements of the load current. The proposed observer is proven to be robust in the presence of perturbations with unknown boundaries. However, the states of the system are only partially observable based on the observability matrix rank condition. Because its observability depends upon the switching control signals, a recent concept known as Z(T N )-observability, which can be used to analyze the observability of hybrid systems, is used to address the switching behavior. Under certain conditions of the switching sequences, the voltage across each capacitor becomes observable. Simulation results and comparisons with a Luenberger switched observer demonstrate the effectiveness and the robustness of the proposed observer with respect to output measurement noise and system uncertainties (load variations).
In this paper, we present a generalization of the supertwisting algorithm for perturbed chains of integrators of arbitrary order. This Higher Order Super-Twisting (HOST) controller is homogeneous with respect to a family of dilations and is continuous. It is built as a dynamic controller (with respect to the state variable of the chain of integrators) and the convergence analysis is performed by the use of a homogeneous strict Lyapunov function which is explicitly constructed. The effectiveness of the controller is finally illustrated with simulations for a chain of integrators of order four, first pure then perturbed, where we compare the performances of two HOST controllers.
In this paper, a variable gain super-twisting algorithm based on a barrier function is proposed for a class of first order disturbed systems with uncertain control coefficient and whose disturbances derivatives are bounded but they are unknown. The specific feature of this algorithm is that it can ensure the convergence of the output variable and maintain it in a predefined neighborhood of zero independent of the upper bound of the disturbances derivatives. Moreover, thanks to the structure of the barrier function, it forces the gain to decrease together with the output variable which yields the non-overestimation of the control gain.
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