Fault Detection Methods Suitable for Automotive Applications in Proton Exchange Fuel Cells

The fault conditions degrade the performance of proton exchange fuel cells and reduce their useful life. The prolonged existence of a fault condition can permanently damage the fuel cell. This paper proposes four methods for fault detection and fault type isolation. These methods were based on the coefficient of variance, ratios of change in output power to change in voltage and change in output voltage to the change in current, fuzzy membership values and Euclidian distance, and wavelet transform. These methods are non-invasive to the fuel cell and involve non-destructive testing. These methods were experimentally validated

Robust fault detection and isolation based on zonotopic unknown input observers for discrete-time descriptor systems

In this paper, we propose a robust fault detection and isolation (FDI) strategy based on zonotopic unknown input observers (UIOs) for discrete-time descriptor linear time-varying (LTV) systems subject to uncertainties and additive actuator faults. System uncertainties including state disturbances and measurement noise are unknown but bounded by predefined zonotopes. The uncertain state estimations and constructed residuals for robust FDI are propagated in a sequence of zonotopes. Based on a defined performance criterion, the fault detection (FD) observer gain is designed to be robust against uncertainties and meanwhile sensitive to faults. The explicit computational method for the FD observer gain is derived. In addition to include fault isolation, a bank of zonotopic UIOs are employed. Finally, we apply the proposed method into two case studies to show its effectiveness.Peer ReviewedPostprint (published version

A novel adaptive command-filtered backstepping sliding mode control for PV grid-connected system with energy storage

In order to solve the problems of power fluctuation in the photovoltaic (PV) grid-connected system and the nonlinearity in the model of inverters, a projection-based adaptive backstepping sliding mode controller with command-filter is designed in the system to adjust the DC-link voltage and the AC side current in the PV gridconnected system. Firstly, the mathematical model of the inverter in PV system is established, then backstepping control method is applied to control it, and the command filter is added to the controller to eliminate the differential expansion of the backstepping controller. Furthermore, the adaptive law based on Lyapunov stability theory is designed to estimate the uncertain parameters in the grid-connected inverter. A projection algorithm is introduced into the adaptive controller due to the demand of guaranteeing the bounded estimated value. Additionally, a sliding mode controller is increased to improve its robustness in this system. Considering the influence of irradiation and temperature changes, a battery energy storage system (BESS) is applied on the DC side to suppress the fluctuation of the output power of the PV system. Finally, the simulation results demonstrate that the presented strategy can control precisely the grid-connected inverter

Robust Fault Detection and Estimation in Nonlinear Systems with Unknown Constant Time-Delays

This paper studies the problem of fault detection and estimation in nonlinear time-delayed systems with unknown inputs, where the time-delays are supposed to be constant but unknown. A new fault detection filter, which can estimate online the time-delays, is first introduced. Then, a reference residual model is proposed to formulate the robust fault detection filter design problem as an H∞ model-matching problem. Furthermore, by a novel robust adaptive fault estimation algorithm, the classical assumption that the time derivative of the output error should be known is removed. In addition, applying a robust H∞ optimization control technique, sufficient conditions for the existence of the fault detection filter (FDF) are derived in terms of linear matrix inequality (LMI). Finally, simulation results are presented to illustrate the effectiveness of the proposed algorithm

Generalised regular form based SMC for nonlinear systems with application to a WMR

In this paper, a generalised regular form is proposed to facilitate sliding mode control (SMC) design for a class of nonlinear systems. A novel nonlinear sliding surface is designed using implicit function theory such that the resulting sliding motion is globally asymptotically stable. Sliding mode controllers are proposed to drive the system to the sliding surface and maintain a sliding mo-tion thereafter. Tracking control of a two-wheeled mobile robot is considered to underpin the developed theoretical results. Model-based tracking control of a wheeled mobile robot (WMR) is first transferred to a stabilisation problem for the corresponding tracking error system, and then the developed theoretical results are applied to show that the tracking error system is globally asymptotically stable even in the presence of matched and mismatched uncertainties. Both experimental and simulation results demonstrate that the developed results are practicable and effective

SISO model-based control of separated flows: Sliding mode and optimal control approaches

International audienceThe challenging problem of active control of separated flows is tackled in the present paper using model-based design principles, and applied to data issued from a two-dimensional separated flow experiment. First, a bilinear state and input delay model of the system has been obtained from experimental data by means of a modified identification procedure. Adequacy and precision of the obtained model are demonstrated and compared with existing results. Next, two control problems (setpoint tracking and optimal control) have been formulated and studied using sliding mode control methodology and averaging analysis. The theoretical control results are supported with numerical simulations

Robust control design for air breathing proton exchange membrane fuel cell system via variable gain second-order sliding mode

The nonlinear and time-dependent characteristic and unknown modeling uncertainty of proton exchange membrane fuel cell (PEMFC) such as complex electro-chemical, thermal, and fluid mechanic phenomena make its controller design quite challenging. In this paper, a controller based on a super twisting algorithm (STA) with variable gains is proposed to control the air breathing system of PEMFC. The strategy includes regulating the oxygen excess ratio ((Formula presented.)) for preventing the stack oxygen starvation and maintaining optimum net power output in spite of external disturbances and model uncertainties. The proposed algorithm has the main advantages of the fixed gain STA, such as robustness against the disturbance and parametric uncertainties with the unknown boundary, chattering reduction, and finite time convergence. The Lyapunov analysis was proposed to assess the stability of the Variable Gain Super Twisting Algorithm (VGSTA). The results verified the effectiveness of the proposed controller with attaining robust regulation against uncertainties, disturbances, and noisy circumstance compared to fixed gain SOSM controllers