Interval Methods for Robust Sliding Mode Control Synthesis of High-Temperature Fuel Cells with State and Input Constraints

Rauh, Andreas; Senkel, Luise

doi:10.1007/978-3-319-31539-3_3

Cited by 8 publications

(5 citation statements)

References 23 publications

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“…In other control-oriented research activities such approaches are employed to prove stability of a closed-loop controller in the presence of hard one-or two-sided state and output as well as actuator constraints. For further details about real-time capable strategies for parameter adaption of nonlinear robust feedback controllers exploiting such barrier functions, the reader is referred to [17,18,37] as well as to [38]. The focus of the last reference is on using sensitivity-based feedforward and predictive control procedures to avoid exceeding state constraints instead of exploiting barrier function techniques.…”

Section: Online Optimization Of the Electric Current And Hydrogen Masmentioning

confidence: 99%

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Kalman Filter-Based Real-Time Implementable Optimization of the Fuel Efficiency of Solid Oxide Fuel Cells

Rauh

2021

Clean Technol.

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The electric power characteristic of solid oxide fuel cells (SOFCs) depends on numerous influencing factors. These are the mass flow of supplied hydrogen, the temperature distribution in the interior of the fuel cell stack, the temperatures of the supplied reaction media at the anode and cathode, and—most importantly—the electric current. Describing all of these dependencies by means of analytic system models is almost impossible. Therefore, it is reasonable to identify these dependencies by means of stochastic filter techniques. One possible option is the use of Kalman filters to find locally valid approximations of the power characteristics. These can then be employed for numerous online purposes of dynamically operated fuel cells such as maximum power point tracking or the maximization of the fuel efficiency. In the latter case, it has to be ensured that the fuel cell operation is restricted to the regime of Ohmic polarization. This aspect is crucial to avoid fuel starvation phenomena which may not only lead to an inefficient system operation but also to accelerated degradation. In this paper, a Kalman filter-based, real-time implementable optimization of the fuel efficiency is proposed for SOFCs which accounts for the aforementioned feasibility constraints. Essentially, the proposed strategy consists of two phases. First, the parameters of an approximation of the electric power characteristic are estimated. The measurable arguments of this function are the hydrogen mass flow and the electric stack current. In a second stage, these inputs are optimized so that a desired stack power is attained in an optimal way. Simulation results are presented which show the robustness of the proposed technique against inaccuracies in the a-priori knowledge about the power characteristics. For a numerical validation, three different models of the electric power characteristic are considered: (i) a static neural network input/output model, (ii) a first-order dynamic system representation and (iii) the combination of a static neural network model with a low-order fractional differential equation model representing transient phases during changes between different electric operating points.

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Section: Online Optimization Of the Electric Current And Hydrogen Masmentioning

confidence: 99%

“…hold. Note, all current and mass flow dependencies of the expressions in (35)- (37) are expressed in terms of the previous commanded values u k , so that filtering of these quantities is not required for an online implementation.…”

Section: Online Optimization Of the Electric Current And Hydrogen Masmentioning

confidence: 99%

Kalman Filter-Based Real-Time Implementable Optimization of the Fuel Efficiency of Solid Oxide Fuel Cells

Rauh

2021

Clean Technol.

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“…In refs. [27] and [28], a governor method was designed to satisfy the constraints of uncertain nonlinear systems, in which the input of the closed loop system is the reference signal, and modification of the reference signal does not violate the state and control constraints. In ref.…”

Section: Introductionmentioning

confidence: 99%

Barrier Lyapunov function and adaptive backstepping-based control of a quadrotor UAV

Khadhraoui,

Zouaoui,

Saad

2023

Robotica

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This paper presents backstepping control and backstepping constraint control approaches for a quadrotor unmanned aerial vehicle (UAV) control system. The proposed methods are applied to a Parrot Mambo drone model to control rotational motion along the $x$ , $y$ , and $z$ axes during hovering and trajectory tracking. In the backstepping control approach, each state of the system controls the previous state and is called “virtual control.” The last state is controlled by the real control input. The idea is to compute, in several steps, a control law that ensures the asymptotic stability of the system. The backstepping constraint control method, based on barrier Lyapunov functions (BLFs), is designed not only to track the desired trajectory but also to guarantee no violation of the position and angle constraints. Symmetric BLFs are introduced in the design of the controller. A nonlinear mathematical model is considered in this study. Based on Lyapunov stability theory, it can be concluded that the proposed controllers can guarantee the stability of the UAV system and the state converges asymptotically to the desired trajectory. To make the control robust, an adaptation law is applied to the backstepping control that estimates the unknown parameters and ensures their convergence to their respective values. Validation of the proposed controllers was performed by simulation on a flying UAV system.

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“…for elements located at the system boundary; Even if spatially semi-discretized models for the temperature distribution in the fuel cell stack (as those shown in Figures 2 and 3 which were described in detail by Rauh et al [9]) are reasonable for the implementation of model-based stack temperature estimators and controllers [10][11][12][13][14][15][16], the use of numerous temperature values for the interior of the stack in a semi-discretized manner is not at all practical for the accurate-offline-based-identification of a current-voltage characteristic as a function of each of these thermal state variables. This holds analogously for the spatial variations of the fractions of the anode and cathode gas mass flows, and their respective partial concentrations, which are depicted schematically in Figure 4 for the same semi-discretization that was previously described for the thermal subsystem model.…”

Section: Introductionmentioning

confidence: 99%

Kalman Filter-Based Online Identification of the Electric Power Characteristic of Solid Oxide Fuel Cells Aiming at Maximum Power Point Tracking

2020

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High-temperature fuel cells are one of the devices currently investigated for an integration into distributed power supply grids. Such distributed grids aim at the simultaneous production of thermal energy and electricity. To maximize the efficiency of fuel cell systems, it is reasonable to track the point of maximum electric power production and to operate the system in close vicinity to this point. However, variations of gas mass flows, especially the concentration of hydrogen contained in the anode gas, as well as variations of the internal temperature distribution in the fuel cell stack module lead to the fact that the maximum power point changes in dependence of the aforementioned phenomena. Therefore, this paper first proposes a real-time capable stochastic filter approach for the local identification of the electric power characteristic of the fuel cell. Second, based on this estimate, a maximum power point tracking procedure is derived. It is based on an iteration procedure under consideration of the estimation accuracy of the stochastic filter and adjusts the fuel cell’s electric current so that optimal operating points are guaranteed. Numerical simulations, based on real measured data gathered at a test rig available at the Chair of Mechatronics at the University of Rostock, Germany, conclude this paper.

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Interval Methods for Robust Sliding Mode Control Synthesis of High-Temperature Fuel Cells with State and Input Constraints

Cited by 8 publications

References 23 publications

Kalman Filter-Based Real-Time Implementable Optimization of the Fuel Efficiency of Solid Oxide Fuel Cells

Kalman Filter-Based Real-Time Implementable Optimization of the Fuel Efficiency of Solid Oxide Fuel Cells

Barrier Lyapunov function and adaptive backstepping-based control of a quadrotor UAV

Kalman Filter-Based Online Identification of the Electric Power Characteristic of Solid Oxide Fuel Cells Aiming at Maximum Power Point Tracking

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