Nonlinear Control and Observation of a Boost Converter Associated with a Fuel-Cell Source in Presence of Model Uncertainty

Tahri, A.; Fadil, H. El; Giri, F.; Chaoui, F.Z.

doi:10.3182/20140824-6-za-1003.00537

Cited by 11 publications

(6 citation statements)

References 14 publications

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“…It is shown in many places that the averaged model of the boost converter, accounting for , is the following :

{\dot{x}}_{1} = \frac{- R_{1}}{L_{1}} x_{1} - \frac{1 - μ_{1}}{L_{1}} x_{2} + \frac{1}{L_{1}} true {true\sum}_{k = 0}^{n} b_{k} x_{1}^{k}

{\dot{x}}_{2} = \frac{1 - μ_{1}}{C_{c d}} x_{1} - \frac{{\overset{i}{true}}_{1}}{C_{d c}}

where the notations are those of Table . Accordingly, x 1 and x 2 denote the average input current i fc and the average output capacitor voltage v dc respectively.…”

Section: System Presentation and Modelingmentioning

confidence: 99%

“…It is shown in many places that the averaged model of the boost converter, accounting for (1), is the following [16]:…”

Section: Presentation and Modeling The Fuel Cell-boost Convertermentioning

confidence: 99%

“…The control objective one seeks is that the load voltage v fc must be tightly regulated to a given reference value V d . It is pointed out in many places [16,19], that the zerodynamics of the system (6a-b), taking the voltage x 2 as output, is unstable, that is, the system seen from the output voltage is the non-minimum phase. The usual practice is to reformulate the control objective in terms of the current x 1 .…”

Section: Fuel Cell-boost Converter Controller Designmentioning

confidence: 99%

See 2 more Smart Citations

Nonlinear Adaptive Control of a Hybrid Fuel Cell Power System for Electric Vehicles – a Lyapunov Stability Based Approach

Tahri

Fadil

Giri

et al. 2015

Asian Journal of Control

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This study deals with the problem of controlling hybrid storage systems in electric vehicles. The storage system includes a DC‐to‐DC switched power converter of boost type associated with a fuel‐cell generator and a buck boost converter connected to a supercapacitor. Both converters operate according to the PWM principle and the whole system model is nonlinear and subject to parameter uncertainties. The control objective is threefold: ensuring a tight dc bus voltage regulation despite the uncertainties on the fuel cell (FC) voltage–current characteristic and on the load converter; (2) guaranteeing a perfect tracking of supercapacitor (SC) current to its reference despite the SC capacitance uncertainty; ensuring asymptotic stability of the closed‐loop system. The control problem is dealt with using a nonlinear adaptive controller designed by the Lyapunov approach. It is formally shown that the proposed controller meets all its control objectives. This theoretical achievement is confirmed by several simulations.

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“…It is shown in many places that the averaged model of the boost converter, accounting for , is the following :

{\dot{x}}_{1} = \frac{- R_{1}}{L_{1}} x_{1} - \frac{1 - μ_{1}}{L_{1}} x_{2} + \frac{1}{L_{1}} true {true\sum}_{k = 0}^{n} b_{k} x_{1}^{k}

{\dot{x}}_{2} = \frac{1 - μ_{1}}{C_{c d}} x_{1} - \frac{{\overset{i}{true}}_{1}}{C_{d c}}

where the notations are those of Table . Accordingly, x 1 and x 2 denote the average input current i fc and the average output capacitor voltage v dc respectively.…”

Section: System Presentation and Modelingmentioning

confidence: 99%

“…It is shown in many places that the averaged model of the boost converter, accounting for (1), is the following [16]:…”

Section: Presentation and Modeling The Fuel Cell-boost Convertermentioning

confidence: 99%

Section: Fuel Cell-boost Converter Controller Designmentioning

confidence: 99%

See 1 more Smart Citation

Nonlinear Adaptive Control of a Hybrid Fuel Cell Power System for Electric Vehicles – a Lyapunov Stability Based Approach

Tahri

Fadil

Giri

et al. 2015

Asian Journal of Control

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show abstract

“…In [30,31], centralized robust and optimal controllers are reported for stability issues in DC micro-grid, however the effects of communication link such as network delays and its failure have not investigated. In [32][33][34][35][36][37][38] several other nonlinear control methods have been proposed with energy management units but all the presented methods are integer order. Fractional order controllers offer additional advantages over integer order controllers such as high degree of freedom.…”

Section: Introductionmentioning

confidence: 99%

Super Twisting Fractional Order Energy Management Control for a Smart University System Integrated DC Micro-Grid

et al. 2020

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This paper designs an intelligent energy management control for a stand alone smart DCmicro-grid using super twisting fractional order method. Based on mathematical model of the micro-grid, controllers are derived for the source side converters such as photovoltaic (PV),wind, AC grid and battery management system, and load side converters. Based on the available measured input and consumed output power, an intelligent energy management algorithm decides the appropriate mode of operation for the source and load side converters controller.All DC loads connected to the micro-grid are treated as essential loads and no load shedding can be allowed by the energy management unit. The energy management unit prioritizes the renewable energy sources (PV and wind) in order to make the micro-grid as cost effective. The performance of the proposed control scheme is compared with the integer order controller and the system is simulated in MATLAB/SIMULINK environment for different test cases.

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“…We propose so that with x ¯ defined in equation (38). It is possible to prove that for all [ v d e i − i d e v ] ≠ 0, besides which, there is always a constant 0 < γ 0 < γ such that Therefore In consequence, the application of Lyapunov’s direct method (Khalil, 1996; Krommydas and Alexandridis, 2014; Tahri et al, 2014) implies that the state-space origin of the unperturbed system e · = f 1 ( t , e ) is asymptotically stable. In this step the asymptotic stability of z = 0 for independent system (44) is shown. We propose the following Lyapunov function candidate with κ 1 , κ 2 > 0 and 0 < ε < κ 1 κ 2 .…”

mentioning

confidence: 99%

Experimental evaluations of voltage regulators for a saturated boost DC-to-DC power converter

Moreno–Valenzuela

Guzman-Guemez

2015

Transactions of the Institute of Measurement and Control

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One of the most common nonlinearities in physical systems is input saturation. Input saturation is rarely considered in the analysis and design of controllers for boost power converters. In addition, the lack of inductor-current measurements and exact knowledge of the supply voltage complicates the problem of voltage regulation even more. In this paper, a new controller is introduced and real-time experiments on output-voltage regulation of a saturated DC-to-DC boost power converter are presented. Specifically, we compare a known scheme with a new control strategy. Both schemes rely on an observer, so knowledge of the supply voltage and the inductor-current measurements is not required. The experimental results indicate that the proposed controller presents the best performance.

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Nonlinear Control and Observation of a Boost Converter Associated with a Fuel-Cell Source in Presence of Model Uncertainty

Cited by 11 publications

References 14 publications

Nonlinear Adaptive Control of a Hybrid Fuel Cell Power System for Electric Vehicles – a Lyapunov Stability Based Approach

Nonlinear Adaptive Control of a Hybrid Fuel Cell Power System for Electric Vehicles – a Lyapunov Stability Based Approach

Super Twisting Fractional Order Energy Management Control for a Smart University System Integrated DC Micro-Grid

Experimental evaluations of voltage regulators for a saturated boost DC-to-DC power converter

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