Applying Optimal Sliding Mode Based Load-Frequency Control in Power Systems with Controllable Hydro Power Plants

Vrdoljak, Krešimir; Perić, Nedjeljko; Petrović, Ivan

doi:10.1080/00051144.2010.11828351

Cited by 6 publications

(3 citation statements)

References 43 publications

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“…As the general analytical solution has not been found [20], it was concluded that stability can be guaranteed if the control signal sampling time is different from the sampling time of the measured output samples. Such a control concept is called multirate output feedback [21][22][23]. The fast output sampling (FOS) method is based on sampling the output signal with higher frequency than the frequency of the control signal samples.…”

Section: Fast Output Sampling Algorithmmentioning

confidence: 99%

State Variables Estimation of Fuel Cell—Boost Converter System Using Fast Output Sampling Method

2013

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Original scientific paperEstimation of state variables of a peak current mode (PCM) controlled DC-DC boost converter supplied by a PEM fuel cell is described in this paper. Since this system is highly nonlinear and non-minimum phase, its state variables are estimated by using fast output sampling method. Estimated state variables are the converter output voltage and its first derivative, and they are suitable for model reference adaptive control or sliding mode based control techniques. The estimator has been designed in a way that it gives a good estimate of the state variables in the continuous and in the discontinuous conduction mode of the converter, and in the presence of measurement and process noise caused by converter switching-mode operation. Experimental results of estimating the state variables on a 450 W boost converter supplied by the emulator of the PEM fuel cell BCS 64-32 show good results of the estimation, regardless of the conduction mode of the converter, i.e. the operating point determined by its output current.Key words: state-space variables, estimation, fast output sampling, peak current mode control, boost converter, step-up converter, PEM fuel cell Procjena varijabli stanja sustava s gorivnimčlankom i uzlaznim pretvaračem metodom brzog uzorkovanja signala. U ovom radu obradena je procjena varijabli stanja sustava s istomjernim uzlaznim pretvaračem u vršnom strujnom načinu upravljanja napajanim PEM gorivnimčlankom. Budući da je taj sustav izrazito nelinearan te neminimalno-fazan, za procjenu njegovih varijabli stanja upotrebljena je metoda brzog uzorkovanja izlaznog signala. Procjenjene varijable stanja su izlazni napon uzlaznog pretvarača te njegova prva derivacija, te su pogodne za adaptivno upravljanje s referentnim modelom i upravljanje temeljeno na kliznim režimima. Procjenitelj je projektiran na način da daje dobru procjenu varijabli stanja u kontinuiranom i diskontinuiranom režimu rada pretvarača, te u uvjetima mjernog i procesnog šuma uzrokovanog sklopnim načinom rada pretvarača. Eksperimentalni rezultati procjene varijabli stanja na uzlaznom pretvaraču snage 450 W napajanim emulatorom gorivnogčlanka BCS 64-32 pokazuju dobre rezultate procjene, neovisno o režimu rada pretvarača, odnosno radnoj točki odredenoj njegovom izlaznom strujom.Ključne riječi: varijable stanja, procjena, brzo uzorkovanje signala, vršno strujno upravljanje, istosmjerni uzlazni pretvarač, PEM gorivničlanak

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Section: Fast Output Sampling Algorithmmentioning

confidence: 99%

State Variables Estimation of Fuel Cell—Boost Converter System Using Fast Output Sampling Method

2013

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“…Sliding‐mode control has many attractive features such as insensitivity to the model errors and parametric uncertainties . Given its advantages, SMC provides powerful techniques to complicated nonlinear dynamic systems for tracking control, including robotic manipulator systems, active suspension vehicle systems, induction motor drive systems, power systems, and spacecraft systems …”

Section: Introductionmentioning

confidence: 99%

Fast terminal sliding‐mode finite‐time tracking control with differential evolution optimization algorithm using integral chain differentiator in uncertain nonlinear systems

Zhang

Krause

2017

Intl J Robust & Nonlinear

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SummaryThis paper presents a fast terminal sliding-mode tracking control for a class of uncertain nonlinear systems with unknown parameters and system states combined with time-varying disturbances. Fast terminal sliding-mode finite-time tracking systems based on differential evolution algorithms incorporate an integral chain differentiator (ICD) to feedback systems for the estimation of the unknown system states. The differential evolution optimization algorithm using ICD is also applied to a tracking controller, which provides unknown parametric estimation in the limitation of unknown system states for trajectory tracking. The ICD in the tracking systems strengthens the tracking controller robustness for the disturbances by filtering noises. As a powerful finite-time control effort, the fast terminal sliding-mode tracking control guarantees that all tracking errors rapidly converge to the origin. The effectiveness of the proposed approach is verified via simulations, and the results exhibit high-precision output tracking performance in uncertain nonlinear systems. KEYWORDS differential evolution, differentiator, nonlinear systems, terminal sliding mode, tracking | INTRODUCTIONSliding-mode control (SMC) is an efficient control scheme and has been widely applied in nonlinear systems. Sliding-mode control has many attractive features such as insensitivity to the model errors and parametric uncertainties.1,2 Given its advantages, SMC provides powerful techniques to complicated nonlinear dynamic systems for tracking control, including robotic manipulator systems, 3 active suspension vehicle systems, 4 induction motor drive systems, 5,6 power systems, 7 and spacecraft systems. The tracking problems using evolutionary optimization in complicated nonlinear systems attract much more attention. Evolutionary optimization algorithms are considered as a powerful optimization tool in solving nonlinear and complicated search spaces.9 Sliding-mode control combined with evolutionary optimization algorithms is presented to improve the tracking performances for complicated nonlinear systems, such as genetic algorithms 10 and particle swarm algorithms. 11,12 These methods have difficulty solving a class of nonlinear tracking problems of unknown system states with time-varying disturbances, which causes an impact on the convergence and stability of the tracking systems.In limited situations, the system states are unknown and needs to be estimated. Along with time-varying disturbances, the differential evolution (DE) optimization algorithm using an integral chain differentiator (ICD) proposed in

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“…In [20,21], two kinds of sliding-mode governors were investigated for hydropower plants. Other reports can be found in [22][23][24]. Usually, one assumption in most of the referred articles is that all the state variables of hydro power systems are measurable.…”

Section: Introductionmentioning

confidence: 99%

Load Frequency Control for Micro Hydro Power Plants by Sliding Mode and Model Order Reduction

Qian

Liu

2015

Automatika

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Original scientific paperMicro hydro is treated as a major renewable energy resource. Such a kind of plants blooms because they can evade some dilemmas like population displacement and environmental problems. But their performance on the frequency index of power systems may be deteriorated in the presence of sudden small load perturbations and parameter uncertainties. To improve the performance, the problem of load frequency control (LFC) raises up. Design of state-based controllers on the aspect of modern control is challenging because only a part of the system states are measurable. This paper addresses the scheme of sliding mode control by model order reduction for the LFC problem of micro hydro power plants. The kind of plants usually has two operating modes, i.e., isolated mode and grid-connected mode. Under each operating mode, mathematical model and model reduction are investigated at first. According to the reduced-order model, a sliding mode control law is subsequently derived. Since the control law is applied to the original system, a sufficient condition about the system stability is proven in light of small gain theory. Simulation results illustrate the feasibility, validity and robustness of the presented scheme. Key words: Load Frequency Control, Micro Hydro Power Plants, Model Order Reduction, Sliding Mode ControlUpravljanje frekvencijom i radnom snagom mikro hidroelektrana kliznim režimom rada i redukcijom reda modela sustava. Mikro hidroelektrane smatraju se jednim od glavnih obnovljivih izvora energije. Ovakve elektrane su poglavito zanimljive pošto izbjegavaju dileme vezane za iseljavanje ljudi i utjecaj na okoliš. Međutim, njihov učinak na indeks frekvencije energetskih sustava može biti negativan zbog naglih manjih promijena u opterećenju i nesigurnosti parametara. Kako bi se unaprijedila učinkovitost, javlja se problem regulacije frekvencije i radne snage. Projektiranje regulatora po varijablama stanja sustava izazovan je problem, jer je mjerljiv samo dio stanja sustava. Ovajčlanak analizira problem upravljanja kliznim režimom rada reducirajući red modela sustava kod regulacije frekvencije i radne snage mikro hidroelektrana. Ovakve elektrane mogu raditi u samostalnom režimu rada ili biti spojene na distribucijsku mrežu. Za oba ražima rada prvo se istražuju matematički modeli te potom njihova redukcija. S obzirom na model reduciranog reda izvodi se upravljački zakon kliznog režima rada. Pošto se zakon upravljanja primjenjuje na izvorni sustav, dokazan je dovoljan uvjet za stabilnost u vidu teorije malog pojačanja. Simulacijski rezutati pokazuju izvedivost, ispravnost i robustnost predloženog pristupa.Ključne riječi: upravljanje frekvencijom i radnom snagom, mikro hidroelektrane, redukcija reda modela sustava, upravljanje u kliznog režimu rada

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Applying Optimal Sliding Mode Based Load-Frequency Control in Power Systems with Controllable Hydro Power Plants

Cited by 6 publications

References 43 publications

State Variables Estimation of Fuel Cell—Boost Converter System Using Fast Output Sampling Method

State Variables Estimation of Fuel Cell—Boost Converter System Using Fast Output Sampling Method

Fast terminal sliding‐mode finite‐time tracking control with differential evolution optimization algorithm using integral chain differentiator in uncertain nonlinear systems

Load Frequency Control for Micro Hydro Power Plants by Sliding Mode and Model Order Reduction

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