Adaptive Wavelet Neural Network Backstepping Sliding Mode Tracking Control for PMSM Drive System

Liu, Da; Li, Muguo

doi:10.7305/automatika.2014.12.456

Cited by 9 publications

(4 citation statements)

References 24 publications

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“…According to the SMC methodology, a SMC law consists of equivalent control law and switching control law [14][15][16]. The equivalent control law ensures the system trajectory stays on the surface after reaching the sliding mode.…”

Section: Isolated Modementioning

confidence: 99%

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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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Section: Isolated Modementioning

confidence: 99%

“…Among these presented control methods, sliding mode control (SMC) is attractive due to its invariance property [14][15][16]. Recently, there has been an increasing interest in applying the control technology [17,18].…”

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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“…A review [13] looked into contemporary views concerning distribution network management and control for small/micro hydro power facilities. SMC is the most appealing of the control techniques offered because of its invariance characteristic [14]- [16]. There has recently been a surge in interest in using control technologies [17], [18].…”

Section: Introductionmentioning

confidence: 99%

Optimal Frequency stability Control Strategy for a Grid-Connected Wind/PV/FC/BESS Coordinated with Hydroelectric Power Plant Storage Energy System Using Variable Structure Control

El-Gammal

Boodoo

2021

EJENERGY

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Because of the growing nonlinear and complexity nature of microgrid systems for example battery energy storage systems, wind-turbine fuel cell, photovoltaic, and micro hydro power plants (BESSs/FC/WT/PV/ Micro Hydro), load-frequency management has been a difficulty. The development of a load-frequency controller based on Proportional–Integral–Derivative (PID) for an autonomous microgrid (MG) with hydro, wind, and PV RES is shown in this article. The suggested LFC goal is to retain the frequency of the micro hydro power plant under variable load situations by controlling the sharing of output power constant generator between the dummy loads and consumer. Using an adaptive fuzzy logic controller to govern nearly the generating unit`s whole operation, the suggested control technique optimally chooses PID settings for each load value. The suggested fuzzy logic-based controller regulates the plant's frequency output despite fluctuating user loads and manages energy distribution by separating the micro network into separate departures connected in priority order. The suggested frequency controller uses a centralised LFC approach centred on a combination of smart load and Battery Energy Storage System to manage the MG frequency (BESS). It regulates MG frequency by providing active power balancing for a variety of events that such systems face in real-world settings, such as energy surplus generation and energy shortage. In Simulink/MATLAB, the suggested structure is simulated. The simulation results clearly demonstrate the proposed frequency controller's ability to dump extra power when the customer load varies while maintaining a consistent supply frequency.

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“…Furthermore, adaptive and robust control techniques remain at the focus of researchers' awareness on the ground of defects in modelling of MEMS and parametric uncertainties in their manufacturing procedures [13][14][15][16][17][18]. Adaptive sliding mode control is one of the most popular methods in MEMS or other mechatronic systems dynamics and control research since it copes with parameter uncertainty and disturbance rejection simultaneously [19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Robust adaptive sliding mode control of a MEMS tunable capacitor based on dead-zone method

2020

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Uncertainty in parameters of a tunable Micro Electro Mechanical System (MEMS) capacitor, as the main component of AC Voltage Reference Source (VRS), is significant to obtain a precise output voltage unaffected by disturbance and noise. Although attempts are done to craft the capacitor with desired physical specification and improve accuracy of parameters, parametric uncertainties transpire in manufacturing due to micro-machining shortcomings. First off, this paper remarks design of a Robust Adaptive Sliding Mode Controller (RASMC) and its application for the MEMS AC VRS for the first time so that it can produce a stable precise regulated output at presence of uncertainties and disturbance. Secondly, it makes a comparison between the proposed novel controller and our previously designed ASMC. The comparison reassures one of robustness at exacerbating conditions in the tunable capacitor dynamics. The novelty is employment of the dead zone-based ASMC to manage parametric uncertainty and disturbance in the MEMS tunable capacitor. It also contributes to adaptive sliding mode control of the dynamics with stiffness and damping coefficients, which are non-slowly-varying time-dependent parameters, approaching dead-zone method. Uncertainty in the plate mass besides bounded time-variant uncertainty in stiffness and damping are considered. These restrictions were not deemed in the previous design.

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Adaptive Wavelet Neural Network Backstepping Sliding Mode Tracking Control for PMSM Drive System

Cited by 9 publications

References 24 publications

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

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

Optimal Frequency stability Control Strategy for a Grid-Connected Wind/PV/FC/BESS Coordinated with Hydroelectric Power Plant Storage Energy System Using Variable Structure Control

Robust adaptive sliding mode control of a MEMS tunable capacitor based on dead-zone method

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