An Adaptive Observer-Based Controller Design for Active Damping of a DC Network With a Constant Power Load

Machado, Juan E.; Astolfi, Alessandro; Arocas-Pérez, José; Pyrkin, Anton A.; Bobtsov, Alexey A.; Griñó, Robert

doi:10.1109/tcst.2020.3037859

Cited by 13 publications

(6 citation statements)

References 16 publications

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“…After the resonance suppression effectiveness evaluation, enhancing the universal adaptability of resonance suppression strategies under different scenarios is a further step to address the above issues. The active damper is connected in parallel to the resonance node, which has been widely applied to suppress resonance and enhance system stability by reshaping system impedance [24][25][26]. Refs.…”

Section: Introductionmentioning

confidence: 99%

DC Active Damper Control Strategy Based on Resonance Suppression Effectiveness Evaluation Method

Zhang,

Wang,

Zhu

et al. 2024

Energies

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With the complication of the power system, features of the resonance interaction behave diversely and pose a threat to the effectiveness of the resonance suppression strategies. Existing resonance suppression strategies are usually designed for specific scenarios which are in close correlation with the impedance frequency-amplitude distribution, and their adaptability under different scenarios is hard to evaluate. In this paper, the resonance suppression domain of a DC distribution network is derived based on the node impedance variation before/after the resonance is suppressed. The derived criterion takes the admittance change of the resonance suppression strategies as variables, and the conservative/ideal suppression domain criteria are defined. On this basis, a method for evaluating the effectiveness of resonance suppression strategies is proposed, which simplifies the evaluation process and avoids a complicated matrix inverse process to each resonance suppression strategy during the system impedance calculation. Furthermore, a DC active damper control strategy based on the resonance suppression strategy evaluation is proposed, and the proposed strategy could suppress resonances under different scenarios by a targeted design of the reshaping admittance parameters. Time domain simulations with a 5-node distribution network are carried out to verify the proposed method.

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Section: Introductionmentioning

confidence: 99%

DC Active Damper Control Strategy Based on Resonance Suppression Effectiveness Evaluation Method

Zhang,

Wang,

Zhu

et al. 2024

Energies

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“…1]). The adaptive controller in [12] requires the knowledge of some system parameters for the observer design, while the adaptive negative impedance strategy in [13] does not establish stability guarantees. A datadriven controller is proposed in [14], where the errors of the output voltage and input current w.r.t.…”

Section: Introductionmentioning

confidence: 99%

Voltage Control of DC Microgrids: Robustness for Unknown ZIP-Loads

Cucuzzella

Kosaraju

Scherpen

2023

IEEE Control Syst. Lett.

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In this letter we propose a new passivitybased control technique for Buck converter based DC microgrids comprising ZIP-loads, i.e., loads with the parallel combination of constant impedance (Z), current (I) and power (P). More precisely, we propose a novel passifying input and a storage function based on the mixed potential function introduced by Brayton and Moser, relaxing restrictive (sufficient) conditions on Z, P and the voltage reference, which are usually assumed to be satisfied in the literature. Consequently, we develop a new passivity-based controller that is robust with respect to uncertain ZIP-loads.

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“…So far, we do not have a very effective control method for the trajectory tracking control problems. In article [19], a self-correcting adaptive method is proposed, to solve problems including dynamic parameters, where the model structure often changes. Trajectory tracking control algorithms for AUV stochastic uncertain nonlinear systems have been proposed.…”

Section: Introductionmentioning

confidence: 99%

Research on Practical Path Tracking Control of Autonomous Underwater Vehicle Based on Constructive Dynamic Gain Controller

Wang,

Peng,

Guo

2023

JMSE

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In this study, the stochastic nonlinear system-based trajectory tracking control problem of an autonomous underwater vehicle (AUV) is studied. We investigate the time-varying gain adaptive control method to find possible approaches to reduce the excessive computational burden. Enhanced adaptive algorithms are devised by considering the dynamic characteristics of AUV motion. By transforming the original controller design problems into parameter selection problems and subsequently solving them using the functional time-varying observer technical theorem, we can achieve optimal control performance. The control system is shown to constrain system state error due to stochastic disturbances within arbitrarily small domains. A coordinate transformation is proposed for all system states to meet boundedness conditions. We show that the closed-loop stability is confirmed, the system is asymptotically probabilistically stable, and contraction limits given in the stability analysis may be used to certify the convergence of the AUV trajectory errors. A large number of simulation studies using an underwater vehicle model have proved the effectiveness and robustness of the proposed approach. A real-time, time-varying gain constructive control strategy is further developed for the hardware-in-the-loop simulation; the effectiveness of the controller design is confirmed by introducing the controller into the AUV actuator model.

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An Adaptive Observer-Based Controller Design for Active Damping of a DC Network With a Constant Power Load

Cited by 13 publications

References 16 publications

DC Active Damper Control Strategy Based on Resonance Suppression Effectiveness Evaluation Method

DC Active Damper Control Strategy Based on Resonance Suppression Effectiveness Evaluation Method

Voltage Control of DC Microgrids: Robustness for Unknown ZIP-Loads

Research on Practical Path Tracking Control of Autonomous Underwater Vehicle Based on Constructive Dynamic Gain Controller

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