Finite Control Set Model Predictive Control for Dynamic Reactive Power Compensation With Hybrid Active Power Filters

Ferreira, S. C.; Gonzatti, Robson Bauwelz; Pereira, Rondineli Rodrigues; Silva, Carlos Henrique da; Silva, L. E. Borges da; Lambert‐Torres, Germano

doi:10.1109/tie.2017.2740819

Cited by 109 publications

(58 citation statements)

References 24 publications

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“…Therefore, a new advanced motor controlling technique is required. As described in section 2.2.1 model predictive control strategy tend to perform better than the classical controllers for highly dynamic applications with improved accuracy [78,79].…”

Section: Resultsmentioning

confidence: 99%

Model Predictive Control of Five-Phase Permanent Magnet Assisted Synchronous Reluctance Motor

Dharmasena

Choi

2019

2019 IEEE Applied Power Electronics Conference and Exposition (APEC)

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Section: Resultsmentioning

confidence: 99%

Model Predictive Control of Five-Phase Permanent Magnet Assisted Synchronous Reluctance Motor

Dharmasena

Choi

2019

2019 IEEE Applied Power Electronics Conference and Exposition (APEC)

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“…Grid-connected converters (GCCs) have been widely employed for power conversion in a lot of different applications, such as renewable power generation [1]- [4], active power filters [5]- [8], and rectifier systems [9], [10], just to name a few. In these scenarios, the converter presents as a controllable current source to the grid.…”

Section: Introductionmentioning

confidence: 99%

Tuning of Discrete Complex Proportional Integral Current Controller for Grid-Connected Converters Based on Critical Damping

Zhao

Cao

et al. 2020

IEEE Access

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Current control is of utmost importance for grid-connected converters to achieve a high level of performance. The complex proportional integral controller is usually employed for its excellent performance in terms of cross-coupling decoupling and stability. The pole/zero cancellation characteristic of the complex proportional integral controller, which is always valid in the continues-time domain, fails in the discrete-time domain, resulting in an oscillatory or even unstable response. The discrete complex proportional integral controller has thus been addressed in this work, which cancels the complex plant pole with a matching zero provided by the controller in the discrete-time domain. It has been proved that pole/zero cancellation of the discrete complex proportional integral controller is always valid, regardless of the variation of the excitation frequency. An important feature of performance independence from the pulse ratio is thus achieved. Also, to achieve the possible highest performance, a tuning method based on critical damping is developed in the discrete-time domain, which addresses the one-sample delay directly in the tuning process. In this manner, the minimum settling time and negligible overshoot for transient response can be achieved, along with the most enhanced stability and avoidance of closed-loop anomalous peaks. Experimental results have verified the effectiveness of the developed method. INDEX TERMS Current control, grid connected converters, complex proportional integral, discretization.

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“…Model predictive control (MPC) is one of the non-linear control methods that has received a lot of attention in the recent publications. The algorithm has been adapted to multiple applications in power electronics where linear hierarchical control was dominating in the past years like electrical drives [2], [3], power filters [4], STATCOM [5], photovoltaics [6], microgrids [7] and many more. The system constraints and multi objective algorithms can easily be implemented making this control concept very attractive due to its straightforward design.…”

Section: Introductionmentioning

confidence: 99%

Analytical Design and Performance Validation of Finite Set MPC Regulated Power Converters

Novak

Nyman

Dragičević

et al. 2019

IEEE Trans. Ind. Electron.

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A new approach to performance validation of finite control set model predictive control (FCS-MPC) regulated power electronics converters is presented in the paper-statistical model checking (SMC). SMC is an established method used in various sectors of industry to provide solutions to problems that are beyond the abilities of classical formal techniques. The method is simple for implementation and requires only an operational system model that can be simulated and checked against properties. The approach will be presented on a standard 2-level voltage source converter (VSC) regulated by the FCS-MPC algorithm. In UPPAAL SMC toolbox the converter system and controller are modeled as a Network of Stochastic Timed Automata. To assess the quality of the model, an equivalent Simulink model is used as a benchmark model. Using the model created in UPPAAL SMC toolbox the performance of the FCS-MPC algorithm is verified. The control algorithm is also tested on an experimental setup. During the evaluation, no significant degradation of reference tracking was found during transients nor under model parameter uncertainty. Index Terms-Controller performance, DC-AC power conversion, finite control set model predictive control, statistical model checking.

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Finite Control Set Model Predictive Control for Dynamic Reactive Power Compensation With Hybrid Active Power Filters

Cited by 109 publications

References 24 publications

Model Predictive Control of Five-Phase Permanent Magnet Assisted Synchronous Reluctance Motor

Model Predictive Control of Five-Phase Permanent Magnet Assisted Synchronous Reluctance Motor

Tuning of Discrete Complex Proportional Integral Current Controller for Grid-Connected Converters Based on Critical Damping

Analytical Design and Performance Validation of Finite Set MPC Regulated Power Converters

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