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Biological Effects of Static Magnetic Fields [[electronic resource] /] / by Xin Zhang, Kevin Yarema, An Xu
| Biological Effects of Static Magnetic Fields [[electronic resource] /] / by Xin Zhang, Kevin Yarema, An Xu |
| Autore | Zhang Xin |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XI, 220 p. 64 illus., 45 illus. in color.) |
| Disciplina | 614.5999 |
| Soggetto topico |
Cancer research
Cell biology Cancer Research Cell Biology |
| ISBN | 981-10-3579-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part 1: Introductory and Background Information -- Chapter 1: Parameters of Magnetic fields -- Chapter 2: Static magnetic fields -- Part 2: Scientific basis for SMF effects on biological systems -- Chapter 3. Impact of SMF on biological molecules -- Chapter 4. Impact of SMF on cells -- Chapter 5. Impact of SMF on animals and other organisms -- Part 3: Opportunities for SMF-based therapies -- Chapter 6. Potential applications of SMF in cancer treatment -- Chapter 7. Potential applications of SMF in other disease treatment. |
| Record Nr. | UNINA-9910253909503321 |
Zhang Xin
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| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Holistic Design of Resonant DC Transformer on Constant Voltage Conversion, Cascaded Stability and High Efficiency / / Xin Zhang [and four others]
| Holistic Design of Resonant DC Transformer on Constant Voltage Conversion, Cascaded Stability and High Efficiency / / Xin Zhang [and four others] |
| Autore | Zhang Xin |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore Pte Ltd., , [2023] |
| Descrizione fisica | 1 online resource (247 pages) |
| Disciplina | 621.31912 |
| Soggetto topico |
Electric currents, Direct
Electric transformers - Design and construction |
| ISBN | 981-19-9115-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- The Proposed Robust Circuit Parameters Design for the CLLC-type DC Transformer in the Hybrid AC/DC Microgrid -- The Proposed Simplified Resonant Parameters Design of the Asymmetrical CLLC-type DC Transformer in the Renewable Energy System via Semi-artificial Intelligent Optimal Scheme -- The Proposed Two-stage Parameter Design Methodology of a Generalized Resonant DC Transformer in Hybrid AC/DC Microgrid with Optimum Active Power Transmission -- Design of Symmetrical CLLC Resonant DC Transformer Considering Voltage Transfer Ratio and Cascaded System Stability -- Parameter Design for Symmetrical CLLC-Type DC Transformer Considering Cascaded System Stability and Power Efficiency -- Design Methodology for Symmetric CLLC Resonant DC Transformer Considering Voltage Conversion Ratio, System Stability and Efficiency -- The Proposed Multi-Time Scale Frequency Regulation of a General Resonant DC Transformer in Hybrid AC/DC Microgrid. |
| Record Nr. | UNINA-9910678259903321 |
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Zhang Xin
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| Singapore : , : Springer Nature Singapore Pte Ltd., , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Law and practice of debt finance in modern China : cross-border perspectives / / Xin Zhang
| Law and practice of debt finance in modern China : cross-border perspectives / / Xin Zhang |
| Autore | Zhang Xin |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (327 pages) |
| Disciplina | 336.340951 |
| Collana | Modern China and international economic law |
| Soggetto topico |
Debts, External - China
Debt financing (Corporations) - China Debt financing (Corporations) |
| ISBN |
981-16-6339-4
981-16-6340-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910743383403321 |
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Zhang Xin
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| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Law and Practice of Debt Finance in Modern China : Cross-Border Perspectives
| Law and Practice of Debt Finance in Modern China : Cross-Border Perspectives |
| Autore | Zhang Xin |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2021 |
| Descrizione fisica | 1 online resource (327 pages) |
| Collana | Modern China and International Economic Law Ser. |
| Soggetto genere / forma | Electronic books. |
| ISBN | 981-16-6340-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910506376003321 |
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Zhang Xin
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| Singapore : , : Springer Singapore Pte. Limited, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Principle, design and optimization of air balancing methods for the multi-zone ventilation systems in low carbon green buildings / / Xin Zhang [and four others]
| Principle, design and optimization of air balancing methods for the multi-zone ventilation systems in low carbon green buildings / / Xin Zhang [and four others] |
| Autore | Zhang Xin |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (167 pages) |
| Disciplina | 605 |
| Soggetto topico | Sustainable buildings |
| ISBN | 981-19-7091-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- About the Authors -- 1 Introduction of the Air Balancing Technology -- 1.1 Background -- 1.1.1 Overview of HVAC Systems -- 1.1.2 Overview of Air Duct Systems -- 1.2 Basic Knowledge of the Air Balancing -- 1.2.1 Mathematical Modeling of the Air Duct System -- 1.2.2 Theoretical Analysis on Energy Consumption in Air Duct Systems Caused by Over Ventilation -- 1.2.3 The Concept and Basic Knowledge of the Air Balancing -- 1.2.4 Benefits of the Air Balancing -- 1.3 Implementation of the Air Balancing -- 1.3.1 Principles of the Air Balancing -- 1.3.2 Traditional Air Balancing Procedure -- 1.3.3 The Existing Air Balancing Methods -- 1.4 Organization of This Book -- References -- 2 A Hierarchical Air Balancing Method via PID Control -- 2.1 Introduction -- 2.2 The Proposed Hierarchical Control Structure for the VAV System -- 2.2.1 Description of the Test Bed -- 2.2.2 The Proposed Hierarchical Control Structure -- 2.3 The Proposed PID Control Strategy of the Fan-Duct System -- 2.3.1 Transfer Function of the Fan-Duct System -- 2.3.2 Open Loop Step Test with Two Points Method -- 2.3.3 PID Parameter Estimation Method Based on the Gain and Phase Margin Method -- 2.4 The Proposed PID Controller of the Damper in the Duct System -- 2.4.1 Characteristic of the Damper -- 2.4.2 Transfer Function Modelling of the Damper -- 2.4.3 PID Parameter Estimation Method -- 2.5 Experimental Results -- 2.5.1 Experiments of the PID Control of the Fan-Duct System -- 2.5.2 Experiments of the PID Controller of the Damper -- 2.5.3 Experiments of the Dual Loop PID Strategy for the Duct System -- 2.6 Conclusion -- References -- 3 A Gradient-Based Online Adaptive Air Balancing Method -- 3.1 Introduction -- 3.2 The Proposed Gradient-Based Online Adaptive Air Balancing Method.
3.2.1 Objective of the Proposed Gradient-Based Online Adaptive Air Balancing Method -- 3.2.2 Refinement of Damper Adjustment with Consideration of Energy Conservation -- 3.2.3 Estimation of Jacobian Matrix and Online Adaptation -- 3.2.4 Low-Pass Filter Trick -- 3.2.5 Final Form of the Proposed Gradient-Based Online Adaptive Air Balancing Method -- 3.3 Design Principle of the Proposed Gradient-Based Online Adaptive Air Balancing Method -- 3.3.1 Base Case of the Gradient-Based Online Adaptive Air Balancing Method -- 3.3.2 Investigation into the Initial Damper Angle ° -- 3.3.3 Investigation into the Refinement Coefficient λ -- 3.3.4 Investigation into the Step Size α -- 3.4 Experimental Validation -- 3.4.1 Experimental Platform and Procedures -- 3.4.2 Validation of the Proposed Gradient-Based Online Adaptive Air Balancing Method on the Test Platform -- 3.5 Conclusion -- References -- 4 A Distributed Cooperative Control-Based Air Balancing Method -- 4.1 Introduction -- 4.2 Theory of the Proposed Distributed Cooperative Control-Based Air Balancing Method -- 4.2.1 Concept of Distributed Cooperative Control: A Consensus Algorithm -- 4.2.2 The Proposed Distributed Cooperative Control-Based Air Balancing Method -- 4.3 Design Principle of the Proposed Distributed Cooperative Control-Based Air Balancing Method -- 4.3.1 Β = 0, Equal q* -- 4.3.2 Β ≠ 0, Equal q* -- 4.3.3 Β ≠ 0, Different q* -- 4.3.4 Β ≠ 0, Different Ts -- 4.4 Experimental Validation -- 4.4.1 Experimental Platform and Experimental Procedures -- 4.4.2 Validation of the Proposed Distributed Cooperative Control-Based Air Balancing Method on the Test Platform -- 4.5 Conclusion -- References -- 5 An Air Balancing Method Using Support Vector Machine -- 5.1 Introduction -- 5.2 Physical-Based System Model of the Duct System -- 5.2.1 Component Model of the Duct System. 5.2.2 Definition of the Physical-Based System Model -- 5.2.3 Computational Model for Duct System -- 5.3 The Proposed Physical Model-Based Air Balancing Procedure -- 5.3.1 Parameter Identification of the Physical Model of the Duct System -- 5.3.2 Damper Position Determination -- 5.4 Data Collection Procedure for the Proposed Air Balancing Method -- 5.5 Experiments Validation -- 5.5.1 Data Sampling and Pre-Processing -- 5.5.2 Parameter Characteristics of SVM -- 5.5.3 Results of Parameter Identification -- 5.5.4 Results of Damper Position Determination -- 5.5.5 Results of Maximum Absolute Percentage Error (MAPE) -- 5.6 Conclusions -- References -- 6 An Air Balancing Method Using Multi-Layer Feed-Forward Network -- 6.1 Introduction -- 6.2 Overview of the Air Balancing Based Energy Saving Control Strategy -- 6.3 MLFFN Based Energy Saving Model of the Ventilation System -- 6.3.1 Experimental Apparatus and Data Collection -- 6.3.2 MLFFN Based Energy Saving Model Construction -- 6.3.3 MLFFN Based Energy Saving Model Validation -- 6.3.4 Analysis of Energy-Saving Ways -- 6.4 The Proposed Air Balancing Control with the MLFFN Based Energy Saving Model -- 6.5 Experimental Validation -- 6.5.1 Command Following Test -- 6.5.2 Energy Saving Potential -- 6.6 Conclusion -- References -- 7 An Air Balancing Method by a Full Data-Driven Duct System Model -- 7.1 Introduction -- 7.2 Problem Description -- 7.2.1 Review of Model-Based Air Balancing Methods -- 7.2.2 Problems of the Existing Model-Based Air Balancing Methods: ASHRAE Damper Model Can Be Inaccurate in Practice -- 7.2.3 Possible Solution: Bypassing the ASHRAE Damper Model and Constructing a Full Data-Driven Duct System (FD3S) Model to Predict the Damper Angle with Terminal Flow Directly -- 7.3 Proposed FD3S Model-Based Air Balancing Method -- 7.3.1 Concept of the Proposed FD3S Model-Based Air Balancing Method. 7.3.2 Proposed FD3S Model-Based Air Balancing Method -- 7.3.3 Advantages of the Proposed Energy-Saving Oriented Air Balancing Method -- 7.4 Experimental Validation -- 7.4.1 Practical Considerations in the Experiment -- 7.4.2 Verification of the Proposed Full Data-Driven Duct System Mode -- 7.4.3 Verification of the Air Balancing Ability on the Test System -- 7.5 Conclusion -- References -- 8 An Air Balancing with Optimal Pressure Set-Point for Minimized Energy Consumption -- 8.1 Introduction -- 8.2 Energy-Saving-Oriented (ESO) Model of Ventilation Systems -- 8.2.1 Definitions for ESO Modeling the Ventilation System -- 8.2.2 ESO Model of the Ventilation System -- 8.2.3 Parameter Identification for the Developed ESO Model -- 8.3 Damper Position Control Method to Achieve Air Balancing -- 8.4 Optimal Static Pressure Set-Point Selection to Minimize Energy Consumption of Ventilation System -- 8.5 Operating Steps for Improved SPR Control Strategy -- 8.6 Experimental Apparatus -- 8.7 Experimental Validation -- 8.7.1 Parameter Selection for SVM Regression Machine Learning Algorithm -- 8.7.2 Parameter Identification for the Developed Model of the Ventilation System -- 8.7.3 Validation of Relative Error of Airflow Rate -- 8.7.4 Validation Through Use of Maximum Absolute Percentage Error -- 8.7.5 Energy-Saving Potential -- 8.8 Conclusion -- References. |
| Record Nr. | UNINA-9910627263703321 |
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Zhang Xin
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| Singapore : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Stability enhancement methods of inverters based on Lyapunov function, predictive control, and reinforcement learning / / Xin Zhang [and three others]
| Stability enhancement methods of inverters based on Lyapunov function, predictive control, and reinforcement learning / / Xin Zhang [and three others] |
| Autore | Zhang Xin |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (175 pages) |
| Disciplina | 262 |
| Soggetto topico | Lyapunov functions |
| ISBN | 981-19-7191-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- About the Authors -- 1 Introduction -- 1.1 Significance of DG in MGs -- 1.2 Categories of MGs -- 1.2.1 AC MG -- 1.2.2 DC MG -- 1.2.3 Hybrid MG -- 1.3 The Cornerstone of MGs: Power Inverters -- 1.3.1 Grid-Connected Inverters: L or LCL Filtered Inverters -- 1.3.2 Standalone Inverters: LC-Filtered Inverter -- 1.3.3 Grid-Connected and Standalone Inverters Cascaded with LC Input Filters -- 1.4 The Necessity of Large-Signal Stability Analysis in Control of Inverters -- 1.4.1 Stability Problems of Inverters and the Existing Small-Signal Stability Analysis -- 1.4.2 The Necessity of Large-Signal Stability Analysis -- 1.4.3 Existing Large-Signal Stability Analysis of Inverters Via Lyapunov's Theory -- 1.4.4 The Motivation of This Book: Advanced Control Strategies for the Power Inverter to Improve Its Large-Signal Stability -- References -- 2 Adaptive Backstepping Current Control of Single-Phase LCL-Grid-Connected Inverters to Improve Its Large-Signal Stability in the Presence of Parasitic Resistance Uncertainty -- 2.1 Introduction -- 2.2 Mathematical Modelling -- 2.3 Derivation of Proposed Control Scheme -- 2.3.1 Step I: Derivation of Pseudo Reference x2ref(t) and Adaptive Law 1 -- 2.3.2 Step II: Derivation of Pseudo Reference x3ref(t) and Adaptive Law 2 -- 2.3.3 Step III: Derivation of Control Law µ(t) and Adaptive Law 3 -- 2.4 Test Results -- 2.5 Conclusion -- References -- 3 An Adaptive Dual-Loop Lyapunov-Based Control Scheme for a Single-Phase Stand-Alone Inverter to Improve Its Large-Signal Stability -- 3.1 Introduction -- 3.2 Mathematical Modelling -- 3.2.1 Average Model of the Investigated System -- 3.2.2 Load Voltage Reference -- 3.2.3 Current-Loop Reference -- 3.2.4 Model of the Load Current -- 3.3 Proposed Adaptive Dual-Loop Lyapunov-Based Control Scheme -- 3.3.1 The Proposed Lyapunov Function.
3.3.2 Derivation of the Adaptive Dual-Loop Control Law -- 3.3.3 Implementation of Proposed Control Scheme -- 3.4 Stability Analysis and Robustness Verification -- 3.4.1 Stability Analysis -- 3.4.2 Robustness Against Plant Parametric Variations -- 3.5 Test Results -- 3.5.1 Steady-State and Dynamic Performance Evaluation -- 3.5.2 Overload and Recovery Scenario -- 3.6 Conclusion -- References -- 4 Lyapunov-Based Control of Three-Phase Stand-Alone Inverters to Improve Its Large-Signal Stability with Inherent Dual Control Loops and Load Disturbance Adaptivity -- 4.1 Introduction -- 4.2 Preliminary of the Proposed Adaptive Dual-Loop Lyapunov-Based Control: Mathematical Modelling -- 4.2.1 Average Model of the Investigated System -- 4.2.2 Load Voltage References vodref, voqref, and Inductor Current References iLdref, iLqref -- 4.2.3 Model of the Load Currents and Proposed Adaptive Laws -- 4.2.4 Modified Inductor Current References iLdref, iLqref Incorporated with Adaptive Laws -- 4.3 Derivation of Proposed Adaptive Decoupled Dual-Loop Lyapunov-Based Control Scheme -- 4.3.1 Proposed Weighted All-in-One Lyapunov Function V -- 4.3.2 Derivation of the Switching Functions and Adaptive Laws -- 4.4 Implementation of Proposed Control Scheme and Its Resulted dq Decoupled Error Dynamics -- 4.4.1 Block Diagram of the Proposed Control Scheme -- 4.4.2 Decoupled Error Dynamics in d Frame and q Frame -- 4.4.3 Recommended Way to Set Load Voltage References -- 4.5 Stability Analysis and Controller Design Guidelines -- 4.5.1 Closed-Loop System Stability Proof -- 4.5.2 Power Loss Analysis, Switching Frequency (fs) Selection and Output LC Filter Design -- 4.5.3 Controller Gains Selection Via Poles Placement -- 4.6 Test Results -- 4.6.1 Performance of Proposed Approach -- 4.6.2 Comparisons Between the Proposed Approach and Existing Control Schemes -- 4.7 Conclusion -- References. 5 An Ellipse-Optimized Composite Backstepping Control Strategy for a Point-of-Load Inverter to Improve Its Large-Signal Stability Under Load Disturbance in the Shipboard Power System -- 5.1 Introduction -- 5.2 Preliminary of the Ellipse-Optimized Composite Backstepping Controller: Mathematical Modelling -- 5.2.1 Dynamic Equations of the Investigated POL Inverter -- 5.2.2 Control Objectives: Load Voltage References x1*, x3* -- 5.3 Recursive Derivation and Implementation of the Proposed Composite Backstepping Controller -- 5.3.1 Two-Step Backstepping Derivation in d Frame -- 5.3.2 Two-Step Backstepping Derivation in q Frame -- 5.3.3 Design of the Kalman Filter to Estimate and Feedforward the Load Currents for Load Disturbance Rejection -- 5.3.4 Implementation of the Proposed Composite Backstepping Controller with a Kalman Filter -- 5.4 Ellipse-Based Controller Gains Optimization, Feedback Gains Matrix Selection, and Robustness Analysis -- 5.4.1 Proposed Intuitive Ellipse-Based Strategy to Optimize the Controller Parameters with Fully Consideration of ξ and ωn -- 5.4.2 Quantitative Selection of the Feedback Gain Matrix G of the Kalman Filter Aided by Ellipse-Optimized Strategy -- 5.4.3 Robustness Analysis of the Proposed Control Scheme Under Parametric Variations and Measurement Errors -- 5.5 Test Results -- 5.5.1 Effectiveness of the Proposed Ellipse-Optimized Controller Gains Selection Strategy -- 5.5.2 Robustness Tests Under Plant Parametric Variations -- 5.5.3 Performance Evaluation Under Linear/Nonlinear Load Step, Reference Step, Overload and Recovery -- 5.5.4 Comparisons Between Existing Lyapunov-Based Approaches and the Proposed Control Scheme -- 5.6 Conclusion -- References -- 6 Stability Constraining Dichotomy Solution Based Model Predictive Control for the Three Phase Inverter Cascaded with Input EMI Filter in the MEA -- 6.1 Introduction. 6.2 Instability Problem of the Researched AC Cascaded System in MEA -- 6.2.1 Instability Problem Description -- 6.2.2 The Instability Reason of CPL with LC Input Filter -- 6.3 Preliminary of the SCDS-MPC Method: Mathematical Modeling of the Researched AC Cascaded System in MEA -- 6.3.1 Conventional Inverter Mathematical Model -- 6.3.2 Improved Mathematical Model with Consideration of the Inverter and Input EMI Filter for Stability Analysis -- 6.4 The Proposed SCDS-MPC Method -- 6.4.1 Conventional Model Predictive Control Scheme -- 6.4.2 Proposed Dichotomy Solution (DS) Based Model Predictive Control -- 6.4.3 Proposed System Stability Constraining Cost Function Definition -- 6.4.4 Sensitivity Analysis of Model Parameters Variation -- 6.5 Test Results -- 6.6 Conclusion -- References -- 7 Composite-Bisection Predictive Control to Stabilize the Three Phase Inverter Cascaded with Input EMI Filter in the SPS -- 7.1 Introduction -- 7.2 Mathematical Modeling -- 7.3 Conventional FCS MPC and Problem Formulation -- 7.4 Proposed Composite Bisection Predictive Control -- 7.4.1 Structure of the Proposed CB-PC Scheme -- 7.4.2 Improved Generic DC-Link Stabilization Strategy Based on Instantaneous Power Theory -- 7.4.3 Indirect Voltage Control Strategy to Achieve Better Transient Response Inspired by the Deadbeat Control -- 7.4.4 Modified Bisection Algorithm -- 7.5 Test Results -- 7.5.1 Effectiveness of the Improved Generic Stabilization Method -- 7.5.2 Transient Performance of the Indirect Voltage Control in Comparison with the Existing Direct Voltage Control -- 7.5.3 Performance of the Proposed CB-PC Under Droop-Akin Strategy With/Without Delay Compensation -- 7.5.4 Comparisons Between the Proposed CB-PC and Existing MPC -- 7.6 Conclusion -- References. 8 Reinforcement Learning Based Weighting Factors' Real-Time Updating Scheme for the FCS Model Predictive Control to Improve the Large-Signal Stability of Inverters -- 8.1 Introduction -- 8.2 Weighting Factors Selection in FCS MPC Affects System Stability -- 8.2.1 Particular Case: WFstability Selection is a Trade-Off Between DC-Link Stabilization and Load Voltage Tracking -- 8.2.2 Generalized Case: WFs Selection Affects System Stability (WFstability in Particular) -- 8.3 WFs' Real-Time Updaing Via the Reinforcement Learning-Based Approach to Improve System Stability -- 8.3.1 Structure of the Proposed Approach -- 8.3.2 RL Agent and Its Selection -- 8.3.3 RL-Based Approach Using a DDPG Agent and Artificial Neural Networks -- 8.4 Verification on the Particular Case: Improving Tracking Accuracy While Ensuring DC-Link Stabilization -- 8.4.1 Configuration of the Observation, Reward, and ANN -- 8.4.2 Parameter Settings and Training Results -- 8.4.3 Test Results -- 8.5 Conclusion -- References. |
| Record Nr. | UNINA-9910633931703321 |
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Zhang Xin
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| Singapore : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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