Xiangyu Meng – författare

Comparison between event-based MPC and traditional MPC, highlighting unique advantages and supported with detailed examples for key algorithms Event-based Model Predictive Control delivers comprehensive knowledge on event-based MPC methods by analyzing the characteristics of event triggering mechanisms and model prediction methods to reduce the burden of optimization problems. The book begins with a comprehensive introduction detailing recent advances related to event-based MPC, then discusses different types of event-based MPC applied to various types of systems. The book provides a quantitative analysis of computation, communication, and energy efficiency gains in various scenarios, highlights new trends such as periodic/aperiodic event triggers and applications in distributed systems, and discusses ongoing challenges and potential research directions. Numerical and key algorithm examples are included throughout to aid in reader comprehension. Written by a team of experts in the field, this book includes information on: A two-stage predictive event-triggered MPC method for disturbed nonlinear continuous systemsAn event-based non-periodic interval sampling MPC method for disturbed discrete nonlinear systemsA composite event-triggered MPC method based on disturbance compensation for constrained discrete systems with slowly varying disturbancesA periodic sampling event-triggered distributed MPC method for the formation control task of multi-agent vehicle systems with nonholonomic constraintsThis book is a definitive resource on the subject for students, researchers, and practitioners in the field of control engineering.

Comparison between event-based MPC and traditional MPC, highlighting unique advantages and supported with detailed examples for key algorithms Event-based Model Predictive Control delivers comprehensive knowledge on event-based MPC methods by analyzing the characteristics of event triggering mechanisms and model prediction methods to reduce the burden of optimization problems. The book begins with a comprehensive introduction detailing recent advances related to event-based MPC, then discusses different types of event-based MPC applied to various types of systems. The book provides a quantitative analysis of computation, communication, and energy efficiency gains in various scenarios, highlights new trends such as periodic/aperiodic event triggers and applications in distributed systems, and discusses ongoing challenges and potential research directions. Numerical and key algorithm examples are included throughout to aid in reader comprehension. Written by a team of experts in the field, this book includes information on: A two-stage predictive event-triggered MPC method for disturbed nonlinear continuous systems An event-based non-periodic interval sampling MPC method for disturbed discrete nonlinear systems A composite event-triggered MPC method based on disturbance compensation for constrained discrete systems with slowly varying disturbances A periodic sampling event-triggered distributed MPC method for the formation control task of multi-agent vehicle systems with nonholonomic constraints This book is a definitive resource on the subject for students, researchers, and practitioners in the field of control engineering.

Comparison between event-based MPC and traditional MPC, highlighting unique advantages and supported with detailed examples for key algorithms Event-based Model Predictive Control delivers comprehensive knowledge on event-based MPC methods by analyzing the characteristics of event triggering mechanisms and model prediction methods to reduce the burden of optimization problems. The book begins with a comprehensive introduction detailing recent advances related to event-based MPC, then discusses different types of event-based MPC applied to various types of systems. The book provides a quantitative analysis of computation, communication, and energy efficiency gains in various scenarios, highlights new trends such as periodic/aperiodic event triggers and applications in distributed systems, and discusses ongoing challenges and potential research directions. Numerical and key algorithm examples are included throughout to aid in reader comprehension. Written by a team of experts in the field, this book includes information on: A two-stage predictive event-triggered MPC method for disturbed nonlinear continuous systems An event-based non-periodic interval sampling MPC method for disturbed discrete nonlinear systems A composite event-triggered MPC method based on disturbance compensation for constrained discrete systems with slowly varying disturbances A periodic sampling event-triggered distributed MPC method for the formation control task of multi-agent vehicle systems with nonholonomic constraints This book is a definitive resource on the subject for students, researchers, and practitioners in the field of control engineering.

This book focuses on the low-frequency oscillation between EMUs and traction networks in high-speed Railways. As the power source of high-speed trains, the traction network's power performance directly affects the safe and stable operation of the train. However, the low-frequency oscillation between EMUs and traction networks will fluctuate voltage or current, resulting in poor power quality, electrical device failure, and even interruption of traction power. Therefore, it is important to reveal the mechanism of low-frequency oscillation and propose suppression strategies. This book systematically shows the newest research results of analysis and suppression of low-frequency oscillation between EMUs and traction networks in high-speed railways, especially in the modeling methods of vehicle-grid systems and suppression strategies for low-frequency oscillation. These methods or strategies can provide important references and help for researchers, scholars, and engineers on traction power technology in high-speed railways. The main contents include the overview of low-frequency oscillation between EMUs and traction networks, the introduction of main modeling methods for vehicle-grid systems, especially single-phase rectifiers, the line-side converter control algorithms in vehicles for the suppression of low-frequency oscillation, the traction substation power compensation strategies for the suppression of low-frequency oscillation, etc.