Event-based Model Predictive Control
暫譯: 事件驅動的模型預測控制

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.