Zongyu Zuo - Böcker

This book presents a concise introduction to the latest advances in robust cooperative control design for multi-agent systems with input delay and external disturbances, especially from a prediction and observation perspective. The volume covers a wide range of applications, such as the trajectory tracking of quadrotors, formation flying of multiple unmanned aerial vehicles (UAVs) and fixed-time formation of ground vehicles.Robust cooperative control means that multi-agent systems are able to achieve specified control tasks while remaining robust in the face of both parametric and nonparametric model uncertainties. In addition, the authors cover a wide range of key issues in cooperative control, such as communication and input delays, parametric model uncertainties and external disturbances. Moving beyond the scope of existing works, a systematic prediction and observation approach to designing robust cooperative control laws is presented.About the AuthorsChunyan Wang is an Associate Professor in the School of Aerospace Engineering at Beijing Institute of Technology, China.Zongyu Zuo is a full Professor with the School of Automation Science and Electrical Engineering, Beihang University, China.Jianan Wang is an Associate Professor in the School of Aerospace Engineering at Beijing Institute of Technology, China.Zhengtao Ding is a Professor in the Department of Electrical and Electronic Engineering at University of Manchester, U.K.

This book presents a concise introduction to the latest advances in robust cooperative control design for multi-agent systems with input delay and external disturbances, especially from a prediction and observation perspective. The volume covers a wide range of applications, such as the trajectory tracking of quadrotors, formation flying of multiple unmanned aerial vehicles (UAVs) and fixed-time formation of ground vehicles.Robust cooperative control means that multi-agent systems are able to achieve specified control tasks while remaining robust in the face of both parametric and nonparametric model uncertainties. In addition, the authors cover a wide range of key issues in cooperative control, such as communication and input delays, parametric model uncertainties and external disturbances. Moving beyond the scope of existing works, a systematic prediction and observation approach to designing robust cooperative control laws is presented.About the AuthorsChunyan Wang is an Associate Professor in the School of Aerospace Engineering at Beijing Institute of Technology, China.Zongyu Zuo is a full Professor with the School of Automation Science and Electrical Engineering, Beihang University, China.Jianan Wang is an Associate Professor in the School of Aerospace Engineering at Beijing Institute of Technology, China.Zhengtao Ding is a Professor in the Department of Electrical and Electronic Engineering at University of Manchester, U.K.

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 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, encouraging readers to contribute to this advancing field. Numerical and key algorithm examples are included throughout to aid in reader comprehension. Written by a team of experts in the field, Event-based Model Predictive Control includes information on: A two-stage predictive event-triggered MPC method for disturbed nonlinear continuous systems, using a predictive approach to introduce the concept of safety prediction valueAn 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 constraintsEvent-based Model Predictive Control is a definitive resource on the subject for students, researchers, and practitioners in the field of control engineering.

This monograph presents new theories and methods for fixed-time cooperative control of multi-agent systems. Fundamental concepts of fixed-time stability and stabilization are introduced with insightful understanding. This book presents solutions for several problems of fixed-time cooperative control using systematic design methods. The book compares fixed-time cooperative control with asymptotic cooperative control, demonstrating how the former can achieve better closed-loop performance and disturbance rejection properties. It also discusses the differences from finite-time control, and shows how fixed-time cooperative control can produce the faster rate of convergence and provide an explicit estimate of the settling time independent of initial conditions. This monograph presents multiple applications of fixed-time control schemes, including to distributed optimization of multi-agent systems, making it useful to students, researchers and engineers alike.