Adaptive Backstepping Consensus Control For Nonlinear Multi Agent Systems
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Adaptive Backstepping Consensus Control for Nonlinear Multi-Agent Systems
Adaptive Backstepping Consensus Control for Nonlinear Multi-Agent Systems: Command Filtered Backstepping offers a new design solution for students, researchers, and engineers working on distributed cooperative control problems for nonlinear multi-agent systems. The book is structured around six key topics, focusing on command filtered backstepping-based distributed adaptive consensus control. By combining command filtered backstepping techniques with adaptive control, fuzzy logic systems, neural networks, and other control approaches, the book investigates and proposes control schemes for the consensus control problem of nonlinear multi-agent systems. Readers will gain a comprehensive understanding of consensus control based on adaptive command filtered backstepping technology.
Adaptive Backstepping Control of Uncertain Systems
Author: Jing Zhou
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-02-07
This book employs the powerful and popular adaptive backstepping control technology to design controllers for dynamic uncertain systems with non-smooth nonlinearities. Various cases including systems with time-varying parameters, multi-inputs and multi-outputs, backlash, dead-zone, hysteresis and saturation are considered in design and analysis. For multi-inputs and multi-outputs systems, both centralized and decentralized controls are addressed. This book not only presents recent research results including theoretical success and practical development such as the proof of system stability and the improvement of system tracking and transient performance, but also gives self-contained coverage of fundamentals on the backstepping approach illustrated with simple examples. Detail description of methodologies for the construction of adaptive laws, feedback control laws and associated Lyapunov functions is systematically provided in each case. Approaches used for the analysis of system stability and tracking and transient performances are elaborated. Two case studies are presented to show how the presented theories are applied.
Distributed Adaptive Consensus Control of Uncertain Multi-Agent Systems
Multi-agent systems are special networked systems full of research interest and practical sense, which are abundant in real life, ranging from mobile robot networks, intelligent transportation management, to multiple spacecraft, surveillance and monitoring. Consensus control is one of the most typical and hot research issues for multi-agent systems. Distributed Adaptive Consensus Control of Uncertain Multi-agent Systems provides innovative technologies to design and analyze distributed adaptive consensus for multi-agent systems with model uncertainties. Based on the basic graph theory and adaptive backstepping control, this monograph: · Describes the state of the art on distributed adaptive control, finite-time consensus control and event-triggered consensus control · Studies distributed adaptive consensus under directed communication graph condition: the methods with linearly parametric reference, hierarchical decomposition, and design of auxiliary filers · Explores adaptive finite-time consensus for uncertain nonlinear systems · Considers distributed adaptive consensus with event-triggered communication via state feedback and output feedback · Investigates distributed adaptive formation control of nonholonomic mobile robots with experimental verification · Provides distributed adaptive attitude synchronization control schemes for multiple spacecraft with event-triggered communication Distributed Adaptive Consensus Control of Uncertain Multi-agent Systems can help engineering students and professionals to efficiently learn distributed adaptive control design tool for handling uncertain multi-agent systems with directed communication graph, guaranteeing finite-time convergence and saving communication resources.