Nonlinear Control Of Nonholonomic Mobile Robot Formations
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Nonlinear Control of Nonholonomic Mobile Robot Formations
"In this thesis, the framework developed to control a single nonholonomic mobile robot is expanded to include the control of formations of multiple nonholonomic mobile robots. A combined kinematic/torque control law is developed for leader-follower based formation control using backstepping in order to accommodate the dynamics of the robots and the formation in contrast with kinematic-based formation controllers typically found in literature"--Abstract, leaf iv.
Time-Varying Formation Tracking Control for Nonlinear Swarm Systems
The book focuses on time-varying formation control approaches for practical nonlinear swarm systems. Time-varying formation control is the basic guarantee for performing other tasks of swarm systems, such as cooperative decision-making and cooperative detection. However, most practical swarm systems have nonlinear dynamic models. This book studies three typical models of practical nonlinear swarm systems, which represent most of the practical systems and construct the corresponding formation control structure. At the same time, the effects of disturbances, uncertain dynamics, random noise and unknown leader's input are considered and processed to improve the robustness and adaptability. The comprehensive and systematic treatment of practical nonlinear time-varying formation control issues is one of the major features of the book, which is particularly suited for readers who are interested to learn time-varying formation control solutions in nonlinear swarm systems. The book benefits researchers, engineers and graduate students in the fields of formation control, nonlinear control, robust control, etc.
Nonlinear Control of Dynamic Networks
Significant progress has been made on nonlinear control systems in the past two decades. However, many of the existing nonlinear control methods cannot be readily used to cope with communication and networking issues without nontrivial modifications. For example, small quantization errors may cause the performance of a "well-designed" nonlinear control system to deteriorate. Motivated by the need for new tools to solve complex problems resulting from smart power grids, biological processes, distributed computing networks, transportation networks, robotic systems, and other cutting-edge control applications, Nonlinear Control of Dynamic Networks tackles newly arising theoretical and real-world challenges for stability analysis and control design, including nonlinearity, dimensionality, uncertainty, and information constraints as well as behaviors stemming from quantization, data-sampling, and impulses. Delivering a systematic review of the nonlinear small-gain theorems, the text: Supplies novel cyclic-small-gain theorems for large-scale nonlinear dynamic networks Offers a cyclic-small-gain framework for nonlinear control with static or dynamic quantization Contains a combination of cyclic-small-gain and set-valued map designs for robust control of nonlinear uncertain systems subject to sensor noise Presents a cyclic-small-gain result in directed graphs and distributed control of nonlinear multi-agent systems with fixed or dynamically changing topology Based on the authors’ recent research, Nonlinear Control of Dynamic Networks provides a unified framework for robust, quantized, and distributed control under information constraints. Suggesting avenues for further exploration, the book encourages readers to take into consideration more communication and networking issues in control designs to better handle the arising challenges.