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Control of Nonlinear Systems
The book Control of Nonlinear Systems–Stability and Performance fills a crucial gap in the field of nonlinear control systems by providing a comprehensive yet accessible treatment of the subject. Unlike many existing texts that are either too complex for beginners or omit essential topics, this book strikes the right balance of mathematical rigor and practicality. The main objective of the book is to simplify and unify the existing techniques for designing and analyzing control systems for nonlinear systems. It aims to alleviate confusion and difficulty in understanding these methods, making it an invaluable resource for students, researchers, and practitioners in the field. By presenting ...
Applications of Computational Intelligence
This book constitutes the refereed proceedings of the 5th IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2022, held in Cali, Colombia during July 27–29, 2022. The 7 extended papers included in this book were carefully reviewed and selected from 38 submissions. They were organized in topical sections as follows: Design of a segmentation and classification system for seed detection based on pixel intensity thresholds and convolutional neural networks.
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...
Adaptive Control of Dynamic Systems with Uncertainty and Quantization
This book presents a series of innovative technologies and research results on adaptive control of dynamic systems with quantization, uncertainty, and nonlinearity, including the theoretical success and practical development such as the approaches for stability analysis, the compensation of quantization, the treatment of subsystem interactions, and the improvement of system tracking and transient performance. Novel solutions by adopting backstepping design tools to a number of hotspots and challenging problems in the area of adaptive control are provided. In the first three chapters, the general design procedures and stability analysis of backstepping controllers and the basic descriptions a...
Optimal Event-Triggered Control Using Adaptive Dynamic Programming
Optimal Event-triggered Control using Adaptive Dynamic Programming discusses event triggered controller design which includes optimal control and event sampling design for linear and nonlinear dynamic systems including networked control systems (NCS) when the system dynamics are both known and uncertain. The NCS are a first step to realize cyber-physical systems (CPS) or industry 4.0 vision. The authors apply several powerful modern control techniques to the design of event-triggered controllers and derive event-trigger condition and demonstrate closed-loop stability. Detailed derivations, rigorous stability proofs, computer simulation examples, and downloadable MATLAB® codes are included f...
Modern Computational Techniques for Engineering Applications
Modern Computational Techniques for Engineering Applications presents recent computational techniques used in the advancement of modern grids with the integration of non-conventional energy sources like wind and solar energy. It covers data analytics tools for smart cities, smart towns, and smart computing for sustainable development. This book- Discusses the importance of renewable energy source applications wind turbines and solar panels for electrical grids. Presents optimization-based computing techniques like fuzzy logic, neural networks, and genetic algorithms that enhance the computational speed. Showcases cloud computing tools and methodologies such as cybersecurity testbeds and data...
Maneuverable Formation Control in Constrained Space
Inspired by the community behaviors of animals and humans, cooperative control has been intensively studied by numerous researchers in recent years. Cooperative control aims to build a network system collectively driven by a global objective function in a distributed or centralized communication network and shows great application potential in a wide domain. From the perspective of cybernetics in network system cooperation, one of the main tasks is to design the formation control scheme for multiple intelligent unmanned systems, facilitating the achievements of hazardous missions – e.g., deep space exploration, cooperative military operation, and collaborative transportation. Various chall...
Variable Gain Control and Its Applications in Energy Conversion
The variable gain control method is a new construction technique for the control of nonlinear systems. By properly conducting state transformation that depends on the variable gains, the control design problem of nonlinear systems can be transformed into a gain construction problem, thus effectively avoiding the tedious iterative design procedure. Different from the classical backstepping method and forwarding design method, the structure of variable gain control is simpler in the sense that fewer design parameters are required, facilitating the improvement of system control performance. To highlight the learning, research, and promotion of variable gain control, Variable Gain Control and It...
16th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2021)
This book of Advances in Intelligent and Soft Computing contains accepted papers presented at SOCO 2021 conference held in the beautiful and historic city of Bilbao (Spain), in September 2021. Soft computing represents a collection or set of computational techniques in machine learning, computer science, and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a through peer-review process, the 16th SOCO 2021 International Program Committee selected 78 papers which are published in these conference proceedings and represents an acceptance rate of 48%. In this relevant edition, a special emphasis is put on the organization of special ...
