This book covers new aspects and frameworks of control, design, and optimization based on the TP model transformation and its various extensions. The author outlines the three main steps of polytopic and LMI based control design: 1) development of the qLPV state-space model, 2) generation of the polytopic model; and 3) application of LMI to derive controller and observer. He goes on to describe why literature has extensively studied LMI design, but has not focused much on the second step, in part because the generation and manipulation of the polytopic form was not tractable in many cases. The author then shows how the TP model transformation facilitates this second step and hence reveals new directions, leading to powerful design procedures and the formulation of new questions. The chapters of this book, and the complex dynamical control tasks which they cover, are organized so as to present and analyze the beneficial aspect of the family of approaches (control, design, and optimization). Additionally, the book aims to convey simple TP modeling; a new convex hull manipulation based possibilities for optimization; a general framework for stability analysis; standardized modeling and system description; relaxed and universal LMI based design framework; and a gateway to time-delayed systems.

The TP and TS Fuzzy model transformation based control design has revolutionized the field of control design by introducing a highly effective approach. Through the TP model transformation, it has become evident that the design of controllers and observers, as well as the effectiveness of applied LMIs, are greatly influenced by the shape of the antecedent Fuzzy sets and the number and location of the consequent systems. Furthermore, the TP model transformation has revealed that the sensitivity of controller and observer design differs in nature. This implies that the overseer and controller design require different TS Fuzzy model representations of the system at hand. This book offers a comprehensive exploration of this phenomenon. The book introduces several new theoretical advancements in the TP or TS Fuzzy model transformation based control design framework. It presents a complete framework for TP and TS Fuzzy model transformation and offers various tools based on this approach to enhance control design effectiveness. The book introduces novel theoretical concepts, such as interpolation between alternative TS Fuzzy model representations, which leads to a new optimization framework. It also explores methods to achieve further complexity reduction beyond rank minimization. Additionally, the book addresses the execution of TS Fuzzy model transformation for large-sized problems and demonstrates how to reinforce various properties of antecedent Fuzzy sets through manipulation. Practical hints and guidance for control design is provided throughout the book, with examples illustrating the application of novel solutions. Matlab codes are also included to facilitate the implementation of the proposed methods.

Tensor Product Model Transformation in Polytopic Model-Based Control offers a new perspective of control system design. Instead of relying solely on the formulation of more effective LMIs, which is the widely adopted approach in existing LMI-related studies, this cutting-edge book calls for a systematic modification and reshaping of the polytopic convex hull to achieve enhanced performance. Varying the convexity of the resulting TP canonical form is a key new feature of the approach. The book concentrates on reducing analytical derivations in the design process, echoing the recent paradigm shift on the acceptance of numerical solution as a valid form of output to control system problems. The salient features of the book include: Presents a new HOSVD-based canonical representation for (qLPV) models that enables trade-offs between approximation accuracy and computation complexity Supports a conceptually new control design methodology by proposing TP model transformation that offers a straightforward way of manipulating different types of convexity to appear in polytopic representation Introduces a numerical transformation that has the advantage of readily accommodating models described by non-conventional modeling and identification approaches, such as neural networks and fuzzy rules Presents a number of practical examples to demonstrate the application of the approach to generate control system design for complex (qLPV) systems and multiple control objectives. The authors’ approach is based on an extended version of singular value decomposition applicable to hyperdimensional tensors. Under the approach, trade-offs between approximation accuracy and computation complexity can be performed through the singular values to be retained in the process. The use of LMIs enables the incorporation of multiple performance objectives into the control design problem and assurance of a solution via convex optimization if feasible. Tensor Product Model Transformation in Polytopic Model-Based Control includes examples and incorporates MATLAB® Toolbox TPtool. It provides a reference guide for graduate students, researchers, engineers, and practitioners who are dealing with nonlinear systems control applications.

Nature-inspired Optimization Algorithms for Fuzzy Controlled Servo Systems explains fuzzy control in servo systems in a way that doesn't require any solid mathematical prerequisite. Analysis and design methodologies are covered, along with specific applications to servo systems and representative case studies. The theoretical approaches presented throughout the book are validated by the illustration of digital simulation and real-time experimental results. This book is a great resource for a wide variety of readers, including graduate students, engineers (designers, practitioners and researchers), and everyone who faces challenging control problems.

This book gathers contributions on fuzzy neural control, intelligent and non-linear control, dynamic systems and cyber-physical systems. It presents the latest theoretical and practical results, including numerous applications of computational intelligence in various disciplines such as engineering, medicine, technology and the environment. The book is dedicated to Imre J. Rudas on his seventieth birthday.

Regardless of the field or discipline, technology is rapidly advancing, and individuals are faced with the challenge of adapting to these new innovations. To remain up-to-date on the current practices, teachers and administrators alike must constantly stay informed of the latest advances in their fields. Teacher Training and Professional Development: Concepts, Methodologies, Tools, and Applications contains a compendium of the latest academic material on the methods, skills, and techniques that are essential to lifelong learning and professional advancement. Including innovative studies on teaching quality, pre-service teacher preparation, and faculty enrichment, this multi-volume book is an ideal source for academics, professionals, students, practitioners, and researchers.

Metacognition plays an important role in numerous aspects of higher educational learning strategies. When properly integrated in the educational system, schools are better equipped to build more efficient and successful learning strategies for students in higher education. Metacognition and Successful Learning Strategies in Higher Education is a detailed resource of scholarly perspectives that discusses current trends in learning assessments. Featuring extensive coverage on topics such as spiritual intelligence strategies, literacy development, and ubiquitous learning, this is an ideal reference source for academicians, graduate students, practitioners, and researchers who want to improve their learning strategies using metacognition studies.