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Condizione: New.

Condizione: As New. Unread book in perfect condition.

Taschenbuch. Condizione: Neu. Neuware - Doctoral Thesis / Dissertation from the year 2019 in the subject Engineering - General, Basics, grade: A.00, , language: English, abstract: The following text examines the questions, how nonlinear system can better be controlled by new optimisation techniques such as feedback linearization.Due to the inevitable nonlinearities in real systems, several nonlinear control methods like feedback linearization, sliding mode control, backstepping approach and further modes are described in detail in the literature. Due to limitations in application of well known classical methods, researchers have struggled for decades to realize robust and practical solutions for nonlinear systems by proposing different approaches or improving classical control methods.The feedback linearization approach is a control method which employs feedback to stabilize systems containing nonlinearities. In order to accomplish this, it assumes perfect knowledge of the system model to linearize the input-output relationship. In the absence of perfect system knowledge, modelling errors inevitably affect the performanceof the feedback controller. Many researchers have come up with a new form of feedback linearization, called robust feedback. This method gives a linearizing control law that transforms the nonlinear system into its linear approximation around an operating point. Thus, it causes only a small transformation in the natural behavior of the system, which is desired in order to obtain robustness.The controllers are required to provide various time domain and frequency domain performances while maintaining sufficient stability robustness. In this regard, the evolutionary optimization techniques provide better option as these are probabilistic search procedures and facilitate inclusion of wide variety of time and frequency domain performance functionals in the objective functions. A significant scope of work remains to be done which provides motivation for the research in the design of robust controllers using evolutionary optimization. Also, emerging techniques using LMI also find potential in controller design for feedback linearized systems.The thrust of the study here is to design robust controllers for nonlinear systems using Evolutionary optimization and LMI.Furthermore, latest control methods for nonlinear system have been studied, deeply, in this thesis. Combining feedback linearization with non linear disturbance observer based control (NDOBC) obtains promising disturbance rejection and reference tracking performance as compared to other robust control methods.…

Condizione: New. Vinay Bhatia is Professor and Head of the Department of Electronics and Communication Engineering at Chandigarh Engineering College (NBA Accredited), CGC Landran (NAAC A+), Punjab, India. He holds a B.Tech, M.Tech, and Ph.D in Electronic.

Condizione: New. Vinay Bhatia is Professor and Head of the Department of Electronics and Communication Engineering at Chandigarh Engineering College (NBA Accredited), CGC Landran (NAAC A+), Punjab, India. He holds a B.Tech, M.Tech, and Ph.D in Electronic.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Doctoral Thesis / Dissertation from the year 2019 in the subject Engineering - General, Basics, grade: A.00, , language: English, abstract: The following text examines the questions, how nonlinear system can better be controlled by new optimisation techniques such as feedback linearization.Due to the inevitable nonlinearities in real systems, several nonlinear control methods like feedback linearization, sliding mode control, backstepping approach and further modes are described in detail in the literature. Due to limitations in application of well known classical methods, researchers have struggled for decades to realize robust and practical solutions for nonlinear systems by proposing different approaches or improving classical control methods.The feedback linearization approach is a control method which employs feedback to stabilize systems containing nonlinearities. In order to accomplish this, it assumes perfect knowledge of the system model to linearize the input-output relationship. In the absence of perfect system knowledge, modelling errors inevitably affect the performanceof the feedback controller. Many researchers have come up with a new form of feedback linearization, called robust feedback. This method gives a linearizing control law that transforms the nonlinear system into its linear approximation around an operating point. Thus, it causes only a small transformation in the natural behavior of the system, which is desired in order to obtain robustness.The controllers are required to provide various time domain and frequency domain performances while maintaining sufficient stability robustness. In this regard, the evolutionary optimization techniques provide better option as these are probabilistic search procedures and facilitate inclusion of wide variety of time and frequency domain performance functionals in the objective functions. A significant scope of work remains to be done which provides motivation for the research in the design of robust controllers using evolutionary optimization. Also, emerging techniques using LMI also find potential in controller design for feedback linearized systems.The thrust of the study here is to design robust controllers for nonlinear systems using Evolutionary optimization and LMI.Furthermore, latest control methods for nonlinear system have been studied, deeply, in this thesis. Combining feedback linearization with non linear disturbance observer based control (NDOBC) obtains promising disturbance rejection and reference tracking performance as compared to other robust control methods. 176 pp. Englisch.…

Paperback. Condizione: new. Paperback. The book highlights emerging developments in intelligent computing, communication technologies, robotics, embedded systems, and data-driven innovations that are shaping the future of smart and autonomous systems.This volume brings together multidisciplinary research focusing on artificial intelligence, computational intelligence, smart communication systems, embedded and VLSI technologies, robotics, automation, cybersecurity, cloud computing, data analytics, IoT-enabled platforms, and intelligent decision-making systems. The book explores innovative methodologies, mathematical models, and practical applications that support next-generation technological ecosystems. Contributions include theoretical advancements, simulation-based studies, experimental implementations, and industrial applications in smart environments and AI-integrated systems. The book also discusses recent trends in machine learning, predictive analytics, human-robot interaction, autonomous systems, and sustainable computing architectures, offering valuable insights into the rapidly evolving landscape of communication and computational sciences.The book is intended for researchers, academicians, scientists, industry professionals, postgraduate students, and practitioners working in the domains of artificial intelligence, communication engineering, computer science, robotics, embedded systems, electronics, and data analytics. It serves as a valuable reference for both academic research and industrial innovation. The book highlights emerging developments in intelligent computing, communication technologies, robotics, embedded systems, and data-driven innovations that are shaping the future of smart and autonomous systems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Doctoral Thesis / Dissertation from the year 2019 in the subject Engineering - General, Basics, grade: A.00, , language: English, abstract: The following text examines the questions, how nonlinear system can better be controlled by new optimisation techniques such as feedback linearization.Due to the inevitable nonlinearities in real systems, several nonlinear control methods like feedback linearization, sliding mode control, backstepping approach and further modes are described in detail in the literature. Due to limitations in application of well known classical methods, researchers have struggled for decades to realize robust and practical solutions for nonlinear systems by proposing different approaches or improving classical control methods.The feedback linearization approach is a control method which employs feedback to stabilize systems containing nonlinearities. In order to accomplish this, it assumes perfect knowledge of the system model to linearize the input-output relationship. In the absence of perfect system knowledge, modelling errors inevitably affect the performanceof the feedback controller. Many researchers have come up with a new form of feedback linearization, called robust feedback. This method gives a linearizing control law that transforms the nonlinear system into its linear approximation around an operating point. Thus, it causes only a small transformation in the natural behavior of the system, which is desired in order to obtain robustness.The controllers are required to provide various time domain and frequency domain performances while maintaining sufficient stability robustness. In this regard, the evolutionary optimization techniques provide better option as these are probabilistic search procedures and facilitate inclusion of wide variety of time and frequency domain performance functionals in the objective functions. A significant scope of work remains to be done which provides motivation for the research in the design of robust controllers using evolutionary optimization. Also, emerging techniques using LMI also find potential in controller design for feedback linearized systems.The thrust of the study here is to design robust controllers for nonlinear systems using Evolutionary optimization and LMI. Furthermore, latest control methods for nonlinear system have been studied, deeply, in this thesis. Combining feedback linearization with non linear disturbance observer based control (NDOBC) obtains promising disturbance rejection and reference tracking performance as compared to other robust control methods.GRIN Publishing GmbH, Waltherstraße 23, 80337 München 176 pp. Englisch.…

Taschenbuch. Condizione: Neu. How Can Robust Control of Nonlinear Systems be Achieved? Examining Optimization Techniques | Bhawna Tandon | Taschenbuch | 176 S. | Englisch | 2019 | GRIN Verlag | EAN 9783346038661 | Verantwortliche Person für die EU: GRIN Publishing GmbH, Waltherstr. 23, 80337 München, info[at]grin[dot]com | Anbieter: preigu Print on Demand.…

Paperback. Condizione: new. Paperback. The book highlights emerging developments in intelligent computing, communication technologies, robotics, embedded systems, and data-driven innovations that are shaping the future of smart and autonomous systems.This volume brings together multidisciplinary research focusing on artificial intelligence, computational intelligence, smart communication systems, embedded and VLSI technologies, robotics, automation, cybersecurity, cloud computing, data analytics, IoT-enabled platforms, and intelligent decision-making systems. The book explores innovative methodologies, mathematical models, and practical applications that support next-generation technological ecosystems. Contributions include theoretical advancements, simulation-based studies, experimental implementations, and industrial applications in smart environments and AI-integrated systems. The book also discusses recent trends in machine learning, predictive analytics, human-robot interaction, autonomous systems, and sustainable computing architectures, offering valuable insights into the rapidly evolving landscape of communication and computational sciences.The book is intended for researchers, academicians, scientists, industry professionals, postgraduate students, and practitioners working in the domains of artificial intelligence, communication engineering, computer science, robotics, embedded systems, electronics, and data analytics. It serves as a valuable reference for both academic research and industrial innovation. The book highlights emerging developments in intelligent computing, communication technologies, robotics, embedded systems, and data-driven innovations that are shaping the future of smart and autonomous systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…