Описание: This book mainly deals with grassland digitalization and recognition through computer vision, which will make contributions to implement of grass auto recognition and data acquisition.
Описание: This book focuses on the implementation, evaluation and application of DNA/RNA-based genetic algorithms in connection with neural network modeling, fuzzy control, the Q-learning algorithm and CNN deep learning classifier.
Описание: This book focuses on the implementation, evaluation and application of DNA/RNA-based genetic algorithms in connection with neural network modeling, fuzzy control, the Q-learning algorithm and CNN deep learning classifier.
Описание: The objective of this dissertation is to advance the state-of-the-art in the kinematic modeling, identification, and control of robotic manipulators with rigid links in an effort to improve robot kinematic performance.
Автор: Yiannis Boutalis; Dimitrios Theodoridis; Theodore Название: System Identification and Adaptive Control ISBN: 3319063634 ISBN-13(EAN): 9783319063638 Издательство: Springer Рейтинг: Цена: 22203.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control.
Описание: Modelling and system identification.- Advanced control methods.- Signal processing for condition monitoring and fault diagnosis.- Applications.
Автор: Yiannis Boutalis; Dimitrios Theodoridis; Theodore Название: System Identification and Adaptive Control ISBN: 3319354124 ISBN-13(EAN): 9783319354125 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control.
Описание: The objective of this dissertation is to advance the state-of-the-art in the kinematic modeling, identification, and control of robotic manipulators with rigid links in an effort to improve robot kinematic performance.
Автор: Duc T. Pham; Xing Liu Название: Neural Networks for Identification, Prediction and Control ISBN: 1447132467 ISBN-13(EAN): 9781447132462 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In recent years, there has been a growing interest in applying neural networks to dynamic systems identification (modelling), prediction and control. The neural network types considered in detail are the muhilayer perceptron (MLP), the Elman and Jordan networks and the Group-Method-of-Data-Handling (GMDH) network.
Описание: This book presents the most important findings from the 9th International Conference on Modelling, Identification and Control (ICMIC’17), held in Kunming, China on July 10–12, 2017. It covers most aspects of modelling, identification, instrumentation, signal processing and control, with a particular focus on the applications of research in multi-agent systems, robotic systems, autonomous systems, complex systems, and renewable energy systems.The book gathers thirty comprehensively reviewed and extended contributions, which help to promote evolutionary computation, artificial intelligence, computation intelligence and soft computing techniques to enhance the safety, flexibility and efficiency of engineering systems. Taken together, they offer an ideal reference guide for researchers and engineers in the fields of electrical/electronic engineering, mechanical engineering and communication engineering.
This book includes original, peer-reviewed research papers from the 11th International Conference on Modelling, Identification and Control (ICMIC2019), held in Tianjin, China on July 13-15, 2019. The topics covered include but are not limited to: System Identification, Linear/Nonlinear Control Systems, Data-driven Modelling and Control, Process Modelling and Process Control, Fault Diagnosis and Reliable Control, Intelligent Systems, and Machine Learning and Artificial Intelligence.
The papers showcased here share the latest findings on methodologies, algorithms and applications in modelling, identification, and control, integrated with Artificial Intelligence (AI), making the book a valuable asset for researchers, engineers, and university students alike.
Автор: Ruiyun Qi; Gang Tao; Bin Jiang Название: Fuzzy System Identification and Adaptive Control ISBN: 3030198812 ISBN-13(EAN): 9783030198817 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Нет в наличии.
Описание: This book provides readers with a systematic and unified framework for identification and adaptive control of Takagi–Sugeno (T–S) fuzzy systems. Its design techniques help readers applying these powerful tools to solve challenging nonlinear control problems. The book embodies a systematic study of fuzzy system identification and control problems, using T–S fuzzy system tools for both function approximation and feedback control of nonlinear systems. Alongside this framework, the book also: introduces basic concepts of fuzzy sets, logic and inference system; discusses important properties of T–S fuzzy systems; develops offline and online identification algorithms for T–S fuzzy systems; investigates the various controller structures and corresponding design conditions for adaptive control of continuous-time T–S fuzzy systems; develops adaptive control algorithms for discrete-time input–output form T–S fuzzy systems with much relaxed design conditions, and discrete-time state-space T–S fuzzy systems; and designs stable parameter-adaptation algorithms for both linearly and nonlinearly parameterized T–S fuzzy systems. The authors address adaptive fault compensation problems for T–S fuzzy systems subject to actuator faults. They cover a broad spectrum of related technical topics and to develop a substantial set of adaptive nonlinear system control tools. Fuzzy System Identification and Adaptive Control helps engineers in the mechanical, electrical and aerospace fields, to solve complex control design problems. The book can be used as a reference for researchers and academics in nonlinear, intelligent, adaptive and fault-tolerant control.
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