Complex Dynamic System Modelling, Identification and Control

• Other Authors: Zhu, Quanmin (Editor), Fusco, Giuseppe (Editor), Na, Jing (Editor), Zhang, Weicun (Editor), Azar, Ahmad Taher (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
• Subjects: Technology: general issues; History of engineering & technology; Internal Model Control (IMC); U-model; U-model-based control (U-control); Two-Degree-of-Freedom IMC (TDF-IMC); dynamic inversion; invariance entropy; automatic control; mutual information; static detection; Chi-square test; permission; FlowDroid; series causality analysis; Bayesian LSTM; multi-sensor system; meteorological data; big measurement data; deep fusion predictor; cobalt removal process; mechanistic kinetic model; parameter estimation; constrained parameter estimation; data reconciliation; robust estimator; gross error detection; feeding composition; fault diagnosis; sensor fault; actuator fault; deep convolutional neural network; robot joints; railway accident prevention; critical hazard identification; accident causality network; integer programming; active diagnosis; active reconfiguration; constrained systems; fault tolerance; interpolation control; linear programming; structured control; flexible spacecraft; prevent oscillations; adaptive fixed-time control; neural network control; strict-feedback high-order nonlinear systems; cluster-delay mean square consensus; multi-agent systems; stochastic disturbances; impulse time windows; impulsive control; multiplicative adaptation; gain adjustment; spectral damping; robust stability; local unknown input; interconnected system; local reconstrucability; global reconstrucability; reduce-order uncertain observer; chaos theory; bifurcation; stabilization; chaos synchronization; robust control; rolling bearing fault; CEEMDAN; DFA; improved wavelet threshold; QPSO; MPE; SVM; adaptive fixed-time; neural network; nonlinear interconnected systems; X-ray pulsar; signal denoising; variational mode decomposition; MIMO; coupling; PSO; CDM; measurement noise; robust controller; n/a
• Online Access: DOAB: download the publication; DOAB: description of the publication

The study of complex dynamic systems has become increasingly important in recent years due to its wide range of applications in fields such as engineering, physics, economics, and biology. These systems are characterized by their interconnectedness, nonlinearities, and feedback loops, which make them difficult to understand and control. As a result, there has been growing interest in developing tools and techniques for the modelling, identification, and control of complex dynamic systems.The aim of this reprint is to provide an overview of the state-of-the-art methods for the modelling, identification, and control of complex dynamic systems. This reprint covers a wide range of topics, including system identification, model-based control, adaptive control, nonlinear control, and predictive control. It also includes case studies and examples from different fields to demonstrate the practical application of these methods.This reprint is intended for researchers, graduate students, and practitioners in the field of control systems. It assumes a basic understanding of linear systems theory, calculus, and linear algebra. Overall, this reprint provides a comprehensive and up-to-date overview of the methods for the modelling, identification, and control of complex dynamic systems.