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Complex Dynamic System Modelling, Identification and Control
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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.
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Keywords
- accident causality network
- active diagnosis
- active reconfiguration
- actuator fault
- adaptive fixed-time
- adaptive fixed-time control
- Automatic control
- Bayesian LSTM
- bifurcation
- big measurement data
- CDM
- CEEMDAN
- chaos synchronization
- chaos theory
- chi-square test
- cluster-delay mean square consensus
- cobalt removal process
- constrained parameter estimation
- constrained systems
- coupling
- critical hazard identification
- data reconciliation
- deep convolutional neural network
- deep fusion predictor
- DFA
- dynamic inversion
- fault diagnosis
- Fault tolerance
- feeding composition
- flexible spacecraft
- FlowDroid
- gain adjustment
- global reconstrucability
- gross error detection
- History of engineering & technology
- improved wavelet threshold
- impulse time windows
- impulsive control
- integer programming
- interconnected system
- Internal Model Control (IMC)
- interpolation control
- invariance entropy
- Linear Programming
- local reconstrucability
- local unknown input
- measurement noise
- mechanistic kinetic model
- meteorological data
- MIMO
- MPE
- multi-agent systems
- multi-sensor system
- multiplicative adaptation
- mutual information
- n/a
- Neural Network
- neural network control
- nonlinear interconnected systems
- Parameter estimation
- permission
- prevent oscillations
- PSO
- QPSO
- railway accident prevention
- reduce-order uncertain observer
- robot joints
- Robust control
- robust controller
- robust estimator
- robust stability
- rolling bearing fault
- sensor fault
- series causality analysis
- signal denoising
- spectral damping
- stabilization
- static detection
- stochastic disturbances
- strict-feedback high-order nonlinear systems
- structured control
- SVM
- Technology, engineering, agriculture
- Technology: general issues
- Two-Degree-of-Freedom IMC (TDF-IMC)
- U-model
- U-model-based control (U-control)
- variational mode decomposition
- X-ray pulsar
Links
DOI: 10.3390/books978-3-0365-7660-2Editions