Complex Dynamic System Modelling, Identification and Control

Dear Colleagues,

Systems are naturally or purposely formed with functional components and connection structures. The complicities could be induced from nonlinearity, dynamics, time delay, uncertainties, disturbances, irreversible processes, and those characteristics generally explained in the other literature.

Modeling is an innate intuition for humans to find rules or mechanisms of phenomena (a process/plant in a human-made system or a natural system such as earth's global climate, organisms, and the human brain) This is generally fitted with the journal titled research – Entropy, as the idea of entropy provides a mathematical way to encode/model the intuitive notion of which processes are obviously complex due to the irreversible characteristics, even though they would not violate the fundamental law of conservation of energy

There are two predominant approaches to establish models, principle (e.g., information theory, statistic physics, statistical mechanics, etc.) based analytical equations and data (measured and simulated) driven input/output fitted set of regression numerical polynomials (most commonly called identification).

Control is a way to improve a system behavior/performance by adding additional functional components and revising system structure to form a closed-loop framework with adaptation and robustness to the uncertainties.

Accordingly, modeling, identification, and control (MIC) is a cross-discipline from all engineering (human-made) systems to all the natural scientific research discoveries.

This Special Issue is encouraging those emerging insights and approaches to provide concise/effective solutions in complex dynamic system modeling, identification, and control. The philosophy embedded in the S.I. is to seek simplicity (solutions) from complicity (problems).

This Special Issue is a forum for presenting new and improved insight, methodologies, and techniques of MIC for complex systems that are challenging for research and (potential) significant for a wide range of applications in the real-world natural and engineering domains. Fundamentally, the papers should justify why the works have not been undertaken by the other colleagues and what the bottleneck issues have been the barriers for such research progression and applications.

Prof. Dr. Quan Min Zhu
Prof. Giuseppe Fusco
Prof. Dr. Jing Na
Dr. Weicun Zhang
Prof. Dr. Ahmad Taher Azar
Guest Editors

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