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Special Issue "Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes"
Deadline for manuscript submissions: 31 December 2019.
Dr. Zhiwei Gao Website E-Mail
Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
Interests: power conversion systems; machine learning; intelligent optimization; condition monitoring; tolerant control; wind turbine systems
Complex industrial automation systems/processes, such as chemical processes, manufacturing systems, wireless network systems, power and energy systems, smart grids and so forth, have greatly contributed to our daily life. However, in a complicated engineering system or industrial process, due to the dynamic environment, a huge amount of energy, the complexity of mechanisms, coupling and interactions among modules and other factors, it has created challenges for condition monitoring, control and optimization applications. On the other hand, complex engineering systems are rather expensive, with a high requirement for system reliability and control performance. As a result, there has been increasing demand in the complex industries to develop reliable condition monitoring techniques to monitor real-time system status, and promote advanced optimization algorithms and resilient control methods to ensure the desired control and operation performance. Recently, artificial intelligence, data-driven techniques, cyber–physical systems, and cloud and cognitive computation have further stimulated research and applications of monitoring, optimization and control techniques.
The Special Issue on "Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes" aims to provide a platform for researchers and engineers to report their recent results, exchange research ideas, and overlook emerging research and application directions in condition monitoring, optimization and advanced control for complex industrial processes.
Potential topics include, but are not limited to, the following:
- Complex dynamic analysis of industrial processes
- Condition monitoring techniques
- Machine learning-based diagnosis and prognosis algorithms
- Advanced optimization methodologies
- Resilience of cyber–physical systems
- Advanced control algorithms and robustness analysis with applications
- Accelerating multiscale dynamic simulations of industrial processes
- Validation and real-time applications
Dr. Zhiwei Gao
Prof. Dr. Michael Z. Chen
Dr. Dapeng Zhang
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Please note that for papers submitted after 31 December 2019 an APC of 1400 CHF applies. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- condition monitoring
- advanced control
- complex industrial processes
- dynamic analysis
- and real-time validation and applications