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Special Issue "Algorithms for PID Controller 2019"
A special issue of Algorithms (ISSN 1999-4893).
Deadline for manuscript submissions: closed (30 December 2019).
Interests: Computational Intelligence and Evolutionary computation, Fuzzy systems, Fuzzy control and modelling, Fuzzy cognitive maps and Petri nets in decision support systems, Intelligent control, Time series prediction, Automation systems in renewable energy resources, Intelligent energy management systems and smart buildings, Design and management of autonomous smart micro grids, Power electronics in photovoltaic systems, Control electrochromic devices, Modelling and control of reverse osmosis desalination
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Special Issue in Energies: Intelligent Decentralized Energy Management in Microgrids
Special Issue in Energies: Intelligent Control in Energy Systems Ⅱ
Special Issue in Applied Sciences: Artificial Intelligence in Smart Buildings
The conventional PID (Proportional–Integral–Derivative) controllers are most widely used in industrial applications because of their simple, robust, cheap, and good performances. To date, the PID control performance remains limited. The requirements for control precision have become higher, and the real systems have become more complex, including higher order, time-delayed linear, nonlinear systems, and systems without a mathematical model and uncertainties. The goal of control algorithms is to determine the optimal PID controller parameters. Practically, all PID controllers made today are based on microprocessors. This has created opportunities to provide additional features, such as automatic tuning, gain scheduling, and continuous adaptation. In addition to the conventional approaches such as the Lyapunov approach and PID control system analysis, there are more advanced and intelligent algorithms for PID tuning methods and metaheuristic algorithms, such as the Genetic Algorithm, Particle Swarm Optimization, Ant Colony Optimization, Big Bang–Big Crunch, etc. In addition, sophisticated control strategies, such as predictive control, self-tuning methods, fuzzy and neural algorithms, are designed to overcome the problems associated with the regulation of PID controller gains.
Prof. Dr. Anastasios Dounis
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. Algorithms 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 1000 CHF (Swiss Francs). 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.
- Evolutionary PID control
- Adaptive fuzzy PID control
- Robust PID algorithms
- Uncertainty of PID algorithm
- Predictive control
- Interval type-2 fuzzy PID controller
- Reinforcement learning algorithm
- Sliding mode
- Lyapunov approach
- Kalman filtering