Advanced Intelligent Control Algorithms for Power, Energy, and Cyber-Physical Systems
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".
Deadline for manuscript submissions: 31 August 2026 | Viewed by 4
Special Issue Editors
Interests: heuristic optimization algorithms; constrained optimization; permanent magnet machines; hybrid optimization algorithms
Special Issues, Collections and Topics in MDPI journals
Interests: renewable energy sources; artificial intelligence and optimization algorithms
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Modern engineering systems—including large-scale power grids, smart manufacturing platforms, autonomous vehicles, and interconnected cyber-physical networks—are rapidly increasing in complexity and intelligence. These systems demand advanced control methodologies capable of addressing nonlinear dynamics, uncertainties, large-scale interactions, and data-rich environments. Traditional control frameworks alone are no longer sufficient to ensure stability, resilience, and optimal performance.
This Special Issue aims to bring together high-impact research on intelligent, adaptive, and learning-based control algorithms designed to optimize, coordinate, and secure complex engineering systems. A particular emphasis is placed on load frequency control (LFC) in modern power systems, not only as a benchmark problem but also as a gateway to understanding control challenges in broader multi-domain networked infrastructures.
The novelty of this Special Issue lies in its integration of AI, machine learning, and intelligent optimization with contemporary control theory—an area gaining significant momentum yet lacking a unified scholarly focus. Contributions that explore emerging domains such as autonomous systems, cyber-physical resilience, network-aware control, and real-time learning-based decision systems are especially encouraged.
Submissions may include original research, comprehensive reviews, or application-oriented studies that demonstrate methodological advances, cross-domain applicability, or real-time implementation insights. Potential areas for this Special Issue include, but are not limited to, the following:
- Intelligent & Learning-Based Control Algorithms
- Power, Energy, and Renewable Systems Control
- Intelligent Control for Autonomous and Networked Systems
- Cyber-Physical Systems, Resilience, and Security
- Theory, Analysis, and Real-Time Implementation
Dr. Łukasz Knypiński
Dr. Ramesh Devarapalli
Dr. Bathina Venkateswara Rao
Guest Editors
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 submissions that pass pre-check are 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 250 words) can be sent to the Editorial Office for assessment.
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 1800 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.
Keywords
- intelligent control learning-based and data-driven control
- adaptive and robust control
- reinforcement learning in control
- neural network and hybrid
- AI controllers
- fuzzy logic and neuro-fuzzy control
- metaheuristic and evolutionary optimization
- load frequency control (LFC)
- smart grids and distributed energy resources
- distributed and decentralized control
- multi-agent coordination
- network-aware and event-triggered control
- model predictive control (MPC)
- cyber-physical systems and resilience
- autonomous and robotic systems
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