Journal Information

Control Engineering Practice

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Impact Factor:
5.3
Publisher:
Elsevier
ISSN:
0967-0661
Viewed:
40857
Tracked:
3

Call For Papers

Control Engineering Practice is an academic journal published by Elsevier. (ISSN 0967-0661, impact factor 5.3).

Aims & Scope A journal of IFAC, The International Federation of Automatic Control. Control Engineering Practice strives to meet the needs of industrial practitioners and industrially related academics and researchers. It publishes papers which illustrate the direct application of control theory and its supporting tools in all possible areas of automation. As a result, the journal only contains papers which can be considered to have made significant contributions to the application of advanced control techniques. It is normally expected that practical results should be included, but where simulation only studies are available, it is necessary to demonstrate that the simulation model is representative of a genuine application. Strictly theoretical papers will find a more appropriate home in Control Engineering Practice's sister publication, Automatica. It is also expected that papers are innovative with respect to the state of the art and are sufficiently detailed for a reader to be able to duplicate the main results of the paper (supplementary material, including datasets, tables, code and any relevant interactive material can be made available and downloaded from the website). The benefits of the presented methods must be made very clear and the new techniques must be compared and contrasted with results obtained using existing methods. Moreover, a thorough analysis of failures that may happen in the design process and implementation can also be part of the paper. The scope of Control Engineering Practice matches the activities of IFAC. Papers demonstrating the contribution of automation and control in improving the performance, quality, productivity, sustainability, resource and energy efficiency, and the manageability of systems and processes for the benefit of mankind and are relevant to industrial practitioners are most welcome. Fields of applications in control and automation: •Automotive Systems •Aerospace Applications •Marine Systems •Intelligent Transportation Systems and Traffic Control •Autonomous Vehicles •Robotics •Human Machine Systems •Mechatronic Systems •Scientific Instrumentation •Micro- and Nanosystems •Fluid Power Systems •Gas Turbines and Fluid Machinery •Machine Tools •Manufacturing Technology and Production Engineering •Logistics •Power Electronics •Electrical Drives •Internet of Things •Communication Systems •Power and Energy Systems •Biomedical Engineering and Medical Applications •Biosystems and Bioprocesses •Biotechnology •Chemical Engineering •Pulp and Paper Processing •Mining, Mineral and Metal Processing •Water/Gas/Oil Reticulation Systems •Environmental Engineering •Agricultural Systems •Food Engineering •Other Emerging Control Applications Applicable methods, theories and technologies: •Modeling, Simulation and Experimental Model Validation •System Identification and Parameter Estimation •Observer Design and State Estimation •Soft Sensing •Sensor Fusion •Optimization •Adaptive and Robust Control •Learning Control •Nonlinear Control •Control of Distributed-Parameter Systems •Model-based Control Techniques •Optimal Control and Model Predictive Control •Controller Tuning •PID Control •Feedforward Control and Trajectory Planning •Networked Control •Stochastic Systems •Fault Detection and Isolation •Diagnosis and Supervision •Actuator and Sensor Design •Measurement Technology in Control •Software Engineering Techniques •Real-time and Distributed Computing •Intelligent Components and Instruments •Architectures and Algorithms for Control •Real-time Algorithms •Computer-aided Systems Analysis and Design •Implementation of Automation Systems •Machine Learning •Artificial Intelligence Techniques •Discrete Event and Hybrid Systems •Production Planning and Scheduling •Automation •Data Mining •Data Analytic •Performance Monitoring •Experimental Design •Other Emerging Control Theories and Related Technologies
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Special Issues

Special Issue on Precision Motion Systems and Control Submission Date: 2026-10-31 Precision motion systems play a vital role in numerous modern technologies, including semiconductor lithography, nanopositioning stages, atomic force microscopy (AFM), transmission and scanning electron microscopy (TEM/SEM), data storage systems, and active vibration isolation platforms. They are also increasingly critical in space-based precision instruments and ultra-high-resolution metrology systems operating under extreme conditions, where reliability and stability must be maintained in environments such as vacuum, radiation, and large thermal variations. These systems demand nanometer- to picometer-level accuracy, high bandwidth, and robust performance under disturbances and uncertainties—making them a central focus in the fields of advanced control, system modeling, and mechatronic design. This special issue aims to bring together recent advances in the design, modeling, actuation, and control of precision motion systems. With growing demands for fast and accurate motion in fields such as photonics, biomedical devices, robotics, advanced manufacturing, and space technologies, the topic is of high relevance to both academic researchers and industry practitioners. Topics of interest include, but are not limited to: Advanced control strategies for precision motion systems, such as reset control, hybrid control, active damping control, data-driven control, active disturbance rejection control, and sliding mode control Linear and nonlinear loop-shaping methods, as well as optimal control techniques for achieving high bandwidth and robust disturbance rejection Advanced feedforward techniques, including AI-driven feedforward, repetitive control, and iterative learning control (ILC) Frequency-domain system identification for MIMO systems, including nonlinear modeling of hysteresis, friction, and related effects Actuation and drive system design, including electromagnetic and piezoelectric actuators (Opto)mechatronic system co-design for high-performance motion systems Experimental validation and industrial case studies in high-precision applications, such as: Precision microscopy systems (e.g., AFM, SEM, TEM), where nanometer- and sub-nanometer-level positioning accuracy is required Nanopositioning platforms using electromagnetic and piezoelectric actuation for ultra-fine motion control Active vibration isolation systems for suppressing disturbances in highly sensitive precision environments Adaptive optics and other motion-critical instruments requiring high stability, accuracy, and bandwidth Space-based and space-compatible precision systems, where robustness under extreme conditions (e.g., vacuum, thermal variations, radiation) is essential Ultra-high-resolution metrology systems operating under extreme conditions, including applications demanding picometer-level resolution and stability These applications operate at the limits of precision engineering, requiring exceptional accuracy, high bandwidth, and robust disturbance rejection under challenging environmental conditions. Guest editors: Dr. Hassan HosseinNia Delft University of Technology, Delft, Netherlands Dr. Lei Zhou University of Wisconsin-Madison, Madison, United States Dr. Shota Yabui Tokyo City University, Tokyo, Japan Dr. Masahiro Mae The University of Tokyo, Tokyo, Japan Dr. Sumeet S Aphale University of Aberdeen, Aberdeen, United Kingdom Dr. Minkyun Noh Korea Advanced Institute of Science and Technology, Daejeon, South Korea Manuscript submission information: Open for Submission: from 16-Apr-2026 to 31-Oct-2026 Submission Site: Submit your manuscript | Control Engineering Practice Article Type Name: "VSI: Precision Motion Systems&Control" - please select this item when you submit manuscripts online All manuscripts will be peer-reviewed. Submissions will be evaluated based on originality, significance, technical quality, and clarity. Once accepted, articles will be posted online immediately and published in a journal regular issue within weeks. Articles will also be simultaneously collected in the online special issue. For any inquiries about the appropriateness of contribution topics, welcome to contact Leading Guest Editor (Dr. Hassan HosseinNia). Guide for Authors will be helpful for your future contributions, read more: Guide for authors - Control Engineering Practice - ISSN 0967-0661 | ScienceDirect.com by Elsevier For more information about our Journal, please visit our ScienceDirect Page: Control Engineering Practice | Journal | ScienceDirect.com by Elsevier Keywords: precision motion control; nano-positioning systems and control; active vibration control; piezoelectric/electromagnetic actuators/motors and drive; (opto-)mechatronic system design https://www.sciencedirect.com/special-issue/332581/precision-motion-systems-and-control
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Special Issue on AI-Driven Control and Planning for Advanced Robotics Submission Date: 2027-05-31 The convergence of Artificial Intelligence (AI) and robotics has reached a critical inflection point. While classical control theory provides rigorous guarantees for stability and robustness, AI-driven control and planning - including Foundation Models, Large Language Models (LLMs), World Model (WM), and Vision-Language-Action (VLA) architectures, Reinforcement learning, Imitation Learning - offers significant potential for robots to operate in unstructured and semantics-rich environments.This Special Issue aims to provide a focused platform for original research that advances AI-driven robotic control and planning while maintaining the precision, reliability, and safety required by control engineering practice, particularly in combination with LLMs. Contributions are expected to demonstrate practical applicability, experimental validation, or highly representative real-world simulations, and to compare proposed methods against established baselines. Consistent with the mission of Control Engineering Practice, papers should emphasize practical relevance, methodological contribution, robustness, deployment issues, and benefits over existing approaches, rather than purely conceptual AI formulations. Foundation-model-enabled robot planning and control.​ Multimodal perception-action architectures. Integration of AI/LLMs with model-based frameworks (e.g., Neural MPC, Control Barrier Functions, and Lyapunov-stable learning). Closed-loop execution with language or vision-language guidance. Control-aware policy refinement and verification. Failure analysis, supervision, and safety mechanisms for AI-enabled robotic systems. Advanced learning-based control/planning (e.g., reinforcement learning, imitation learning, neural controller, neural planner) that outperforms traditional algorithms. Safety-critical shielding, formal methods for neural control loops, and robustness analysis of AI-driven systems. Sim-to-real transfer with representative validation. Domain-specific robotic applications in industrial automation, autonomous vehicles, logistics, field robotics, and biomedical or medical robotic systems. Guest editors: Prof. Yingbai Hu Affiliation: Hunan University, Changsha, China Prof. Hongtian Chen Affiliation: Shanghai Jiao Tong University, Shanghai, China Prof. Jiming Chen Affiliation: Zhejiang University, Hangzhou, China Prof. Chun-Yi Su Affiliation: Concordia University, Montreal, Canada Prof. Leonardo S. Mattos Affiliation:Istituto Italiano di Tecnologia, Genoa, Italy Manuscript submission information: Open for Submission: from 01-Oct-2026 to 31-May-2027 Article Type Name: "VSI: CONPRA_AI-Driven Control" - please select this item when you submit manuscripts online All manuscripts will be peer-reviewed. Submissions will be evaluated based on originality, significance, technical quality, and clarity. Once accepted, articles will be posted online immediately and published in a journal regular issue within weeks. Articles will also be simultaneously collected in the online special issue. For any inquiries about the appropriateness of contribution topics, please contact the Leading Guest Editor (Yingbai Hu). Keywords: AI-driven control; Foundation models; Large language models; Vision-language-action architectures; RL/IL based control/planning; Neural control; Sim-to-real transfer; Industrial and medical robotics https://www.sciencedirect.com/special-issue/335109/ai-driven-control-and-planning-for-advanced-robotics
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