Call for Papers

15th International Conference on Automatic Control and Soft Computing (CONTROLO 2022) will provide an excellent opportunity for presenting new research results and to discuss the latest developments in the fields of control, automation, robotics and soft computing.

Download here the Call for Papers PDF version

Research topics of interest for submission include, but are not limited to:

Control Systems

Adaptive Control
Aeronautics and Aerospace control
Control Education
Control technology, sensors and actuators
Control Theory, Architectures and Applications
Discrete-event systems
Distributed Control
Fault Detection, Diagnosis and Fault Tolerant Control
Fractional Signals, Systems and Control
Fuzzy and Neuro-Fuzzy Systems and Control
Human in the Control-Loop
Hybrid Systems
Intelligent and AI Based Control
Linear and Nonlinear Control
Modelling, Simulation, Estimation and Identification
Networked Control Systems
Optimal, Robust and Stochastic Control
Optimization approaches
Remote and Virtual Laboratories

Automation & Robotics

Automated Guided Vehicles
Autonomous Agents
Cyber Physical Systems
Embedded Systems
Factory Modelling and Automation
Grafcet and Petri-Nets
Human-Agent Interaction
Human-Machine Interaction and Industry 5.0
Industrial Automation
Industrial Networks
Internet of Things and Industry 4.0
Manufacturing systems
Mechatronics Systems
Mobile Robots
Modelling of Complex Systems
Perception and Awareness
Process Automation
Real-Time Systems
Vision, Recognition and Reconstruction

Soft-Computing with application to Control, Automation or Robotics

Adaptive and Dynamic Programming
Artificial Intelligence and Pattern Recognition
Cloud, Fog and Big Data
Cognitive Artificial Systems
Computational Intelligence
Data Mining and Information Retrieval
Data Reduction and Interpretation
Evolution of AI Systems
Independent and Cognitive Computing
Intelligent Agents and Context Awareness
Knowledge Acquisition and Representation
Machine Learning
Perception Intelligent Decision Systems
Reinforcement and Deep-Learning