CONTROLO 2026 — 17th APCA International Conference on Automatic Control and Soft Computing

The CONTROLO 2026 brings together academia and professionals from the industry to share cutting-edge concepts, recent developments and research results, and practical achievements and work-in-progress from industry in the fields of control, automation, robotics and soft computing.

Topics: Control Systems, Automation and Robotics, Soft-Computing with application to Control, Automation or Robotics, Adaptive Control, Aeronautics and Aerospace control, Control Education, Control technology, sensors and actuators, Control Theory, Architectures and Applications, Discrete-event systems, Distributed Control, Estimation and Identification, Fault Detection, Diagnosis and Fault Tolerant Control, Fuzzy and Neuro-Fuzzy Systems and Control, Human in the Loop Control, Hybrid Systems, Intelligent and AI Based Control, Linear and Nonlinear Control, Modelling and Simulation, Networked Control Systems, Optimal, Robust and Stochastic Control, Optimization Approaches, Remote and Virtual Laboratories, Automated Guided Vehicles, Autonomous Agents, Cyber-Physical Systems, Embedded Systems, Factory Modelling and Automation, Grafcet and Petri-Nets, Human-Agent Interaction, Human-Machine Interfaces, Industrial Networks and Automation, Industrial Automation, Instrumentation, 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, Robotics, Vision, Recognition and Reconstruction, 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