International Journal of Advanced Control and System Engineering

International Journal of Advanced Control and System Engineering

International Journal of Advanced Control and System Engineering is a peer-reviewed online journal launched in 2015 that publishes original research articles and review papers, experimentally and theoretically. Papers published in this journal cover all major topics under automatic control systems including embedded control systems, real-time systems, and digital and analog control.

• Advanced Control Systems: Classical and modern control, linear and nonlinear control, optimal control, robust control, adaptive control, stochastic control, predictive control, sliding-mode control, decentralized control, and multivariable control.
• Intelligent Control Systems: Fuzzy logic control, neural-network control, neuro-fuzzy systems, machine-learning-based control, reinforcement learning, expert systems, evolutionary control, and AI-assisted control strategies.
• System Modelling and Simulation: Mathematical modelling, dynamic system modelling, state-space analysis, system identification, simulation methods, parameter estimation, model validation, digital simulation, and simulation-based optimization.
• Industrial Automation and Process Control: Programmable logic controllers, SCADA systems, distributed control systems, process automation, manufacturing automation, supervisory control, industrial monitoring, and real-time control systems.
• Robotics and Autonomous Systems: Industrial robots, mobile robots, robotic manipulators, autonomous vehicles, unmanned systems, path planning, trajectory control, localization, navigation, motion control, and multi-robot systems.
• Mechatronic Systems: Integrated mechanical, electrical, electronic, and control systems; servo systems; actuators; motion-control systems; smart machines; precision engineering; and intelligent mechatronic systems.
• Cyber-Physical Systems: Integrated computation, communication and physical processes, embedded intelligence, networked control, smart sensing, cyber-physical production systems, distributed control, and real-time system integration.
• Embedded and Real-Time Control: Microcontroller-based systems, embedded controllers, FPGA-based control, digital signal controllers, real-time operating systems, hardware-in-the-loop systems, and embedded automation.
• Control of Electrical Power Systems: Load-frequency control, voltage control, power-system stabilization, renewable-energy control, microgrid control, smart-grid control, power-electronic control, energy-management systems, and grid automation.
• Renewable Energy Control Systems: Solar photovoltaic control, wind-energy control, maximum power point tracking, hybrid renewable-energy systems, inverter control, distributed generation, and renewable-energy optimization.
• Electric Vehicle Control Systems: EV powertrain control, motor-drive control, battery-management systems, regenerative braking, charging control, vehicle-to-grid systems, autonomous vehicle control, and EV safety systems.
• Power Electronics and Converter Control: Converter modelling, inverter control, DC-DC converter control, multilevel converters, PWM techniques, model-predictive control of converters, and intelligent power-electronic control.
• Process Systems Engineering: Chemical, thermal, fluid, manufacturing, energy and industrial process modelling, process optimization, process monitoring, fault diagnosis, and advanced process control.
• Sensors, Instrumentation and Measurement: Smart sensors, transducers, measurement systems, data acquisition, sensor fusion, instrumentation systems, condition monitoring, and intelligent sensing.
• Signal Processing for Control Applications: Digital signal processing, filtering, state estimation, sensor signal processing, feature extraction, noise reduction, real-time signal analysis, and control-oriented signal processing.
• System Identification and Estimation: Parametric and non-parametric identification, state estimation, observer design, Kalman filtering, parameter estimation, data-driven modelling, and adaptive estimation.
• Optimization in Control and System Engineering: Linear and nonlinear optimization, evolutionary algorithms, swarm intelligence, multi-objective optimization, metaheuristic methods, optimal scheduling, and control-system optimization.
• Fault Detection, Diagnosis and Fault-Tolerant Control: Fault detection, anomaly detection, condition monitoring, predictive maintenance, fault isolation, fault-tolerant control, reliability analysis, and resilient systems.
• Human–Machine Systems: Human-machine interfaces, operator-support systems, supervisory control, human-in-the-loop control, cognitive systems engineering, ergonomic interface design, and human-robot interaction.
• Networked and Distributed Control Systems: Networked control, wireless control networks, distributed control, cooperative control, multi-agent systems, consensus control, communication delays, and decentralized architectures.
• Artificial Intelligence in Control Engineering: Machine learning, deep learning, reinforcement learning, predictive analytics, AI-based modelling, intelligent fault diagnosis, autonomous decision-making, and learning-based control.
• Digital Twins and Virtual Engineering: Digital twins, virtual commissioning, real-time simulation, model-based engineering, predictive system monitoring, digital replicas, and simulation-assisted control.
• Smart Manufacturing and Industry 4.0: Industrial IoT, smart factories, intelligent automation, cyber-physical production systems, predictive maintenance, digital manufacturing, robotics, and data-driven control.
• Control of Mechanical and Structural Systems: Vibration control, active suspension, vehicle dynamics, structural control, aerospace control, mechanical-system optimization, dynamic loading, and smart structures.
• Control Applications in Agriculture and Environment: Smart irrigation, greenhouse automation, precision agriculture, environmental monitoring, agricultural robotics, climate-control systems, and automated farming technologies.
• Biomedical Control and Healthcare Systems: Physiological control systems, rehabilitation robotics, biomedical instrumentation, assistive devices, healthcare automation, intelligent monitoring, and closed-loop medical systems.
• Smart Infrastructure and Building Automation: HVAC control, intelligent buildings, smart energy systems, transportation control, traffic systems, infrastructure monitoring, and smart-city automation.
• Safety, Security and Resilient Control: Safe control architectures, system reliability, secure control, cybersecurity of control systems, resilient automation, fault recovery, and safety-critical engineering systems.
• Emerging Trends in Control and System Engineering: Edge AI, autonomous systems, collaborative robotics, intelligent transportation, self-optimizing systems, digital twins, quantum control concepts, and next-generation control technologies.