List of Category, Technical Area, and Keyword
 
 
When a paper is submitted in the IFAC CMMS, the author chooses at least one keyword for the paper. Among the selected keywords, the first keyword will be used to determine the corresponding Technical Area, in which the reviewing process is handled. Use this page for a summary of all keywords of 17th IFAC World Congress.

Note: In the Submission Form of IFAC CMMS, Submission Category is selected first as follows,

 

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and then, the keyword selection window will pop-up.

 

Submission Category    Technical Area     Keyword
1. Systems and Signals  1.1. Modeling, Identification and Signal Processing Bayesian methods
  Channel estimation/equalisation
  Error quantification
  Particle filtering/Monte Carlo methods
  Software for system identification
  Subspace methods
  Errors in variables identification
  Fault detection and diagnosis
  Filtering and smoothing
  Mechanical and aerospace estimation
  Nonparametric methods
  Vibration and modal analysis
  Bounded error identification
  Continuous time system estimation
  Frequency domain identification
  Hybrid and distributed system identification
  Nonlinear system identification
  Recursive identification
  Closed loop identification
  Grey box modelling
  Identification for control
  Input and excitation design
  Time series modelling
  1.2. Adaptive and Learning Systems Gain scheduling
  Linear parametrically varying (LPV) methodologies
  Autotuning
  Iterative modelling and control design
  Adaptation and learning in physical agents
  Adaptive control of systems
  Nonlinear systems
  Switching control
  Adaptive system and control
  Model reference adaptive control
  Nonlinear adaptive control
  Robust adaptive control
  Iterative learning control
  Adaptive control by neural networks
  1.3. Discrete Event and Hybrid Systems Discrete event systems modeling and control
  Automata, Petri Nets and other tools
  Supervisory control of hybrid systems
  Queueing systems
  Discrete event simulation
  Hybrid systems modeling and control
  Hybrid systems stability
  Switched discrete and hybrid systems
  Quantized systems
  Verification
  Control over communication
  1.4. Stochastic Systems Stochastic control
  Stochastic system identification
  Estimation and filtering
  Realization theory
  Synthesis of stochastic systems
  Randomized methods
  Learning theory
  Statistical data analysis
  Simulation of stochastic systems
  1.5. Networked Systems Cooperative systems
  Complex system management
  Control of networks
  Control over networks
  Multi-agent systems
  Coordination of multiple vehicle systems
  Networked embedded control systems
  Sensor networks
  Control under communication constraints
  Control under computation constraints
  Control and estimation with data loss
  Distributed control and estimation
  Networked robotic systems
2. Design Methods  2.1. Control Design Decentralization
  Data-based control
  Supervision and testing
  Digital implementation
  Switching stability and control
  Control in neuroscience
  Control in system biology
  Controller constraints and structure
  Model validation in design methods
  Adaptive control
  Parametric optimization
  Analytic design
  Fault-tolerant
  2.2. Linear Control Systems Time-invariant systems
  Time-varying systems
  N-dimensional systems
  Infinite-dimensional systems
  Complex systems
  Fractional systems
  Positive systems
  Systems with time-delays
  Descriptor systems
  2.3. Non-Linear Control Systems Asymptotic stabilization
  Regulation
  Tracking
  Disturbance rejection
  Output feedback control
  Robust control of nonlinear systems
  Control of constrained systems
  Nonlinear observer and filter design
  Application of nonlinear analysis and design
  Anti-windup
  Constrained control
  Delay systems
  LMIs
  Parameter-varying systems
  Linear systems
  Lyapunov methods
  Nonlinear system control
  Observers for linear systems
  Stability of NL systems
  Stability of hybrid systems
  Control of switched systems
  Systems with saturation
  Robust control
  Aerospace applications
  2.4. Optimal Control Optimal control theory
  Singularities in optimization
  Non-smooth and discontinuous optimal control problems
  Control problems under conflict and/or uncertainties
  Differential or dynamic games
  Stochastic optimal control problems
  Evolutionary algorithms
  Large scale optimization problems
  Static optimization problems
  Modeling for control optimization
  Algorithms and software
  Industrial applications of optimal control
  2.5. Robust Control Robustness analysis
  Sum-of-squares
  Robust linear matrix inequalities
  Probabilistic robustness
  Distributed robust controller synthesis
  Optimization based controller synthesis
  Robust controller synthesis
  Quantitative feedback theory
  Robust control applications
  Robust estimation
  Linear parameter-varying systems
  Robust time-delay systems
  Uncertainty descriptions
  Convex optimization
  Relaxations
3. Computers, Cognition and Communication  3.1. Computers for Control Computers for control
  3.2. Cognition and Control Knowledge-based control
  Fuzzy and neural systems relevant to control and identification
  Controller optimisation by genetic and evolutionary algorithms
  Reinforcement learning control
  Robust fuzzy control
  Adaptive fuzzy control
  3.3. Computers, Communication and Telematics Telecommunication-based automation systems
  Remote equipment servicing
  Remote and distributed control
  Remote sensor data acquisition
  The Internet
  Tele-presence
  Tele-operation
  Tele-maintenance
  Tele-diagnosis
  Tele-medicine
  Tele-education
  Traffic control
  Robots for hazardous environments
  Remote industrial production
  Smart homes
4. Mechatronics, Robotics and Components  4.1. Components and Technologies for Control Rule-based approaches
  Data-fusion
  Hardware/software co-design
  Dedicated circuits
  Multi sensor systems
  Intelligent controllers
  Perception devices and positioning systems
  Microsystems: nano- and micro-technologies
  Microsensors
  Microactuators
  Microsystems
  Measurement & actuation
  Auto-configuration
  Diagnosis and self-diagnosis
  Self-learning
  Fuzzy logic
  Neural networks technology
  Genetic algorithms
  Virtual instruments
  4.2. Mechatronic Systems Hardware-in-the-loop simulation
  Design methodologies
  Application of mechatronic principles
  Mechatronic systems
  Modelling
  Identification and control methods
  4.3. Robotics Robotics technology
  Flying robots
  Mobile robots
  Perception and sensing
  Autonomous robotic systems
  Guidance navigation and control
  Telerobotics
  Embedded robotics
  Intelligent robotics
  Robots manipulators
  Information and sensor fusion
  Networked robotic system modelling and control
  4.4. Cost Oriented Automation Architectures and software tools for enterprise integration and networking
  Human collaboration with automation systems
  Sensor and data fusion
  Cost reduction with e-maintenance systems
  Low cost MEMS
  SME-oriented automation and decision support systems
  Low cost automation case studies
  Advances in automation education
  Integration technologies applied to product development and manufacturing
  Efficient use of intelligent machinery and automation systems
  e-Technologies in networked product development and manufacturing
  4.5. Human Machine Systems Decision making and cognitive processes
  Modeling of human performance
  Work in real and virtual environments
  Design methodology for HMS
  Task allocation-sharing and job design
  Intelligent interfaces
  Human operator support
  Multi-modal interaction
  Modeling of HMS
  Engineering methods for HMS
5. Manufacturing and Logistics Systems  5.1. Manufacturing Plant Control Production & logistics over manufacturing networking
  Manufacturing automation over networks
  Industrial communication protocols
  Dependable manufacturing systems control
  Discrete event systems in manufacturing
  Maintenance models and services
  Intelligent maintenance systems
  Assembly and disassembly
  Manufacturing plant control
  RFId and ubiquitous manufacturing
  Life-cycle control
  e-Manufacturing technologies and facilities
  Intelligent manufacturing systems
  Holonic manufacturing systems
  Flexible and reconfigurable manufacturing systems
  Bio-inspired manufacturing systems and self-organization
  Multi-agent systems applied to industrial systems
  5.2. Manufacturing Modeling for Management and Control Modeling of manufacturing operations
  Modeling of assembly units
  Production activity control
  Process supervision
  Quality assurance and maintenance
  Procedures for process planning
  Production planning and control
  Job and activity scheduling
  Logistics in manufacturing
  5.3. Enterprise Integration and Networking Collaborative networked organizations principles
  Protocols and information communication
  Enterprise networks design and implementation
  Unified enterprise modelling language
  Enterprise model validation
  5.4. Large Scale Complex Systems Decentralisation
  Intelligent control of large scale systems
  Decision support systems in manufacturing
  Large scale complex systems
  Identification and model reduction
  Dynamics and control of large scale structures
  Hierarchical multilevel and multilayer control
  Modelling and control of discrete event and hybrid systems
  Methodologies and tools for analysis of complexity
  Analysis of heterogeneous knowledge in modelling
  Knowledge discovery (data mining)
  Supervisory control
6. Power and Process Systems  6.1. Chemical Process Control Industrial applications of process control
  Process control applications
  Applications in semiconductor manufacturing
  Applications in advanced materials manufacturing
  Batch and semi-batch process control
  Estimation and control in systems biology
  Advanced control technology
  Control of micro- and nano-systems
  Control of particulate processes
  Control and optimization of supply chains
  Real time optimization and control
  Control of distributed systems
  Model predictive and optimization-based control
  Nonlinear model reduction
  Nonlinear process control
  Estimation and fault detection
  Process modeling and identification
  Model-based methods for system identification
  Monitoring and performance assessment
  Design and control
  Control of multi-scale systems
  6.2. Mining, Mineral and Metal Processing Measurement and instrumentation
  Identification and modelling
  Process observation and parameter estimation
  Data mining and multivariate statistics
  Fault diagnosis and fault tolerant control
  Advanced process control
  Robotics
  Monitoring of product quality and control performance
  Process optimisation
  Maintenance scheduling and production planning
  Expert systems is process industry
  Neural networks in process control
  Neural fuzzy modelling and control
  Artifical intelligence
  6.3. Power Plants and Power Systems Modeling, operation and control of power systems
  Load forecast
  Load flow and stability calculations
  Dynamic interaction of power plants
  Constraint and security monitoring and control
  Control system design
  Test and documentation
  Real time simulation and dispatching
  Instrumentation and control systems
  Intelligent control of power systems
  Distribution automation
  Impact of deregulation on power system Control
  Analysis and control in deregulated power systems
  6.4. Fault Detection, Supervision & Safety of Technical Process Pattern recognition based methods for FDI
  Fault tolerant control for networked systems
  Analysis of reliability and safety
  Design of fault tolerant/reliable systems
  Maintenance strategies
  Parameter estimation based methods for FDI
  Statistical methods/signal analysis for FDI
  Methods based on neural networks and/or fuzzy logic for FDI
  Methods based on discrete event models, on hybrid or on qualitative models for FDI
  Distributed fault detection and isolation
  Human factors
  Observer based and parity space based methods for FDI
  Process performance monitoring/statistical process control
  Passive approaches to fault tolerant control
  Active approaches to fault tolerant control
7. Transportation and Vehicle Systems  7.1. Automotive Control Modeling, supervision, control and diagnosis of automotive systems
  Automobile powertrains
  Vehicle dynamic systems
  Intelligent driver aids
  Electric fuel cell
  Hybrid and alternative drive vehicles
  Integrated traffic management
  General automobile/road-environment strategies
  System integration and supervision
  Distributed discrete-event systems
  Automotive sensors and actuators
  In-vehicle communication networks
  Man-machine interfaces
  Information displays/system
  Automotive system identification and modelling
  Kalman filtering techniques in automotive control
  Adaptive and robust control of automotive systems
  Nonlinear and optimal automotive control
  Control architectures in automotive control
  7.2. Marine Systems Marine system navigation, guidance and control
  Dynamic positioning
  Autonomous underwater vehicles
  Unmanned marine vehicles
  Autonomous surface vehicles
  Neural networks
  Fuzzy logic in marine systems
  Genetic algorithms in marine systems
  Marine system identification and modelling
  Decision support systems in marine systems
  Coordinated control
  Cooperative control
  Kalman filtering techniques in marine systems control
  Sensors and actuarors
  Adaptive and robust control in marine system
  Nonlinear and optimal marine system control
  Control architectures in marine systems
  7.3. Aerospace Control of systems in vehicles
  High accuracy pointing
  Man-in-the-loop systems
  Autonomous systems
  Guidance, navigation and control of vehicles
  Avionics and on-board equipments
  Flight dynamics identification, formation flying
  Health monitoring and diagnosis
  Decision making and autonomy, sensor data fusion
  Mission control and operations
  7.4. Transportation Systems Modeling and simulation of transportation systems
  Automatic control, optimization, real-time operations in transportation
  Information processing and decision support
  Man-machine interface in transportation
  Human factors in vehicular system
  Navigation
  Transportation logistics
  Safety
  Simulation
  Intelligent transportation systems
  Freight transportation
  7.5. Intelligent Autonomous Vehicles Sensing
  Sensor integration and perception
  Cooperative perception
  Architectures
  Mechanical design of autonomous vehicles
  Autonomous vehicle navigation, guidance and control
  Trajectory tracking and path following
  Motion control
  Mission planning and decision making
  Map building
  Localization
  SLAM
  Teleoperation
  Human and vehicle interaction
  Multi-vehicle systems
  Networks of robots and intelligent sensors
  Cooperative navigation
  Swarm behaviour and multi-agent systems
  Learning and adaptation in autonomous vehicles
  Applications of intelligent autonomous vehicles
  Test evaluation of autonomous vehicles
8. Bio- and Ecological Systems  8.1. Control in Agriculture Modeling and control of agriculture
  Greenhouse control
  Animal husbandry
  Crop processes
  Crop modelling
  CFD in agriculture
  Bioresponses
  Bio-energetics
  Agricultural solar energy use
  Controlled ecological life support systesm (CELLS)
  Plant factories
  Optimal control in agriculture
  Biosensors in agriculture
  Software sensors in agriculture
  Speaking organism systems
  Robotics and mechatronics for agricultural automation
  Agricultural robotics
  Precision farming
  Autonomous vehicles in agriculture
  Post-harvesting and food processing
  Drying
  Food quality
  Food processing control
  Quality assessment
  Grading systems
  Information technologies and ergonomics in agriculture
  AI in agriculture
  Wireless sensor networks in agriculture
  Artificial neural nets in agriculture
  Image analysis in agriculture
  Pattern recognition in agriculture
  Standardisation in agriculture
  Man-machine systems in agriculture
  Agricultural ergonomics
  8.2. Modeling and Control of Biomedical Systems Model formulation, experiment design
  Identification and validation
  Biosignals analysis and interpretation
  Developments in measurement, signal processing
  Tracer kinetic modeling using various imaging systems
  Biomedical system modeling, simulation and visualization
  Decision support and control
  Cellular, metabolic, cardiovascular, neurosystems
  Healthcare management, disease control, critical care
  Pharmacokinetics and drug delivery
  Control of physiological and clinical variables
  Biomedical imaging systems
  Intensive and chronic therapy
  Control of voluntary movements, respiration
  Rehabilitation engineering and healthcare delivery
  Kinetic modelling and control of biological systems
  Quantification of physiological parameters for diagnosis and treatment assessment
  8.3. Modeling and Control of Environmental Systems Natural and environmental systems
  Risk analysis, impact evaluation
  Management of natural resources
  Panning and management for participatory decision making
  Integration of technology and environment
  8.4. Biosystems and Bioprocesses Metabolic engineering
  Modelling and identification
  Parameter and state estimation
  Fault diagnosis and monitoring
  Data mining tools
  Bioinformatics
  Dynamics and control
  Downstream processing
  Integrated bioprocessing: case studies
  Scheduling, coordination, optimization
  Life cycle analysis
  Microbial technology
  Mammalian, insect and plant cell technology
  Pharmaceutical processes
  Food engineering
  Wastewater treatment processes
9. Social Systems  9.1. Economic and Business Systems Econometric models
  General equilibrium models
  Models with explicit expectations and learning
  Agent-based models
  Neural networks in social systems
  Estimation and identification of economic systems
  Modeling languages
  Software tools and algorithms
  Artificial intelligence
  Genetic and evolutionary programming
  Decision support and expert systems
  National and regional economies
  Optimal control
  Forecasting
  Dynamic games
  Multi-country models
  Operations research applications
  Applications in finance
  9.2. Social Impact of Automation Socially desirable requirements for automation development
  Socially acceptable alternatives for automation design
  Socially acceptable requirements for information technologies development
  Environmental, health and safety implications of automation
  Ambient intelligence
  Agile society
  Cognitive aspects of automation
  Education, training and eLearning
  eSociety, eGovernment and eTerritory
  Ethical society
  Human and Humanoid
  Human-centred systems engineering
  Knowledge and competences management
  Management of technology
  Network centric collaboration
  Systems engineering
  9.3. Developing Countries Positive impact of knowledge transfer on social life
  Negative impact of technological transfer without basic scientific background
  Positive impact of technological transfer
  Chance of developing countries in effecting the scientific progress
  Imposed drawbacks on scientific contributions from developing countries
  Negative impact of the inability to reach high technology dependent data
  University and industrial relations
  Effect of good/bad prejudgments on developing relations with developed countries
  Impact of highly educated technicians/engineers on industry
  Importance of continuous education for academic staff
  9.4. Control Education e-Learning
  Internet-based teaching technologies
  Teaching curricula
  University-industry cooperation
  9.5. Supplemental Ways of Improving International Stability Identify, define, and improve factors that significantly influence international stability
H. Highlight Session  H. Highlight Session Control education
  Automation in the steel industry
  Automation in the semiconductor, display, and electronics industry
  Control technology in the automotive industry
  Automation in shipbuilding
  Ubiquitous robotic companion
  Life care intelligent robot



 
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