Technical Committees and their Scopes

1 SYSTEMS AND SIGNALS

1.1 Modelling, Identification, and Signal Processing

Addresses all aspects of system modelling and identification, from theoretical and methodological developments to practical applications. Considers model selection, model fitting, identification methods, robust estimation, tracking and adaptation, measures of model fit, model validation, fault detection, linear/nonlinear models, experiment design, and automatic methods. Includes non-parametric, state-space, and frequency domain methods as well as distributed parameter models.

1.2 Adaptation and Learning Systems

Addresses continuous and discontinuous adaptation and learning rules for prediction, control optimization and signal processing. Focuses on model-based and data-based adaptive control, adaptation schemes for prediction, filtering, modelling and decision making. Facilitates migrating intelligence into adaptive systems, gain scheduling including linear parameterically varying (LPV) methodologies, auto-tuning, iterative schemes, switching control, fault detection and isolation.

1.3 Discrete Event and Hybrid Dynamic Systems

Focuses on the design, analysis and control of Discrete Event Systems (DES) and Hybrid Systems (HS). Discrete event systems are characterized by countable state spaces and state trajectories evolving through "jumps" (discrete events) from one state to another. Hybrid systems combine event-driven dynamics with conventional time-driven dynamics. Issues involved in the design, analysis, and controller synthesis for such systems include synchronization, concurrency, optimization and conflict of events.

1.4 Stochastic Systems

Promotes and disseminates knowledge related to probabilistic and statistical methods in modelling, identification, estimation and control. Fields of interest include: stochastic control, estimation theory, system identification, realization theory, synthesis of stochastic systems, learning theory, randomized methods, statistical analysis and simulation of dynamic systems. The emphasis is on methodological and conceptual aspects, in both theory and in applications. One of the primary goals of the Committee is to act as catalyst to bring together the expertise and knowledge developed by different communities and in different contexts.

1.5 Networked Systems

Focuses on two main topical areas. Control OF networks and control OVER networks. In the former, control theory provides the tool for regulating the flow of packets on communication networks, through the design of routers, source laws and associated protocols. In the latter, communication theory tools are used to design effective controllers for remote control applications, where the loop is closed over an unreliable communication link.

2 DESIGN METHODS

2.1 Control Design

Considers a wide variety of aspects in the design of control systems, ranging from methodologies to computational techniques and simulation studies. Includes issues on controller constraints and structure, decentralization, digital implementation, model validation, supervision and testing. Addresses also topics on parametric optimization, analytical design, data-based control system design, fault tolerant and switching control. Moreover, it also considers the new challenging fields of synthetic biology and modelling and the control of biochemical networks.

2.2 Linear Control Systems

Fosters analysis and synthesis for dynamic systems described by linear differential and difference equations. This includes the study of finite-dimensional time-invariant and time-variant systems, descriptor systems, n-dimensional systems, systems with time delays infinite dimensional systems, complex systems, fractional systems and positive systems. Promotes investigation of the structural properties of linear control systems. Considers also control methods and structural properties for decoupling, disturbance rejection, model following, fault detection and diagnosis.

2.3 Non-linear Control Systems

Fosters methods for analysis and design of control systems described by nonlinear differential or difference equations. Considers all nonlinear controller design methods including, but not limited to, methods of asymptotic stabilization, regulation, tracking, disturbance rejection and output feedback control. Includes robust control of nonlinear systems, control of constrained systems, nonlinear observer and filter design and the application of nonlinear analysis and design techniques to all fields.

2.4 Optimal Control

Fosters classical and modern optimization methods used for solving optimal control problems (calculus of variations, dynamic programming, nonlinear programming, optimal control, differential games, evolutionary algorithms). Includes modelling of control optimization, large-scale optimization problems and methods, static optimization problems, non-smooth and discontinuous problems of control and optimization, optimization under uncertainties, singularities in optimization, algorithms and software and industrial applications of optimal control.

2.5 Robust Control

Focuses on the analysis and optimal controller synthesis for systems affected by uncertainties. Includes the development of tools for investigating the fundamental trade-off between uncertainty size and achievable controller performance, with particular emphasis on suitable relaxation schemes resulting in efficient numerical algorithms even for systems of high complexity. Covers the whole chain of practical controller design from system modelling by identification, via optimization-based controller synthesis, up to real-life control system implementation, with robustness guarantees for all sources of potential uncertainties.

3 COMPUTERS, COGNITION AND COMMUNICATION

3.1 Computers for Control

Considers all aspects of computer-based control, including real-time computing systems, real-time communications and distributed control systems, hardware and software architectures and platforms, development methodologies, software engineering and software tools, hardware and software in safety-critical applications, as well as control of the operational processes in computing systems themselves.

3.2 Computational Intelligence in Control

Focuses on all aspects of knowledge-based, fuzzy, neuro-fuzzy and neural (both, artificial and biologically plausible) systems and evolutionary algorithms relevant to control, both in theory and application driven.

This includes modelling, identification, forecasting, stability analysis, design, learning, adaptation, evaluation, implementation, definition of performance objectives and operation constraints, as well as awareness for computational issues, brain-computer interfacing, bio-informatics and computer-aided design tools.

3.3 Telematics: Control via Communication Networks 

Considers all aspects of computerized and telecommunication-based automation systems, providing services to remote equipment, partially methods of remote and distributed control, remote sensor data acquisition, the Internet, and tele-presence, for tele-operation, tele-maintenance, tele-diagnosis, tele-medicine, tele-education, traffic control, robots for hazardous environments, remote industrial production, maritime and aerospace systems, and smart homes.

4 MECHATRONICS, ROBOTICS AND COMPONENTS

4.1 Components and Technologies for Control

Deals with components (sensors, actuators and instruments) and technologies (generic methodologies, techniques, new developments and sub-systems) for advanced control and measurement applications. Topics of interest include functionalities, quality of service and performance, data handling techniques, design methods and tools, implementation and modelling of components and instruments, mechatronics, MEMS, communications networks and fieldbuses, and applications to various engineering systems.

4.2 Mechatronics Systems

Covers the integrated design of mechanical parts with the embedded control system, and includes software tools, modelling, identification and control methods, hardware-in-the-loop simulation, human-machine interfaces, and specific design methodologies. Mechatronic principles are applied in a wide variety of areas, such as vehicles (aircraft, automobiles, ships, spacecraft and trains), engines, medical systems, information storage systems, precision mechatronic systems (optical systems, machine tools), robots, and micro-/nano-systems. Examples of other focal points are active bearings, MEMS, motion and vibration control, smart structures and education for mechatronic systems.

4.3 Robotics

Covers actual robotics topics from the viewpoint of theory and applications, including RT (robot technology), robot manipulators, mobile robots, flying robots, autonomous systems, telerobotics, networked robotics, embedded robotics, intelligent robotics, perception and sensing, information and sensor fusion, guidance, navigation and control. Application fields address daily life, transportation, service, medicine, agriculture, manufacturing, underwater, mining, space, and entertainment.

4.4 Cost-Oriented Automation

Promotes reference architectures, development approaches and maintenance strategies for cost savings in manufacturing processes, transportation, and building automation. In also promotes intelligent maintenance systems with the integration of human skills, decentralized process control strategies, and addresses automation integrated with information processing.

4.5 Human-Machine Systems

Considers all conditions where humans (individuals as well as groups) use, control or supervise tools, machines or technological systems. Fosters analysis, design, modelling and evaluation of HM-systems and includes: decision making and cognitive processes, modelling of human performance (reliability, mental load, predictability), real and virtual environments, design methodology, task allocation-sharing and job design, intelligent interfaces, human operator support, work organization, and selection and training criteria.

5 MANUFACTURING SYSTEMS

5.1 Manufacturing Plant Control

Addresses the scientific challenges of automation and issues raised by the integrated manufacturing systems (IMS) paradigm in order to apply micro electro-mechanical systems (MEMS), mechatronics, manufacturing execution systems (MES), multi-agents systems (MAS), holonic manufacturing systems (HMS) and e-technologies to digitally control with more agility in the entire manufacturing chain, from design through manufacturing, to maintenance and service, over the whole product and process life cycle.

5.2 Manufacturing Modelling for Management and Control

Addresses theory and application of descriptive and prescriptive models of e-manufacturing and supply chain systems, from simulation and information to optimization, analytic and knowledge-based models oriented to production and service management, including enterprise and multi-enterprise resource planning, communication- , agent- , and Internet-based manufacturing.

5.3 Enterprise Integration and Networking

Fosters research in enterprise networking and integration; in particular, enterprise networking reference architectures, enterprise engineering methodologies, and enterprise modelling and application protocols. Aims are to identify theoretically sound and practically viable techniques for enterprise Internet-based collaboration, enterprise networking, and Unified Enterprise Modelling Language to support the exchange of enterprise models among various user communities and of modelling tools.

5.4 Large Scale Complex Systems

Focus on manufacturing and related systems characterized by a large number of variables, non-linearities, uncertainties, and/or a networked structure of interconnected subsystems. It aims at developing new hierarchical control methods, decision-making and risk analysis techniques together with practical solutions based on new advances in computer and communication tools.

6 INDUSTRIAL SYSTEMS

6.1 Chemical Process Control

Focuses on development of new chemical process control techniques and algorithms for application in pilot and industrial-sized plants. Processes of interest include all techniques used in petroleum, chemical, petrochemical, specialty chemical, and pharmaceutical processes as well as in the food, cement, and paper and pulp industries. Has a strong interest in the treatment of biological processes. Also considers system descriptions, component selection, sensors, actuators, monitoring, local control, plant-wide control, real-time optimization, planning and scheduling and technology transfer.

6.2 Mining, Mineral and Metal Processing

Fosters all aspects of process control in the fields of mining, mineral and metal processing, by providing a forum for discussion and dissemination of information on related control theory and applications, measurements, automation and optimization. Also includes exploration of fossil materials, recycling system control and Internet-based control.

6.3 Power Plants and Power Systems

Addresses all aspects of modelling, operation, and control of power plants and power systems. Includes load forecast and flow calculation, dynamic interactions of power plants and power systems, constraints and security control concepts, tools for control system design, testing and documentation, real time simulation and dispatching, technical impact of deregulation on power system control, and security monitoring as well as analysis and control in deregulated power systems.

6.4 Safeprocess

Promotes on-line fault detection and isolation (FDI), estimation and diagnosis, with a view to predictive maintenance and supervision, as well as fault tolerant control. Addresses residual generation, residual evaluation, performance monitoring, statistical hypothesis testing, on-line change detection, software sensors, active input signal generation for FDI, decision making, controller reconfiguration and switching. Promotes analysis tools such as failure mode effect analysis (FMEA), severity analysis and reliability theory to achieve fault tolerant designs.

7 TRANSPORTATION AND VEHICLES SYSTEMS

7. 1 Automotive Control

Considers modelling, supervision, control, and diagnosis of automotive systems, automobile power trains, propulsion, vehicle dynamic systems, and electrical and alternative drive vehicles. Includes integrated traffic management, general automobile/road-environment strategies, and distributed discrete-event systems. Considers also automotive sensors, in-vehicle communication networks, human-machine interfaces, and information displays/systems.

7.2 Marine Systems

Considers theory and application of automatic control engineering and artificial intelligence techniques to the maritime field. To include surface vessels, floating structures, subsea systems, underwater vehicles, human factors, autonomous craft, and other devices within the marine environment. Addresses navigation, guidance and control, monitoring and surveillance, fault diagnosis, optimization, planning, modelling, identification, and control architectures. Interests also span total vessel control to computer systems for marine applications, and detailed control of ancillary and auxiliary subsystems.

7.3 Aerospace

Deals with every aspect of dynamics, control, and mission control of aeronautical and space related systems including missiles, launch and re-entry vehicles, aircraft, satellites, space stations, helicopters, and autonomous aerospace systems. Addresses conceptual definition, design, simulation, testing, verification, operations and post-operational analysis. Also includes systems in vehicles (e.g. pointing systems and manipulators), man-in-the-loop systems, guidance, navigation and vehicle control, mission control and operations.

7.4 Transportation Systems

Addresses ground transportation systems (road and guided transport) and air traffic control systems for both passengers and transported goods with regard to modelling, simulation, surveillance, control, optimization, real-time operations, information processing, and decision support. Also addressed are common aspects and generic techniques for all transportation modes (road, rail, air, maritime, and intermodal), in the areas of system engineering, human-machine interface, human factors navigation, logistics, safety, simulation, surveillance, control, and intelligent transportation systems (ITS).

7.5 Intelligent Autonomous Vehicles

Considers generic methodologies and techniques applicable to intelligent autonomous vehicles. Includes mobile robots on land, at sea, in air or in space, multi-vehicle systems and networks of autonomous vehicles. Addresses sensing, seinsor integration and perception, architectures, planning, mission and motion control, navigation and cooperative navigation techniques, SLAM, teleoperation, human- and vehicle interaction and practical applications. Interests span from intelligent vehicle control to auxiliary systems support.

8 BIO AND ECOLOGICAL SYSTEMS

8.1 Control in Agriculture

Fosters modelling and control aspects of agriculture. Methodologies for agricultural production lines such as photosynthesis of crops under environmental stresses, soil-plant atmosphere cycle and metabolism of farm animals. Post-harvest processes such as grading, drying, storage of crops including fruits and vegetables. Food processing (quality and safety). Environmental and climate control of greenhouses, warehouses and animal houses. Energy issues in agriculture such as heating, cooling, lighting, and energy saving.

8.2 Modelling and Control of Biomedical Systems

Considers applications of systems, modelling, informatics and control concepts, methodologies and techniques in biology, physiology, medicine and healthcare. Specific topics include: drug delivery and pharmacokinetics, control of physiological and clinical variables in high dependency medicine and in managing chronic disease, signal and image analysis, rehabilitation engineering, healthcare delivery, clinical decision support, telemedicine and e-Health.

8.3 Modelling and Control of Environmental Systems

Promotes the development of modelling and control methodologies for natural systems. Emphasis is placed on the synergistic role of risk analysis, impact evaluation, management of natural resources with the design of planning and management systems for participatory decision making, to ensure an effective integration of technology and environment through a multi-objective approach.

8.4 Biosystems and Bioprocesses

Covers all major areas of biosystems and bioprocesses, where computers are used to aid bioprocess design, supervision, diagnosis, operation, optimization and control, in monitoring, modelling, estimation, fault diagnosis and monitoring, data mining tools, bioinformatics, control, scheduling, optimization, life-cycle analysis with applications in microbial and (any) cell technology; pharmaceutical, food processes waste biotreatment, and in downstream processing and integrated bioprocessing.

9 SOCIAL SYSTEMS

9.1 Economic and Business Systems

Addresses modelling techniques for economic systesms. It bridges the gap between economics and engineering by encompassing areas of research in econometrics, statistics, computer science, artificial intelligence, and other useful tools for decision and control in economics and management. The focus topics include (but are not limited to) modelling techniques ( (econometrics, time series, agent-based, and financial engineering), computational intelligence (neural networks, wavelets, decision support systems, and evolutionary and genetic programming) and planning and control (forecasting, management, optimal control, and geographic information sciences).

9.2 Social Impact of Automation

Addresses relationships between automated systems and social environments. This includes the social effects of automation, socially desirable requirements for automation development, and socially acceptable alternatives for automation design. Also addressed are environmental, health, and safety implications of automation, engineering ethics, professional responsibility, and public policy.

9.3 Developing Countries

Fosters the development of automation and related topics, such as education and training for automation, in developing countries. Control and automation compatibility with social and economic structures of developing countries. Stimulates developing countries' interest in IFAC, invites and assists NMOs to organize workshops, symposia and regional conferences to bring together scientists and specialists for the purpose of sharing and comparing experiences.

9.4 Control Education

Addresses university education and continuing education issues in control engineering. Methodology for improving the theory, practice, and accessibility of control systems education. Control engineering laboratories, experiments, computer aided design, distance and virtual education technologies, e-learning and Internet-based teaching technologies. Cooperation and technology transfer between academia and industry. Control engineering education in developing countries (in collaboration with the TC on Developing Countries). Control Engineering Textbook Prize nomination.

9.5 Supplemental Ways of Improving International Stability - SWIIS

To identify, define, and improve factors that significantly influence international stability. To outline ways in which IFAC can use its own systems and control capabilities to enhance international stability and build a more peaceful world. To interact with other organizations having similar goals. To cooperate with other IFAC TCs regarding SWIIS activities.