Conferences related to Neurocontrollers

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2020 59th IEEE Conference on Decision and Control (CDC)

The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.


2020 American Control Conference (ACC)

The ACC is the annual conference of the American Automatic Control Council (AACC, the U.S. national member organization of the International Federation for Automatic Control (IFAC)). The ACC is internationally recognized as a premier scientific and engineering conference dedicated to the advancement of control theory and practice. The ACC brings together an international community of researchers and practitioners to discuss the latest findings in automatic control. The 2020 ACC technical program will

  • 2019 American Control Conference (ACC)

    Technical topics include biological systems, vehicle dynamics and control, adaptive control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2018 Annual American Control Conference (ACC)

    Technical topics include biological systems, vehicle dynamics and control, adaptive control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2017 American Control Conference (ACC)

    Technical topics include biological systems, vehicle dynamics and control, adaptive control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2016 American Control Conference (ACC)

    Control systems theory and practice. Conference topics include biological systems, vehicle dynamics and control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2015 American Control Conference (ACC)

    control theory, technology, and practice

  • 2014 American Control Conference - ACC 2014

    All areas of the theory and practice of automatic control, including but not limited to network control systems, model predictive control, systems analysis in biology and medicine, hybrid and switched systems, aerospace systems, power and energy systems and control of nano- and micro-systems.

  • 2013 American Control Conference (ACC)

    Control systems theory and practice. Conference themes on sustainability, societal challenges for control, smart healthcare systems. Conference topics include biological systems, vehicle dynamics and control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2012 American Control Conference - ACC 2012

    All areas of control engineering and science.

  • 2011 American Control Conference - ACC 2011

    ACC provides a forum for bringing industry and academia together to discuss the latest developments in the area of Automatic Control Systems, from new control theories, to the advances in sensors and actuator technologies, and to new applications areas for automation.

  • 2010 American Control Conference - ACC 2010

    Theory and practice of automatic control

  • 2009 American Control Conference - ACC 2009

    The 2009 ACC technical program will cover new developments related to theory, application, and education in control science and engineering. In addition to regular technical sessions the program will also feature interactive and tutorial sessions and preconference workshops.

  • 2008 American Control Conference - ACC 2008

  • 2007 American Control Conference - ACC 2007

  • 2006 American Control Conference - ACC 2006 (Silver Anniversary)

  • 2005 American Control Conference - ACC 2005

  • 2004 American Control Conference - ACC 2004

  • 2003 American Control Conference - ACC 2003

  • 2002 American Control Conference - ACC 2002

  • 2001 American Control Conference - ACC 2001

  • 2000 American Control Conference - ACC 2000

  • 1999 American Control Conference - ACC '99

  • 1998 American Control Conference - ACC '98

  • 1997 American Control Conference - ACC '97

  • 1996 13th Triennial World Congress of the International Federation of Automatic Control (IFAC)


2020 IEEE Industry Applications Society Annual Meeting

The Annual Meeting is a gathering of experts who work and conduct research in the industrial applications of electrical systems.


2020 IEEE International Conference on Industrial Technology (ICIT)

ICIT focuses on industrial and manufacturing applications of electronics, controls, communications, instrumentation, and computational intelligence.


2020 IEEE International Conference on Robotics and Automation (ICRA)

The International Conference on Robotics and Automation (ICRA) is the IEEE Robotics and Automation Society’s biggest conference and one of the leading international forums for robotics researchers to present their work.


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Periodicals related to Neurocontrollers

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Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Automation Science and Engineering, IEEE Transactions on

The IEEE Transactions on Automation Sciences and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. We welcome results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, ...


Control Systems Technology, IEEE Transactions on

Serves as a compendium for papers on the technological advances in control engineering and as an archival publication which will bridge the gap between theory and practice. Papers will highlight the latest knowledge, exploratory developments, and practical applications in all aspects of the technology needed to implement control systems from analysis and design through simulation and hardware.


Energy Conversion, IEEE Transaction on

Research, development, design, application, construction, installation, and operation of electric power generating facilities (along with their conventional, nuclear, or renewable sources) for the safe, reliable, and economic generation of electrical energy for general industrial, commercial, public, and domestic consumption, and electromechanical energy conversion for the use of electrical energy


Fuzzy Systems, IEEE Transactions on

Theory and application of fuzzy systems with emphasis on engineering systems and scientific applications. (6) (IEEE Guide for Authors) Representative applications areas include:fuzzy estimation, prediction and control; approximate reasoning; intelligent systems design; machine learning; image processing and machine vision;pattern recognition, fuzzy neurocomputing; electronic and photonic implementation; medical computing applications; robotics and motion control; constraint propagation and optimization; civil, chemical and ...


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Most published Xplore authors for Neurocontrollers

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Xplore Articles related to Neurocontrollers

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IEE Colloquium on 'Non-Linear Control' (Digest No.1994/130)

IEE Colloquium on Non-Linear Control, 1994

None


A new neural architecture for homing missile guidance

Proceedings of 1995 American Control Conference - ACC'95, 1995

We present a new neural architecture which imbeds dynamic programming solutions to solve optimal target-intercept problems. They provide feedback guidance solutions, which are optimal with any initial conditions and time-to- go, for a 2D scenario. The method discussed in this study determines an optimal control law for a system by successively adapting two networks - an action and a critic ...


A continually online trained neurocontroller for the series branch control of the UPFC

Proceedings of the International Joint Conference on Neural Networks, 2003., 2003

The crucial factor affecting the modern power systems today is load flow control. The Unified Power Flow Controller (UPFC) provides an effective means for controlling the power flow and improving the transient stability in a power network. The UPFC has fast complex dynamics and its conventional control is based on a linearized model of the power system. This paper presents ...


Neurocontrollers designed by a genetic algorithm

First International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, 1995

The paper discusses problems existing in neural network design using mathematically guided training methods. It presents a genetic algorithm based design technique to train the network, which overcomes all these problems. The paper also presents suitability conditions for using the genetic algorithm based design methods and develops, under these conditions, direct neurocontrollers with a novel structure inspired by proportional plus ...


Robot vision tracking with a hierarchical CMAC controller

KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516), 2000

Vision has extensively expanded robots' capabilities, making the robot control problem more complex. To track a target with a robot arm in a three- dimensional space involves the use of precise commands. We propose to insert a hierarchical neurocontroller based on CMAC (cerebellar model articulation controller) networks in a visual servoing loop. This hierarchical structure splits the robot's workspace and ...


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Educational Resources on Neurocontrollers

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IEEE.tv Videos

No IEEE.tv Videos are currently tagged "Neurocontrollers"

IEEE-USA E-Books

  • IEE Colloquium on 'Non-Linear Control' (Digest No.1994/130)

    None

  • A new neural architecture for homing missile guidance

    We present a new neural architecture which imbeds dynamic programming solutions to solve optimal target-intercept problems. They provide feedback guidance solutions, which are optimal with any initial conditions and time-to- go, for a 2D scenario. The method discussed in this study determines an optimal control law for a system by successively adapting two networks - an action and a critic network. This method determines the control law for an entire range of initial conditions; it simultaneously determines and adapts the neural networks to the optimal control policy for both linear and nonlinear systems. In addition, it is important to know that the form of control does not need to be known in order to use this method.

  • A continually online trained neurocontroller for the series branch control of the UPFC

    The crucial factor affecting the modern power systems today is load flow control. The Unified Power Flow Controller (UPFC) provides an effective means for controlling the power flow and improving the transient stability in a power network. The UPFC has fast complex dynamics and its conventional control is based on a linearized model of the power system. This paper presents the design of a neurocontroller that controls the power flow and regulates voltage along a transmission line. The continually online neurocontroller is used for controlling the series inverter of UPFC. Simulation results carried out in the PSCAD/EMTDC environment are presented to show the successful control of UPFC and the power system.

  • Neurocontrollers designed by a genetic algorithm

    The paper discusses problems existing in neural network design using mathematically guided training methods. It presents a genetic algorithm based design technique to train the network, which overcomes all these problems. The paper also presents suitability conditions for using the genetic algorithm based design methods and develops, under these conditions, direct neurocontrollers with a novel structure inspired by proportional plus derivative control. Techniques are also developed to select the architectures in the same process of parameter training. The proposed methods are validated by several examples, including one with plant transport delay.

  • Robot vision tracking with a hierarchical CMAC controller

    Vision has extensively expanded robots' capabilities, making the robot control problem more complex. To track a target with a robot arm in a three- dimensional space involves the use of precise commands. We propose to insert a hierarchical neurocontroller based on CMAC (cerebellar model articulation controller) networks in a visual servoing loop. This hierarchical structure splits the robot's workspace and assigns different CMAC controllers imposing thus a specialized region CMAC. Compared to a single CMAC with the same number of weights, the neurocontroller's sensitivity and precision is increased. Robot positioning and target tracking with visual feedback can then be done with a better precision.

  • Optimal neurocontrollers for discretized distributed parameter systems

    We propose to use the framework of backpropagation through time (BPTT) to create optimal feedback neurocontrollers for distributed parameter systems (DPS). DPS are systems distributed in space while evolving in time. Unlike the lumped parameter systems, DPS are represented by a set of partial differential equations in the state space. Our neurocontrollers obtained for discretized DPS in the infinite-horizon regulator setting are applicable to a broad set of initial states (an envelope of initial state profiles). We compare our technique and results with another approach to synthesizing optimal DPS neurocontrollers introduced.

  • Multidimensional sampling aspects of neurocontrol with feedforward networks

    This paper deals with results from the n-D (n-dimensional) sampling theory relevant to neurocontrol. These form a proper setting for modelling with feedforward neural networks for the purposes of nonlinear control. The focus is on RBF networks in the context of n-D sampling. RBF neural structure may be applied as an interpolating filter, according to the n-D sampling theory.

  • Adaptive control of discrete systems using neural networks

    Etxebarria (1994) has presented a simple adaptive control scheme for discrete systems using two linear two-layered neural networks. Specifically, one of these networks is used to learn online the dynamics of the unknown plant using the Widrow-Hoff delta rule. The other network uses this learning to adjust its connection weights and to generate the control signal. Etxebarria has proven that the resulting closed-loop system is globally stable and has shown that the controlled output tracks the reference signal asymptotically. The author states that there is room for improving the performance of the adaptive neural control scheme of Etxebarria, in particular, its transient performance. In this correspondence, a method is proposed to enhance the transient performance of the above control scheme by replacing the output y of the unknown plant by a linear combination of y and its derivative y/spl dot/. Furthermore, the proposed method does not change the structure of both the neural estimator and controller and, as such, the increase in overall computation is minimal. Two examples, based on simulation and experimental studies, are presented to demonstrate the effectiveness of the proposed method.<<ETX>>

  • Neurocontroller based on ADHDP for rectifier in HVDC system

    A novel neurocontroller based on ADHDP for rectifier in HVDC transmission system is presented in this paper. The action dependent heuristic dynamic programming (ADHDP), a member of the adaptive critic designs family is used for the design of the rectifier neurocontroller in HVDC. The action network and critic network of the neurocontroller are designed using BP artificial neural networks. Using a proportional-integrator approach, the proposed neurocontroller is capable of dealing with actual rather than deviation signals. Simulation results are provided to show that the proposed controller performs better than the conventional PID controller.

  • ATM switching network with neural control

    An original switching architecture for ATM networks is presented. The described approach assumes cell path parallelism and neural control. In order to show performances of this solution some numerical results are also included.



Standards related to Neurocontrollers

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