IEEE Organizations related to Bang-bang Control

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Conferences related to Bang-bang Control

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2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


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 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 Systems, Man, and Cybernetics (SMC)

The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.


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Periodicals related to Bang-bang Control

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Most published Xplore authors for Bang-bang Control

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Xplore Articles related to Bang-bang Control

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Computer control strategies for induction motor drives

1988 International Conference on Control - CONTROL 88., 1988

The problem of utilizing advanced discrete control techniques for the realization of the control system of a drive using a frequency controlled induction motor as an actuator is complicated not only by motor nonlinearities and saturation of state variables but also by the constraints imposed by the online implementation of the selected control algorithm. To have satisfactory operation of the ...


Online evolutionary control using a hybrid genetic based controller

IEEE Conference on Robotics, Automation and Mechatronics, 2004., 2004

Servo system controlled by the proposed hybrid GA based controller is presented in this paper. Due to their powerful optimization property, genetic algorithms are currently being investigated for development of a learning controller. However, because of time consuming in evolutionary process and the unstable response during learning period, most of genetic based controllers are implemented on off-line learning problems. To ...


Stabilizing control for an inverted pendulum with restricted travel

2009 American Control Conference, 2009

For the problem of stabilizing an inverted pendulum with restricted travel, a saturating control law is developed that satisfies the amplitude constraint on the cart and has a large region of attraction. The explicit expression of the region of attraction is also obtained. The analysis and design are performed based on the linearized model of the system, as in the ...


Correction to "Stochastic bang-bang control"

IEEE Transactions on Automatic Control, 1974

None


Computer Disk File Track Accessing Controller Design based upon Cell-to-Cell Mapping

1992 American Control Conference, 1992

The concept of cell-to-cell mapping is proposed for the track accessing controller design of computer disk file actuators. Conventional design approach uses the classical bang-bang control theory. The result does not include any structural resonance of the actuator, and the constraints are only imposed in an ad hoc fashion. No optimization results can be claimed. By working with the cell-to-cell ...


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Educational Resources on Bang-bang Control

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IEEE-USA E-Books

  • Computer control strategies for induction motor drives

    The problem of utilizing advanced discrete control techniques for the realization of the control system of a drive using a frequency controlled induction motor as an actuator is complicated not only by motor nonlinearities and saturation of state variables but also by the constraints imposed by the online implementation of the selected control algorithm. To have satisfactory operation of the motor and to ensure a good matching of its mathematical model, it is necessary to ensure that motor flux and stator current never exceed properly assigned values. Two control strategies for computer control are formulated and their effects on the system transient performance are investigated with particular attention to the problems of online application. In the first strategy the stabilizing feedback control for the nonlinear motor model is obtained by using the second method of Lyapunov for discrete systems. The resulting control law is a linear function of the state variables with coefficients which are nonlinear functions of the value assumed by the slip angular frequency in the corresponding sampling interval. In the second strategy the control law is of the bang-bang type and is obtained by assuming that the bilinear control variable may assume only two values.<>

  • Online evolutionary control using a hybrid genetic based controller

    Servo system controlled by the proposed hybrid GA based controller is presented in this paper. Due to their powerful optimization property, genetic algorithms are currently being investigated for development of a learning controller. However, because of time consuming in evolutionary process and the unstable response during learning period, most of genetic based controllers are implemented on off-line learning problems. To investigate this controller for the online learning, in this paper, a hybrid control architecture that integrates bang-bang controller with a genetic based controller is proposed. Bang-bang control is applied in the case of the actual output is far away from the set point (high error range). In such mode, bang-bang control is required to avoid the unstable response. In medium and small error ranges, a genetic based controller is applied as a learning controller. Simulation results demonstrate the effectiveness and learning ability of the proposed controller.

  • Stabilizing control for an inverted pendulum with restricted travel

    For the problem of stabilizing an inverted pendulum with restricted travel, a saturating control law is developed that satisfies the amplitude constraint on the cart and has a large region of attraction. The explicit expression of the region of attraction is also obtained. The analysis and design are performed based on the linearized model of the system, as in the study of Lin et al. The control law has two design parameters: T and k, which are both positive. As T approaches 0, the region of attraction approaches the maximal one. These parameters are chosen to optimize the transient response of the closed-loop system considering the input constraint, observation noise, etc. The effectiveness of the control law is demonstrated by simulations and experiments.

  • Correction to "Stochastic bang-bang control"

    None

  • Computer Disk File Track Accessing Controller Design based upon Cell-to-Cell Mapping

    The concept of cell-to-cell mapping is proposed for the track accessing controller design of computer disk file actuators. Conventional design approach uses the classical bang-bang control theory. The result does not include any structural resonance of the actuator, and the constraints are only imposed in an ad hoc fashion. No optimization results can be claimed. By working with the cell-to-cell mapping, the structural resonance can be included without any additional difficulty, and the constraints can also be included in the consideration while still satisfying the optimal control requirement. The results showed that when pure inertia model is assumed, classical bang-bang control configuration for the velocity profile is still obtained. When more complex model is used, the classical bang-bang control does not achieve optimization. A more delicate velocity profile is thus necessary.

  • A near-minimum time controller for two coordinating robots grasping an object

    The development of a near-minimum-time control for two coordinating robots manipulating an object in a workspace is addressed. Optimal control theory is used to derive a feedback controller which will enable the two robots to move an object from one place to another in near-minimum time. A dynamic model for the two robots and the load is established and then linearized using the average dynamics method. The model is continuously updated at every control interval, making it suitable for high-speed applications such as minimum-time problems. Bang-bang control theory in conjunction with synchronization of execution time for each joint is used to derive the near-minimum-time controller. The model and the control law are simulated for two distinct schemes. One is a master-slave configuration of the two robots, and the other is based on an optimal controller for both robots. The simulation results indicate that the proposed controller implemented for both schemes behaves favorably.<>

  • On the linear quadratic minimum-time problem

    A nontraditional minimum-time problem that includes quadratic-state and control-weighting terms in the performance index is investigated. This formulation provides a convenient solution to the problem that uses the solution of the Riccati equation to compute the optimal feedback gain and the optimal time. In some cases the latter is simply found using the derivative of the Riccati equation solution.<>

  • Application study of optimal control for beer saccharification temperature

    The beer saccharification temperature process has great phase lag, and the technology for brewage needs its control track the set point curve fast without overshoot. The normal PID algorithm apparently canpsilat satisfy these demands. This paper presents a new method called compound optimal control - combined model predictive control (MPC) with bang-bang control, The simulation shows that the method not only has faster tracking speed, higher control accuracy and no overshoot compared with the normal PID control and dynamic matrix control only, but also has stronger suppressing capability of disturbance than PID control. Thus this system can satisfy the technical demands, and also shorten the saccharification time simultaneously. And it need not complicated process modeling, can be carried out simply, so it can be extended to other temperature rising processes easily.

  • Numerical application of Szego's method for constructing Liapunov functions

    A numerical algorithm for the construction of Liapunov functions is described. This algorithm is based upon the method of Szego and is applicable to a particular class of systems. The algorithm is described for second-order systems although extension to systems of higher order would appear to be possible.

  • Third-order theory and bang-bang control of voice coil actuators

    A theory of voice coil motor actuators involving third-order differential terms in displacement that includes the inductance of the motor coil has been developed for bang-bang control time-optimal performance. Universal curves have been obtained using the theory that exhibits relationships between dimensionless quantities. The curves enable designers to choose appropriate actuator performance parameters to meet design objectives. Experimental methods have been described to determine some of the important parameters involved in the theory.



Standards related to Bang-bang Control

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Jobs related to Bang-bang Control

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