Conferences related to Control nonlinearities

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2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

FUZZ-IEEE 2021 will represent a unique meeting point for scientists and engineers, both from academia and industry, to interact and discuss the latest enhancements and innovations in the field. The topics of the conference will cover all the aspects of theory and applications of fuzzy sets, fuzzy logic and associated approaches (e.g. aggregation operators such as the Fuzzy Integral), as well as their hybridizations with other artificial and computational intelligence techniques.


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 16th International Workshop on Advanced Motion Control (AMC)

AMC2020 is the 16th in a series of biennial international workshops on Advanced Motion Control which aims to bring together researchers from both academia and industry and to promote omnipresent motion control technologies and applications.


2020 IEEE 29th International Symposium on Industrial Electronics (ISIE)

ISIE focuses on advancements in knowledge, new methods, and technologies relevant to industrial electronics, along with their applications and future developments.


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Periodicals related to Control nonlinearities

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Applied Superconductivity, IEEE Transactions on

Contains articles on the applications and other relevant technology. Electronic applications include analog and digital circuits employing thin films and active devices such as Josephson junctions. Power applications include magnet design as well asmotors, generators, and power transmission


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 ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Circuits and Systems I: Regular Papers, IEEE Transactions on

Part I will now contain regular papers focusing on all matters related to fundamental theory, applications, analog and digital signal processing. Part II will report on the latest significant results across all of these topic areas.


Circuits and Systems II: Express Briefs, IEEE Transactions on

Part I will now contain regular papers focusing on all matters related to fundamental theory, applications, analog and digital signal processing. Part II will report on the latest significant results across all of these topic areas.


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Most published Xplore authors for Control nonlinearities

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Xplore Articles related to Control nonlinearities

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Data-based internal model controller design for a class of nonlinear systems

2005 International Conference on Control and Automation, 2005

An internal model control (IMC) design strategy is proposed for a class of nonlinear systems that can be described by data-based modeling technique called just-in-time learning (JITL). The proposed controller consists of a conventional linear controller augmented by a series of correction terms to account for nonlinearities in the system. The resulting controller is shown to have superior performance when ...


A cascaded sliding mode hybrid force/position controller

Proceedings of the IEEE International Symposium on Industrial Electronics, 2005. ISIE 2005., 2005

This paper presents a novel method for controlling force and position simultaneously using a sliding-mode position controller and a sliding-mode position error estimator for the position controller according to force error (which is used to control force essentially). The main advantage of this method is that there is no explicit control mode switching between distinct force and position controllers, but ...


Time varying approach to adaptive control of nonlinear systems

Proceedings of the 1997 American Control Conference (Cat. No.97CH36041), 1997

This work investigates a stabilizing control law for a plant with not necessarily known nonlinearities under the assumption that the dynamics of the system are slow relative to the sample period. We treat the coefficients of an affine model of the dynamics as unknown parameters. It is shown that it is feasible to construct an adaptive control law provided that ...


Torque and flux control of induction motors: a physically-based approach

Proceedings of IECON'94 - 20th Annual Conference of IEEE Industrial Electronics, 1994

We address the problem of torque and rotor flux control of induction motors perturbed by an unknown constant load torque. Our main contribution is the proof that this objective can be achieved without linearizing the motor dynamics. The design, which is presented as a variation of model matching, proceeds in two steps: 1) define a target closed loop dynamics compatible ...


Adaptive fuzzy control of a belt-driven precision positioning table

IEEE International Electric Machines and Drives Conference, 2003. IEMDC'03., 2003

Because of their lower cost, higher speed, and longer travel, belt drive positioning systems are quite desirable over screw-driven systems. However, belt drive systems are inherently difficult to control due to belt flexibility, stretch, backlash, and other nonlinearities. In this paper, a composite fuzzy controller, consisting of a feedback fuzzy controller and a feedforward acceleration compensator, is introduced to control ...


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Educational Resources on Control nonlinearities

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IEEE-USA E-Books

  • Data-based internal model controller design for a class of nonlinear systems

    An internal model control (IMC) design strategy is proposed for a class of nonlinear systems that can be described by data-based modeling technique called just-in-time learning (JITL). The proposed controller consists of a conventional linear controller augmented by a series of correction terms to account for nonlinearities in the system. The resulting controller is shown to have superior performance when compared with a linear IMC controller. This is evaluated by a case study of a polymerization reactor.

  • A cascaded sliding mode hybrid force/position controller

    This paper presents a novel method for controlling force and position simultaneously using a sliding-mode position controller and a sliding-mode position error estimator for the position controller according to force error (which is used to control force essentially). The main advantage of this method is that there is no explicit control mode switching between distinct force and position controllers, but one sliding-mode position controller, for which the force error affects the position error by means of a sliding-mode position error estimator, is used for both cases. With experimental results on a voltage-driven piezo actuator, submicron accuracy (a maximum position error of 0.2 μm) for position control and a maximum force error of 0.02 N are achieved. Also, it is shown that with this approach, the jump of control input (the main stability problem of using separate force and position controllers) is removed without losing control power.

  • Time varying approach to adaptive control of nonlinear systems

    This work investigates a stabilizing control law for a plant with not necessarily known nonlinearities under the assumption that the dynamics of the system are slow relative to the sample period. We treat the coefficients of an affine model of the dynamics as unknown parameters. It is shown that it is feasible to construct an adaptive control law provided that the plant is pointwise stabilizable. We investigate the general applicability of this technique by quantifying the restrictions required for closed loop stability of the adaptive system.

  • Torque and flux control of induction motors: a physically-based approach

    We address the problem of torque and rotor flux control of induction motors perturbed by an unknown constant load torque. Our main contribution is the proof that this objective can be achieved without linearizing the motor dynamics. The design, which is presented as a variation of model matching, proceeds in two steps: 1) define a target closed loop dynamics compatible with the physical model of the motor that delivers the desired torque and operates in a balanced regime; and 2) propose a nonlinear dynamic output feedback controller that insures asymptotic model matching. A complete proof of global asymptotic stability is given under the assumption of known motor parameters. When the motor resistances are unknown, a globally convergent adaptive scheme is also presented. Two key features of our physically-based design are: 1) the control law does not require measurement of rotor variables; and 2) it does not rely on nonlinear dynamics cancellation. The controller is designed without considering the classical Park's coordinate transformation of the motor model, therefore directly giving its implementable form.<<ETX>>

  • Adaptive fuzzy control of a belt-driven precision positioning table

    Because of their lower cost, higher speed, and longer travel, belt drive positioning systems are quite desirable over screw-driven systems. However, belt drive systems are inherently difficult to control due to belt flexibility, stretch, backlash, and other nonlinearities. In this paper, a composite fuzzy controller, consisting of a feedback fuzzy controller and a feedforward acceleration compensator, is introduced to control a belt drive precision positioning table. Using a linear encoder with a resolution of 0.5 /spl mu/m, zero final positioning error and RMS track following error of around 30 /spl mu/m are obtained. A self-tuning scheme based on evolutionary computation (EC) is then proposed to make this controller adaptive. The evolutionary computation optimizes the controller gains by experimentally running the controller on the actual system with a step command. The test results of the actual system have demonstrated the effectiveness and efficiency of the proposed self-tuning technique.

  • Linear approximations of nonlinear systems

    A method for designing an automatic flight controller for short and vertical take off aircraft is presently being developed at NASA Ames Research Center. This technique involves transformations of nonlinear systems to controllable linear systems and takes into account the nonlinearities of the aircraft. In general, the transformations cannot always be given in closed form. Using partial differential equations, an approximate linear system called the modified tangent model, was recently introduced. A linear transformation of this tangent model to Brunovsky canonical form can be constructed, and from this an approximation (about a state space point x0) of an exact transformation for the nonlinear system can be found. Here we show that a canonical expansion in Lie brackets about the point x0 yields the same modified tangent model.

  • Identification and compensation of gear backlash without output position sensor in high-precision servo systems

    High-performance position control can be improved by the compensation of gear backlash. This paper presents a compensation method that does not need an output position sensor. In the first section, two different methods of on- system backlash identification are described. One method is based on dynamic reaction to a small torque impulse injected by the motor, while the other analyses the change of torque at the end of the backlash dead zone in a quasi- stationary trajectory. The second section of the paper deals with backlash compensation. Based on the identified value of backlash, the angular error of the output shaft is reduced. A self-learning time-optimal control method is described. Experimental measurements demonstrate the excellent performance and accuracy of the compensated system.

  • Expert PID controller for an industrial process

    Online proportional-integral-derivative (PID) controller tuning can be effectively implemented using the rule-based expert system approach. Results are presented on the optimum and nearly invariant properties of a PID controller. An implementation of the results using an expert system approach is then presented together with some results using a simulation of the industrial process. Finally, the hardware interface of the expert system to the process is described.<<ETX>>

  • A controlled invariarice problem for the VTOL aircraft with bounded internal dynamics

    This paper discusses a problem of controlled invariance for the VTOL aircraft, namely we require the output of the system to stay on a given curve on the output space, with the requirement that the curve must be followed completely. The problem is solved essentially by means of a Lyapunov technique which recalls some results from the theory for slowly varying nonautonomous linear systems. The main obstacle encountered lies in the fact that the internal dynamics of the constrained system lose controllability in some "critical points" along the reference curve (close to the point where the reference curve is vertical). The overall closed loop system is characterized by an alternations of periods of stability and instability and its state is proved to be globally stable under some conditions. Simulations results are provided for the cases where the curve is a straight line and a circle.

  • Design and implementation of fuzzy-based PID controller

    Conventional proportional integral derivative (PID) controller is widely used in many industrial applications due to its simplicity in structure and ease of design. However, it is difficult to achieve the desired control performance in the presence of unknown nonlinearities, time delays, disturbances as well as changes in system parameters. Consequently several PID models have been suggested so at to alleviate these effects on the performance of the PID controllers. One such method is based on fuzzy logic technique which is considered much more appropriate when precise mathematical formulation is infeasible or difficult to achieve. Furthermore, some applications such as semiconductor packaging, computer disk drives, and ultra-precision machining require a fast and high precision processing. Consequently, there is the need to consider digital signal processor (DSP)-based fuzzy PID for use in such applications. Design and implementation of such technique is proposed in this paper. Results of simulation studies have demonstrated the feasibility of this controller since it produces fast response with smooth motion control.



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