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Yoichi Hori - One of the best experts on this subject based on the ideXlab platform.

  • a new model reference Adaptive Controller for four quadrant vector controlled induction motor drives
    IEEE Transactions on Industrial Electronics, 2012
    Co-Authors: A Ravi V Teja, Chandan Chakraborty, Suman Maiti, Yoichi Hori
    Abstract:

    In this paper, a new model reference Adaptive Controller (MRAC) for the speed estimation of the vector-controlled induction motor drive is presented. The proposed MRAC is formed using instantaneous and steady-state values of X (= v* × i where v = voltage and i = current vector in synchronously rotating reference frame), which is a fictitious quantity and has no physical significance. This formulation is not only simply realizable but also made the sensorless drive stable in all the four quadrants of operation. Speed estimation does not involve computation of stator or rotor flux. Requirement of no additional sensors makes the drive suitable for retrofit applications. A simple modification of the Controller can estimate the stator resistance in all the four quadrants of operation, if speed signal is available. The proposed MRAC-based speed sensorless vector control drive as well as the stator resistance estimation technique has been simulated in MATLAB/SIMULINK and experimentally validated through a dSPACE-1104-based laboratory prototype. A study on stability of such systems is also added.

  • model reference Adaptive Controller based rotor resistance and speed estimation techniques for vector controlled induction motor drive utilizing reactive power
    IEEE Transactions on Industrial Electronics, 2008
    Co-Authors: Suman Maiti, Chandan Chakraborty, Yoichi Hori
    Abstract:

    In this paper, a detailed study on the model reference Adaptive Controller (MRAC) utilizing the reactive power is presented for the online estimation of rotor resistance to maintain proper flux orientation in an indirect vector controlled induction motor drive. Selection of reactive power as the functional candidate in the MRAC automatically makes the system immune to the variation of stator resistance. Moreover, the unique formation of the MRAC with the instantaneous and steady-state reactive power completely eliminates the requirement of any flux estimation in the process of computation. Thus, the method is less sensitive to integrator-related problems like drift and saturation (requiring no integration). This also makes the estimation at or near zero speed quite accurate. Adding flux estimators to the MRAC, a speed sensorless scheme is developed. Simulation and experimental results have been presented to confirm the effectiveness of the technique.

Suman Maiti - One of the best experts on this subject based on the ideXlab platform.

  • a new model reference Adaptive Controller for four quadrant vector controlled induction motor drives
    IEEE Transactions on Industrial Electronics, 2012
    Co-Authors: A Ravi V Teja, Chandan Chakraborty, Suman Maiti, Yoichi Hori
    Abstract:

    In this paper, a new model reference Adaptive Controller (MRAC) for the speed estimation of the vector-controlled induction motor drive is presented. The proposed MRAC is formed using instantaneous and steady-state values of X (= v* × i where v = voltage and i = current vector in synchronously rotating reference frame), which is a fictitious quantity and has no physical significance. This formulation is not only simply realizable but also made the sensorless drive stable in all the four quadrants of operation. Speed estimation does not involve computation of stator or rotor flux. Requirement of no additional sensors makes the drive suitable for retrofit applications. A simple modification of the Controller can estimate the stator resistance in all the four quadrants of operation, if speed signal is available. The proposed MRAC-based speed sensorless vector control drive as well as the stator resistance estimation technique has been simulated in MATLAB/SIMULINK and experimentally validated through a dSPACE-1104-based laboratory prototype. A study on stability of such systems is also added.

  • model reference Adaptive Controller based rotor resistance and speed estimation techniques for vector controlled induction motor drive utilizing reactive power
    IEEE Transactions on Industrial Electronics, 2008
    Co-Authors: Suman Maiti, Chandan Chakraborty, Yoichi Hori
    Abstract:

    In this paper, a detailed study on the model reference Adaptive Controller (MRAC) utilizing the reactive power is presented for the online estimation of rotor resistance to maintain proper flux orientation in an indirect vector controlled induction motor drive. Selection of reactive power as the functional candidate in the MRAC automatically makes the system immune to the variation of stator resistance. Moreover, the unique formation of the MRAC with the instantaneous and steady-state reactive power completely eliminates the requirement of any flux estimation in the process of computation. Thus, the method is less sensitive to integrator-related problems like drift and saturation (requiring no integration). This also makes the estimation at or near zero speed quite accurate. Adding flux estimators to the MRAC, a speed sensorless scheme is developed. Simulation and experimental results have been presented to confirm the effectiveness of the technique.

Chandan Chakraborty - One of the best experts on this subject based on the ideXlab platform.

  • a new model reference Adaptive Controller for four quadrant vector controlled induction motor drives
    IEEE Transactions on Industrial Electronics, 2012
    Co-Authors: A Ravi V Teja, Chandan Chakraborty, Suman Maiti, Yoichi Hori
    Abstract:

    In this paper, a new model reference Adaptive Controller (MRAC) for the speed estimation of the vector-controlled induction motor drive is presented. The proposed MRAC is formed using instantaneous and steady-state values of X (= v* × i where v = voltage and i = current vector in synchronously rotating reference frame), which is a fictitious quantity and has no physical significance. This formulation is not only simply realizable but also made the sensorless drive stable in all the four quadrants of operation. Speed estimation does not involve computation of stator or rotor flux. Requirement of no additional sensors makes the drive suitable for retrofit applications. A simple modification of the Controller can estimate the stator resistance in all the four quadrants of operation, if speed signal is available. The proposed MRAC-based speed sensorless vector control drive as well as the stator resistance estimation technique has been simulated in MATLAB/SIMULINK and experimentally validated through a dSPACE-1104-based laboratory prototype. A study on stability of such systems is also added.

  • model reference Adaptive Controller based rotor resistance and speed estimation techniques for vector controlled induction motor drive utilizing reactive power
    IEEE Transactions on Industrial Electronics, 2008
    Co-Authors: Suman Maiti, Chandan Chakraborty, Yoichi Hori
    Abstract:

    In this paper, a detailed study on the model reference Adaptive Controller (MRAC) utilizing the reactive power is presented for the online estimation of rotor resistance to maintain proper flux orientation in an indirect vector controlled induction motor drive. Selection of reactive power as the functional candidate in the MRAC automatically makes the system immune to the variation of stator resistance. Moreover, the unique formation of the MRAC with the instantaneous and steady-state reactive power completely eliminates the requirement of any flux estimation in the process of computation. Thus, the method is less sensitive to integrator-related problems like drift and saturation (requiring no integration). This also makes the estimation at or near zero speed quite accurate. Adding flux estimators to the MRAC, a speed sensorless scheme is developed. Simulation and experimental results have been presented to confirm the effectiveness of the technique.

Naira Hovakimyan - One of the best experts on this subject based on the ideXlab platform.

  • mathcal l _1 Adaptive control for switching reference systems application to flight control
    arXiv: Optimization and Control, 2021
    Co-Authors: Steven Snyder, Pan Zhao, Naira Hovakimyan
    Abstract:

    This paper presents a framework for the design and analysis of an $\mathcal{L}_1$ Adaptive Controller with a switching reference system. The use of a switching reference system allows the desired behavior to be scheduled across the operating envelope, which is often required in aerospace applications. The analysis uses a switched reference system that assumes perfect knowledge of uncertainties and uses a corresponding non-Adaptive Controller. Provided that this switched reference system is stable, it is shown that the closed-loop system with unknown parameters and disturbances and the $\mathcal{L}_1$ Adaptive Controller can behave arbitrarily close to this reference system. Simulations of the short period dynamics of a transport class aircraft during the approach phase illustrate the theoretical results.

  • l1 Adaptive control for switching reference systems application to flight control
    IFAC-PapersOnLine, 2019
    Co-Authors: Steven Snyder, Pan Zhao, Naira Hovakimyan
    Abstract:

    Abstract This paper presents a framework for design and analysis of an L1 Adaptive Controller with switching reference systems. Use of switching reference systems allows the desired behavior to be scheduled across the operating envelope, which is often required in aerospace applications. The analysis uses a switched reference system that assumes perfect knowledge of uncertainties and uses corresponding non-Adaptive Controller. Provided that this switched reference system is stable, it is shown that the closed-loop system with unknown parameters and disturbances and the L1 Adaptive Controller can behave arbitrarily close to this reference system. Simulations of the short period dynamics of a transport class aircraft during the approach phase illustrate the theoretical results.

  • filter design for feedback loop trade off of l1 Adaptive Controller a linear matrix inequality approach
    AIAA Guidance Navigation and Control Conference and Exhibit, 2008
    Co-Authors: Naira Hovakimyan, Chengyu Cao, Kevin Wise
    Abstract:

    This paper presents a convex optimization method for the feedback-loop tradeoff of L1 Adaptive Controller. Both problems of performance improvement and time-delay margin maximization are shown to be cast into Linear Matrix Inequality (LMI) type conditions. First, each of these conditions is studied separately towards a distinct objective, and next two similar LMI algorithms are proposed for optimization of one of the objectives with a prespecified constraint on the other.

  • l1 Adaptive Controller for a missile longitudinal autopilot design
    AIAA Guidance Navigation and Control Conference and Exhibit, 2008
    Co-Authors: Jiang Wang, Chengyu Cao, Naira Hovakimyan, Richard E Hindman, Brett D Ridgely
    Abstract:

    This paper considers application of L1 Adaptive output feedback Controller to a missile longitudinal autopilot design. The proposed Adaptive Controller has satisfactory performance in the presence of parametric uncertainties and time-varying disturbances. Simulations demonstrate the benefits of the control method and compare the results to Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) with Loop Transfer Recovery (LTR) design.

  • l 1 Adaptive Controller for nonlinear systems in the presence of unmodelled dynamics part ii
    American Control Conference, 2008
    Co-Authors: Chengyu Cao, Naira Hovakimyan
    Abstract:

    This paper presents a novel Adaptive control methodology for a class of uncertain nonlinear systems in the presence of unmodelled dynamics. The Adaptive Controller ensures uniformly bounded transient response for system's both input and output signals simultaneously. The performance bounds can be systematically improved by increasing the adaptation gain.

Tamer Basar - One of the best experts on this subject based on the ideXlab platform.

  • Adaptive Controller design for tracking and disturbance attenuation in parametric strict feedback nonlinear systems
    IEEE Transactions on Automatic Control, 1998
    Co-Authors: Zigang Pan, Tamer Basar
    Abstract:

    The authors develop a systematic procedure for obtaining robust Adaptive Controllers that achieve asymptotic tracking and disturbance attenuation for a class of nonlinear systems which are described in the parametric strict-feedback form and are subject to additional exogenous disturbance inputs. Their approach to Adaptive control is performance-based, where the objective for the Controller design is not only to find an Adaptive Controller, but also to construct an appropriate cost functional, compatible with desired asymptotic tracking and disturbance attenuation specifications, with respect to which the Adaptive Controller is "worst case optimal". Three main issues of the paper are: the backstepping methodology, worst case identification schemes, and singular perturbations analysis. Closed-form expressions have been obtained for an Adaptive Controller and the corresponding value function. A numerical example involving a third-order system is given.

  • Adaptive Controller design for tracking and disturbance attenuation in parametric strict feedback nonlinear systems
    IFAC Proceedings Volumes, 1996
    Co-Authors: Zigang Pan, Tamer Basar
    Abstract:

    Abstract We develop a systematic procedure for obtaining robust Adaptive Controllers that achieve asymptotic tracking and disturbance attenuation for nonlinear systems in parametric-strict-feedback form and subject to additional exogenous disturbance inputs. Our approach is performance based, where the objective is to find not only an Adaptive Controller, but also an appropriate cost functional, compatible with desired asymptotic tracking and disturbance attenuation specifications, with respect to which the Adaptive Controller is "worst-case optimal." Using the backstepping methodology, worst-case identification schemes, and singular perturbations analysis, we obtain closed-form expressions for the solutions of associated Hamilton-Jacobi-Isaacs equations or inequalities, thereby guaranteeing satisfaction of dissipation inequalities for the Adaptive Controllers.