Adaptive Suppression of Multiple Time-Varying Unknown Vibrations Using an Inertial Actuator

Landau, Ioan Doré; Alma, Marouane; Martínez, John J.; Buche, Gabriel

doi:10.1109/tcst.2010.2091641

Cited by 45 publications

(74 citation statements)

References 17 publications

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“…A detailed description of the system can be found in [18]. The proposed method was used to design a controller capable of rejecting a sinusoidal disturbance with a time-varying frequency.…”

Section: Simulation Resultsmentioning

confidence: 99%

Fixed-order LPV controller design for rejection of a sinusoidal disturbance with time-varying frequency

Emedi

Karimi

2012

2012 IEEE International Conference on Control Applications

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“…A detailed description of the system can be found in [18]. The proposed method was used to design a controller capable of rejecting a sinusoidal disturbance with a time-varying frequency.…”

Section: Simulation Resultsmentioning

confidence: 99%

Fixed-order LPV controller design for rejection of a sinusoidal disturbance with time-varying frequency

Emedi

Karimi

2012

2012 IEEE International Conference on Control Applications

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“…Researchers have recognized that the crucial task of enhanced MRAC for PMSM systems is to reject various external disturbances and improve robustness in various uncertainties. Landau et al proposed a direct feedback adaptive regulation scheme to suppress multiple unknown and/or time-varying vibrations, and minimized the residual force by applying an appropriate control effort through the internal model principle and Youla-Kucera parameterization [6]. However, performance is affected by the model and unmodeled dynamics because this approach introduced a dynamic model for external disturbances to the controller.…”

Section: State Of the Artmentioning

confidence: 99%

Enhanced Model Reference Adaptive Control based on Data-driven Technique for Permanent Magnet Synchronous Motors with Uncertainties

Qiao¹,

Liu²,

Zong³

2017

JESTR

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Precise velocity control of permanent magnet synchronous motors (PMSMs) is challenging due to the uncertainties induced by the mathematical model, unmodeled dynamics, and various disturbances; consequently, the traditional model reference adaptive control (MRAC) for PMSMs becomes questionable. In order to improve the traditional MRAC and lessen the influence of various sources of uncertainty, this study proposes an enhanced MRAC approach based on datadriven technique. First, the approach established an equivalent differential expression linear model for the discrete-time nonlinear description of PMSM and designed a data-driven controller using a model-free adaptive technique. This design depended on the unique bounded parameter referred as pseudo-partial-derivative (PPD) that was a slowly time-varying parameter relating to the system action point or system dynamics. Second, the approach identified the parameter PPD using Popov criterion to ensure the asymptotic stability of the controlled system. Finally, the approach was simulated and applied on a 50 kW PMSM drive of Toyota Prius II hybrid electric vehicles to demonstrate the effects of different control parameters. Results show that the proposed approach does not suffer from the drawback of the modeling process and unmodeled dynamics and provides improved velocity-tracking precision against parameter variations and external disturbances. When the weight factor increases from 0.1 to 1 or the pseudo-orders from 1 to 5, the velocity presents high robustness. Moreover, the approach yields satisfactory disturbance rejection and fault tolerance compared with the traditional MRAC even if some input and output (I/O) data are missing. This study solves the problem of dependence on plant models for the traditional MRAC and achieves better suppression of uncertainties, demonstrating the effective applications of this approach for actual nonlinear motor systems with uncertainties.

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“…and the normalizing signal m(k) is given by (17). In implementing the above scheme we also need to monitor the covariance matrix P (t) to make sure it does not become small in some directions i.e.…”

Section: B Adaptive Control Design: Unknown Disturbance Casementioning

confidence: 99%

Robust stability and performance of adaptive jitter supression in laser beam pointing

Jafari¹,

Ioannou²,

Fitzpatrick³

et al. 2013

52nd IEEE Conference on Decision and Control

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Abstract-This paper studies the robustness and performance of an adaptive scheme for suppression of laser beam jitter in the presence of unmodeled dynamics in a continuoustime formulation. To demonstrate the level of performance that can be achieved in the case of known disturbances, at first we consider the ideal case (non-adaptive) when a complete information about characteristics of the noise-corrupted periodic disturbance is available. Then the adaptive case when the disturbance is unknown with time-varying characteristics is investigated. The results show under what conditions jitter suppression can be achieved and what parameters contribute to the performance of the adaptive control scheme. Numerical simulations are given to demonstrate the efficacy of the robust adaptive control law.

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Adaptive Suppression of Multiple Time-Varying Unknown Vibrations Using an Inertial Actuator

Cited by 45 publications

References 17 publications

Fixed-order LPV controller design for rejection of a sinusoidal disturbance with time-varying frequency

Fixed-order LPV controller design for rejection of a sinusoidal disturbance with time-varying frequency

Enhanced Model Reference Adaptive Control based on Data-driven Technique for Permanent Magnet Synchronous Motors with Uncertainties

Robust stability and performance of adaptive jitter supression in laser beam pointing

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