Application of Unscented Kalman Filter in adaptive control structure of two-mass system

Dróżdż, K.; Szabat, K.

doi:10.1109/epepemc.2016.7752157

Cited by 6 publications

(3 citation statements)

References 9 publications

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“…The unscented Kalman filter [45,52] discrete function description can be presented as set of follow steps:…”

Section: Classical and Fuzzy Ukf Algorithmsmentioning

confidence: 99%

“…In this study the fuzzy UKF is proposed to determine the mechanical state variables of the elastic system and the value the load machine's mechanical time constant. Contrary to [45], where the classical UKF was discussed, in the present paper a combination of the UKF with a fuzzy system is considered. The following variables are used as an input variables of the fuzzy system: the load machine's time constant (estimated value), the electromagnetic torque and the estimated shaft torque.…”

Section: Introductionmentioning

confidence: 99%

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A Fuzzy Unscented Kalman Filter in the Adaptive Control System of a Drive System with a Flexible Joint

Szabat

Wróbel

Dróżdż³

et al. 2020

Energies

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This paper presents an application of an Unscented- and a Fuzzy Unscented- Kalman Filter (UKF and FUKF) to the estimation of mechanical state variables and parameters in a drive system with an elastic connection. The cascade control structure incorporating an IP controller supported by two additional feedbacks and suitable adaptation mechanism is investigated in this study. The coefficients of the control structure are retuned on the basis of the value of mechanical parameters estimated by filter. The effectiveness of the proposed approaches (classical and fuzzy) is researched through simulation and experimental tests.

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“…The unscented Kalman filter [45,52] discrete function description can be presented as set of follow steps:…”

Section: Classical and Fuzzy Ukf Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Fuzzy Unscented Kalman Filter in the Adaptive Control System of a Drive System with a Flexible Joint

Szabat

Wróbel

Dróżdż³

et al. 2020

Energies

Self Cite

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“…The majority of the described observer design methods concern load velocity observers. Among them are Luenberger observers (linear or nonlinear) [31], Kalman filters (extended, unscented) [32,33], moving horizon estimators [34], multilayer observers [35,36], LQ observers [37], and fixed gain filters (FGFs) [13]. A separate group consists of observers designed by numerous techniques inspired by artificial intelligence, but usually, the stability of such solutions was not proven.…”

Section: Introductionmentioning

confidence: 99%

Observer-Based, Robust Position Tracking in Two-Mass Drive System

Kabziński

Mosiołek

2022

Energies

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Precise motion control remains one of the most important problems in modern technology. It is especially difficult in the case of two-mass systems with flexible coupling if only the motor position and velocity are measured. We propose a new methodology of control system design in this situation. The concept is founded on a robust observer design, based on a linear matrix inequality (LMI) solution. The observer cooperates with the original nonlinear controller. The presented approach allows us to solve the position tracking problem for a two-mass drive, with unknown parameters, in the presence of disturbances (for instance, nonlinear friction-like torques) acting on both ends of the flexible shaft. Under this set of assumptions, the problem was never solved previously. The closed-loop system stability is investigated, and the uniform ultimate boundedness of state estimation errors and tracking errors is proven using Lyapunov techniques. Numerical properties of the design procedure and characteristic features of the observer, controller, and closed-loop system are demonstrated by several examples.

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Kriging-Based Design for Robust High-Performance Control Systems

Micheli

Laflamme

2020

ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng.

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High-performance control systems (HPCS) are sophisticated vibration-mitigation devices that include active, semiactive, and hybrid systems. HPCS leverage feedback mechanisms to dynamically adjust the damping force in response to motion, offering a good mitigation performance over a wide excitation bandwidth. These damping systems are attractive for multihazard mitigation of civil structures. However, the application of HPCS necessitates the design and integration of a closed-loop control system that can be susceptible to local failure or reduction in performance in the form of, for example, malfunctions of HPCS components, noisy measurements, wear, aging, and power unavailability. It follows that these sources of uncertainties may cause concerns and impede the wide acceptability and deployment of HPCS. A solution is to enhance the robustness of the closed-loop configuration through, for example, added redundancies and/or more robust, yet more expensive, components. In this paper, a Kriging-based design procedure is presented enabling the robust design of closed-loop control systems. The design procedure consists of constructing a Kriging surrogate that maps uncertainties to structural performance, and using that surrogate to identify the most influential sources of uncertainties. After, these identified uncertainties are made more robust in order to decrease the variance in the HPCS performance over the lifetime of the structure. The performance of the HPCS is directly quantified through a life cycle cost analysis to obtain probability distributions on the expected financial impacts. The proposed procedure is demonstrated on a numerically simulated 39-story structure exposed to wind loads. Uncertainties in both the HPCS configuration (i.e., damping devices and sensors) and external load are considered. Results demonstrate that the proposed framework can be used to substantially improve the robustness of the closed-loop system. Also, through a comparison against a robust passive-viscous case, it is shown that robustly designed HPCS significantly outperform a passive system in terms of vibration mitigation and life cycle costs.

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Application of Unscented Kalman Filter in adaptive control structure of two-mass system

Cited by 6 publications

References 9 publications

A Fuzzy Unscented Kalman Filter in the Adaptive Control System of a Drive System with a Flexible Joint

A Fuzzy Unscented Kalman Filter in the Adaptive Control System of a Drive System with a Flexible Joint

Observer-Based, Robust Position Tracking in Two-Mass Drive System

Kriging-Based Design for Robust High-Performance Control Systems

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