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1

Generalized state space model and small signal stability analysis of Z-source converter

Kouhanjani Masoud Jokar, Soltani Sina, Mardaneh Mohammad

Archives of Electrical Engineering

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2023

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Vol. 72, nr 1

173--188

EN

This paper proposes two nonlinear exact and simple state space models of a Z-source converter (ZSC) connected to an ac grid. A generic model of a ZSC accompanied with proper controllers are proposed and a dynamic model of the whole system is derived; as a result, based on a simple one, an equivalent block diagram of the current-controlled ZSC system is proposed. The ac small signal stability method is applied and the impact of controller parameters on network’s stability is discussed. Besides, overall system dynamic performance has been assessed in the event of perturbations. Time-domain simulations have been implemented in PSCAD/EMTDC to validate the accuracy of the models and effectiveness of the proposed controllers. The results of the exact model are compared with the response of the equations which are applied in MATLAB.

2

Modeling of two-wheeled self-balancing robot driven by DC gearmotors

Frankovsky P., Dominik L., Gmiterko A., Virgala I., Kurylo P., Perminova O.

International Journal of Applied Mechanics and Engineering

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2017

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Vol. 22, no. 3

739--747

EN

This paper is aimed at modelling a two-wheeled self-balancing robot driven by the geared DC motors. A mathematical model consists of two main parts, the model of robot’s mechanical structure and the model of the actuator. Linearized equations of motion are derived and the overall model of the two-wheeled self-balancing robot is represented in state-space realization for the purpose of state feedback controller design.

3

Disturbance modeling and state estimation for offset-free predictive control with state-space process models

Tatjewski P.

International Journal of Applied Mathematics and Computer Science

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2014

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Vol. 24, no. 2

313--323

EN

Disturbance modeling and design of state estimators for offset-free Model Predictive Control (MPC) with linear state-space process models is considered in the paper for deterministic constant-type external and internal disturbances (modeling errors). The application and importance of constant state disturbance prediction in the state-space MPC controller design is presented. In the case with a measured state, this leads to the control structure without disturbance state observers. In the case with an unmeasured state, a new, simpler MPC controller-observer structure is proposed, with observation of a pure process state only. The structure is not only simpler, but also with less restrictive applicability conditions than the conventional approach with extended process-and-disturbances state estimation. Theoretical analysis of the proposed structure is provided. The design approach is also applied to the case with an augmented state-space model in complete velocity form. The results are illustrated on a 2 x 2 example process problem.

4

An importance measure for multi-component systems with Semi-Markov dynamics

Hellmich M., Berg H. P.

Journal of Polish Safety and Reliability Association

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2012

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Vol. 3, No. 1

147--156

EN

We consider semi-Markov reliability models of multi-component systems with a discrete state space, general enough to include systems with maintenance or repair. We assume that for all system states the functioning or failure of each component is specified. In this setup we propose a component importance measure which is close in spirit to the classical steady state Barlow–Proschan importance measure for repairable binary coherent systems. We discuss our importance measure to some extent, highlighting the relation to the classical Barlow–Proschan measure, and present formulas expressing it in terms of quantities easily obtained from the building blocks of the semi-Markov process. Finally an example of a two-component cold standby system with maintenance and repair is presented which illustrates how our importance measure can be used in practical applications.

5

Optimality of the auxiliary particle filter

Douc R., Moulines É, Olsson J.

Probability and Mathematical Statistics

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2009

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Vol. 29, Fasc. 1

1--28

EN

In this article we study asymptotic properties of weighted samples produced by the auxiliary particle filter (APF) proposed by Pitt and Shephard [17]. Besides establishing a central limit theorem (CLT) for smoothed particle estimates, we also derive bounds on the Lp error and bias of the same for a finite particle sample size. By examining the recursive formula for the asymptotic variance of the CLT we identify first-stage importance weights for which the increase of asymptotic variance at a single iteration of the algorithm is minimal. In the light of these findings, we discuss and demonstrate on several examples how the APF algorithm can be improved.

6

Prognozowanie trwałości środków technicznych z wykorzystaniem wielu wskaźników degradacji i zdarzeń awaryjnych w ujęciu modelu ciągłej przestrzeni stanów

Zhou Y., Ma L., Mathew J., Sun Y., Wolff R.

Eksploatacja i Niezawodność

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2009

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nr 4

72-81

PL

Prognozowanie trwałości środków z wykorzystaniem wskaźników degradacji wiąże się z dwoma zagadnieniami praktycznymi:(1) identyfikacją progów niepewnego uszkodzenia dla wskaźników degradacji oraz (2) łączeniem licznych wskaźników degradacji otrzymanych na podstawie danych z monitorowania stanu. Model degradacji w przestrzeni stanów stanowi efektywne podejście do tych dwóch zagadnień. Jednakże dotychczasowe badania dotyczące tego modelu w dużej mierze przyjmują założenie dyskretnego czasu lub dyskretnych stanów, które wymaga równych odstępów między przeglądami lub dyskretyzacji ciągłych wskaźników degradacji. Aby uniknąć konieczności zakładania dyskretnego czasu i dyskretnych stanów, w niniejszej pracy zaproponowano model przestrzeni stanów oparty na procesie Gamma. Proces Gamma charakteryzuje własność monotoniczna rosnącą, która odpowiada nieodwracalnym procesom degradacji środków technicznych w trakcie jednego cyklu serwisowego. Własność monotoniczna rosnąca ułatwia również ustalenie funkcji prawdopodobieństwa, gdy brane są pod uwagę czasy uszkodzeń. W artykule sformułowano algorytmy estymacji parametrów oraz prognozowania czasu życia dla modelu przestrzeni stanów opartego na procesie Gamma. Dodatkowo określono metodę oceny efektywności wskaźników w modelowaniu degradacji. Proponowany model przestrzeni stanów oparty na procesie Gamma oraz jego algorytmy weryfikowano przy użyciu danych symulacyjnych oraz danych terenowych pozyskanych z przedsiębiorstwa zajmującego się ciekłym gazem ziemnym.

EN

Two practical issues are involved in asset life prediction using degradation indicators: (1) identifying uncertain failure thresholds of degradation indicators and (2) fusing multiple degradation indicators extracted from condition monitoring data. The state space degradation model provides an effective approach to address these two issues. However, existing research on the state space degradation model largely adopts a discrete time or states assumption which requires equal inspection intervals or discretising continuous degradation indicators. To remove the discrete time and states assumptions, this paper proposes a Gamma-based state space model. The Gamma process has a monotonically increasing property that is consistent with the irreversible degradation processes of engineering assets within a single maintenance cycle. The monotonically increasing property also makes the establishment of the likelihood function more straightforward when failure times are considered. In this paper, parameter estimation and lifetime prediction algorithms for the Gamma-based state space model are developed. In addition, an effectiveness evaluation approach for indicators in degradation modelling is established. The proposed Gamma-based state space model and algorithms are validated using both simulated data and a field dataset from a liquefied natural gas company.

7

Obtaining State Space Model from Bond Graph Model with Derivative Causality Using Laplace Transform

Antić D., Stanković L., Nikolić V.

Machine Dynamics Problems

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2003

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Vol. 27, No. 2

5-10

EN

One method for obtaining the state space model from the bond graph model is based on using signal graph as an indirect tool. In case the signal graph nodes are time functions, the direct state space model obtaining is only possible for bond graphs with integral causality. Interposing the Laplace operator "s" into the signal graph is proposed in this paper. Thus, in case of derivative causality presence in the bond graph as well, the necessary transformations of the equations are minimized.

8

State space models of electrohydraulic servo drives

Milecki A.

Archiwum Technologii Maszyn i Automatyzacji

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2003

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Vol. 23, Nr 2

175-180

EN

In the paper the theoretical models of electrohydraulic servo drive unit are discussed. The classical model presented as transfer function is shown. In the paper set of differential equations describing electrohydraulic servo drive units are presented and discussed. Then linear and non linear state space models of electrohydraulic servo drives are shown. In non linear models such non-linearities like square root flow characteristic, friction characteristic and parameter dependences on piston position are included. The presented in the paper model enables design different modern controllers.

PL

W artykule przedstawiono klasyczny, oparty na transmitancjach operatorowych, model serwo-napędu elektrohydraulicznego. Podano podstawowe równania pozwalające na stworzenie liniowego modelu stanu serwonapędu elektrohydraulicznego. Zaproponowano również nieliniowy model stanu serwonapędu. Uwzględniono w nim takie nieliniowości, jak pierwiastkowa charakterystyka przepływu, tarcie i zależność parametrów od położenia tłoka siłownika hydraulicznego. Zwrócono uwagę na zalety przedstawienia obiektu za pomocą równań stanu.

9

Fuzzy adaptive-predictive decentralized control of discrete time interconnected systems

Tzafestas S., Kyriannakis E., Apostolikas G.

Systems Science

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2002

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Vol. 28, nr 1

5-24

EN

Proposes an approach for the design of discrete-time decentralized control systems with m-step delay sharing information pattern, employing model-based predictive control (MBPC) combined with fuzzy prediction for the interconnections among the subsystems. A state space model is used at each control station to predict the corresponding subsystem output over a long-range time period. The interaction trajectories are considered to be non-linear functions of the states of the subsystems. For all cases the interconnections and the necessary predictions for them are estimated by an appropriate adaptive fuzzy identifier based on the generation of linguistic IF-THEN rules and the on-line construction of a common fuzzy rule base. Representative computer simulation results are provided and compared for nontrivial example systems.