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Bladed disks are critical parts of aeronautic turbojet engines requiring numerous dynamic analysis tests to fully achieve their design process. This work presents subspace state-space identification techniques for estimation of modal parameters of bladed disks using realistic although numerically generated test case data. Indeed, modal testing of bladed disks can exhibit high modal density leading to modal estimation issues. This study focuses on subspace state-space identification framework as it is an efficient way to process vector valued time series and thus to estimate modal parameters in a context of high modal density. In order to evaluate the techniques of interest, a versatile modal model has been specifically implemented to simulate data representative of full scale rotating aeronautic fan modal tests. This model is easily adjustable allowing to evaluate the identification methods in a more or less severe estimation context. The performance of the investigated methods is discussed and compared with the prescribed parameters of the model. Moreover, different techniques to estimate the order of the associated state-space model are reviewed and tested over several simulated configurations. Finally, a method to evaluate the uncertainties over the model parameters using covariance of estimator results and pseudospectrum computation is proposed and discussed over the investigated test cases. [ABSTRACT FROM AUTHOR]

The article deals with the approach to designing robust system for stabilization of equipment assigned for operation on ground moving vehicles. The mathematical model of stabilization system including non-linear differential equations and state space representation is given. The features of basic external disturbances specific for ground moving vehicles are represented and analysed. The classification of external disturbances is suggested. Expressions for forming filters providing simulation of specific external disturbances are derived. The basic peculiarities of synthesis of spatial stabilization system for ground moving vehicle equipment are described. The simulation results are represented. During simulation, irregularities of different types are taken into consideration. The description of means for simulation of stabilization system of the studied type are considered. The obtained results can be useful for equipment operated on moving vehicles of the wide class. [ABSTRACT FROM AUTHOR]

Plate-like structures in channel flow are commonly found in engineering. This paper reports a theoretical study on the static aeroelastic instability of an inverted cantilevered plate in an inviscid channel flow through the state space. This study begins with the kernel function of the flow potential determined in the Fourier domain with the help of the mirror image method. Then, the instability equation is derived from the operator theory and transformed in the state space. Finally, with Glauert's expansion, model functions, and error functions, the instability problem of such a plate has been modeled as a mathematical function approximation problem and solved by the least squares method. The derived instability equation is considered at the continuum level of description, and no approximation appears at the first equation level. The convergence and reliability of the proposed modeling and its solutions approximation are entirely tested, and it can successfully predict the instability boundary, behavior, and the channel effect. Numerical results show that the decreased channel height and asymmetric plate placement in the channel significantly decrease the critical flow velocity. The plate instability modes are close to the plate's first natural ones and not sensitive to the channel parameters. This conclusion allows further theoretical exploration of a semi-analytical approximation of the instability boundary from the obtained instability equation. The current modeling strategy in a continuum sense may provide a new idea and essential reference for other instability problems. [ABSTRACT FROM AUTHOR]

In this paper, a new perfect control law dedicated to nonminimum-phase unstable LTI MIMO systems governed in the continuous-time state–space domain is proposed. Two algorithms are investigated, one of which has turned out to be definitely accurate. Henceforth, the inverse model control-based formula can be applied to any right-invertible plants having more input than output variables. Last, not least, through the application of some generalized inverses, the perfect control procedure guarantees the structural stability behavior even for unstable systems. Thus, the notion of the nonminimum-phase property should be understood in terms of a possible achieveability covering the entire class of LTI MIMO continuous-time plants. Theoretical and practical simulation examples performed in the Matlab/Simulink environment confirm the feasibility of the newly introduced approach. • A new perfect control law devoted to nonminimum-phase unstable systems is offered. • The IMC-originated approach is derived from the application of generalized inverses. • A new method certifies a stability for unstable and nonminimum-phase systems. • A new procedure is associated with the continuous-time state–space MIMO framework. • Theoretical and practical scenarios confirm the correctness of the new solution. [ABSTRACT FROM AUTHOR]

Chlorine is a widely used disinfectant and proxy for water quality (WQ) monitoring in water distribution networks (WDN). Chlorine-based WQ regulation and control aim to maintain pathogen-free water. Chlorine residual evolution within WDN is commonly modeled using the typical single-species decay and reaction dynamics that account for network-wide, spatiotemporal chlorine concentrations only. Prior studies have proposed more advanced and accurate descriptions via multi-species dynamics. This paper presents a host of novel state-space, control-theoretic representations of multi-species water quality dynamics. These representations describe decay, reaction, and transport of chlorine and a fictitious reactive substance to reflect realistic complex scenarios in WDN. Such dynamics are simulated over space- and time-discretized grids of the transport partial differential equation and the nonlinear reaction ordinary differential equation. To that end, this paper (i) provides a full description on how to formulate a high fidelity model-driven state-space representation of the multi-species water quality dynamics and (ii) investigates the applicability and performance of different Eulerian-based schemes (Lax–Wendroff, backward Euler, Crank–Nicolson, and Implicit Upwind) and Lagrangian-based schemes (Method of Characteristics) in contrast with EPANET and its EPANET-MSX extension. Numerical case studies reveal that the Implicit Upwind scheme, Method of Characteristics, and Lax–Wendroff scheme outperform other schemes with reliable results under reasonable assumptions and limitations. [ABSTRACT FROM AUTHOR]

In most financial markets, prices for long-maturity derivatives are not readily available due to illiquidity. This reality is particularly common in bond markets, as it is very challenging to model prices consistently???for medium-to-long-term bonds under a single specification of the underlying interest rate process. We develop a bond market state-space model that incorporates uncertainty in the underlying interest rate process parameters. Our state-space representation, coupled with the complementary Kalman filtering, provides a modeling configuration that permits for liquidity risk management and pricing that is designed in a consistent fashion for both medium- and long-term bonds. As an example, we constructed a state-space bond market modeling system formulated on the two-factor Vasicek interest rate model. Wherein, the interest rate model is subject to noise for medium-to-long-term bond maturities and follows an unobservable process. We demonstrate our Kalman filter algorithm using the observed United States (US) 10 year bond yield data. [ABSTRACT FROM AUTHOR]

This study theoretically investigates the modeling of spherical catalytic self-phoretic magnetic Janus microrobot (MJR) evolving in uniform viscous flow. A 2-D state-space representation of the MJR is developed, exhibiting a state-dependent-coefficient (SDC) form. To evaluate the consistency of the modeling formalism, a dual Kalman filter (DKF) methodology is employed with respect to experimental results when unknown parameters or uncontrollable inputs are considered. In fact, the self-phoretic thrust mechanism and the magnetodynamics of the MJR are not well-known. SDC-DKF is implemented, and we find that there is good agreement between the dynamics computed from our theoretical predictions and the experimental observations in a wide range of model parameter variations. [ABSTRACT FROM AUTHOR]

• An integrated method to deal with nonlinear responses of rotor-bearing system. • Apply FRF-based HBM to predict nonlinear response of large-scale rotor models. • Obtain FRF matrix using spectral decomposition in second-order state space. • Deriving rotational speed-eigen-solutions relationship via Taylor series expansion. • Model reduction for eigen-problems with large asymmetric matrices. In the development and maintenance of gas turbines, the efficient computation to predict the responses of large-scale and complex rotating structures with local nonlinear joints is crucial. In this paper, a novel integrated strategy as a trade-off between time expense and accuracy for response prediction in large scale rotor-bearing system with local nonlinear joints is developed using the frequency response function based harmonic balance method (FRF-based HBM). To tackle the numerical challenges arising from asymmetrical matrices in rotating systems, a new approach is presented to compute the FRF using a spectral decomposition in second-order state space. Furthermore, the analytical mapping of eigen-solution against rotational speed based on Taylor series expansion is developed to address the computational expenses associated with speed-dependent FRF matrices. Then, a model reduction is adopted to mitigate the additional computational costs arising from the high-order unsymmetric matrices. The superior qualities and practical value in engineering of the new strategy are demonstrated on two numerical cases. The first is a one-dimensional rotor-bearing model subjected to the cubic nonlinear force under investigation, this approach shows an exceptionally high level of accuracy in response prediction, when compared to both the Runge-Kutta method and the harmonic balance method (HBM) without any form of model reduction. Another is a large-scale rotor-bearing model with two squeeze film dampers, the computational speed, being thousands of times faster than the HBM method and several times faster than the HBM considering the CMS model reduction, underscores the efficiency of this approach. [ABSTRACT FROM AUTHOR]

Recently, variable digital filters (VDFs) have become an essential research topic. This paper presents a simple method for the design of infinite impulse response (IIR) VDFs with high tuning accuracy. First, VDFs were created using a state-space model based on a frequency transformation, which requires the inverse matrix and the square root that leads to high computational cost. Then a new algorithm was implemented to generate the same VDFs absent the complex calculations that utilized negative binomial and Taylor series approximations in a simple state-space formulation. This algorithm provides high-accuracy approximations of the inverse matrix and square root compared to other algorithms that have been developed. Thus, the proposed VDFs have high tuning accuracy with respect to finite wordlength effects. [ABSTRACT FROM AUTHOR]

Based on the general structure of mechanical systems described by their state-space representation, the Takagi–Sugeno fuzzy modeling, and the controllability property of fuzzy systems, an algebraic and practical approach to computing the fuzzy gain capable of ensuring the stability property of the Takagi–Sugeno fuzzy model is proposed in this article. The main idea consists of finding a continuous fuzzy gain such that any linear behavior, defined by the adequate selection of eigenvalues, is induced in the closed-loop fuzzy system. Therefore, by continuity, if the fuzzy model is an approximation sufficiently close to the mechanical system, then such a nonlinear system is also stabilized by the fuzzy controller. A notable advantage of the proposed method, when compared with similar approaches, is the simplicity of the resulting gain. The validity of the approach is illustrated through the numerical simulation of a sufficiently complex nonlinear system. [ABSTRACT FROM AUTHOR]

Classical microwave circuit theory is incapable of representing some phenomena at the quantum level. To include quantum statistical effects, various theoretical treatments can be employed. Quantum input-output network (QION) theory is one such treatment. Another formalism, called SLH theory, incorporates scattering matrices (S), coupling vectors (L), and system Hamiltonians (H). These theoretical treatments require a reformulation of classical microwave theory. To make these topics comprehensible to an electrical engineer, we demonstrate some underpinnings of microwave quantum optics in terms of microwave engineering. For instance, we equate traveling-wave phasors in a transmission line ($V_0^+$) directly to bosonic field operators. Furthermore, we extend QION to include a state-space representation and a transfer function for a single port quantum network. This serves as a case study to highlight how microwave methodologies can be applied in open quantum systems. Although the same conclusion could be found from a full SLH theory treatment, our method was derived directly from first principles of QION.

• The original contribution of the paper is a dq-real domain admittance transfer matrix model of PV-qZ systems. • The study presents some of the the two main origins of instability in multi-terminal AC grid-connected PV-qZ systems. • The study also illustrates the weakness of GNC related to stability assessment and grid partition points. Photovoltaic (PV) power systems are becoming one of the most popular green power systems. Power converters are used in these systems. Among them, quasi-Z-source inverters (qZSIs) are currently on the rise. However, instabilities can appear in multi-terminal AC grid-connected power electronics, such as PV power systems, due to the interaction between power electronic controls and the grid. Modeling of qZSI-based PV power systems is lacking in the literature and stability assessment of grid-connected qZSI-based PV power systems is not yet well understood. Accordingly, the present paper contributes with an s -domain dq -real admittance transfer matrix model of qZSI-based PV power systems derived from their small-signal state-space averaged model. The paper also describes a systematic procedure to study multi-terminal AC grid-connected qZSI-based PV power systems by the nodal admittance method, where the proposed qZSI-based PV power system model is incorporated into the nodal admittance matrix to study stability concerns. Thus, AC grid dynamics in the presence of qZSI-based PV power systems can be investigated using impedance-based stability criteria. The proposed model and the procedure are applied in a stability study of two applications where solutions for improving stability issues are presented. In these applications, the two main causes of instabilities in AC-grid connected PV-qZ systems are analyzed in detail. The study is validated by PSCAD/EMTDC simulation.. [ABSTRACT FROM AUTHOR]

This study presents a method for small‐signal analysis of an advanced, multi‐variable control system for variable speed hydropower (VSHP) plants. A model predictive controller (MPC) optimises the power plant performance. In parallel, a virtual synchronous generator‐type (VSG) converter control ensures that the VSHP contributes to virtual inertia and frequency control of the power system. The aim of the small‐signal analysis is to parametrise the cost function of the MPC to minimise oscillatory modes between the VSHP hydraulic system and the power system. A state‐space representation of the MPC is developed by assuming a stable steady‐state operating point equal to the reference values of the MPC cost function, and that no constraints are active. This state‐space representation allows for small‐signal analysis of the power system, including the MPC. The results show that the modes between the hydraulic system and the power system are well‐damped and negligible when the costs of deviations in the hydraulic system are low compared to the cost of deviations in the VSG power reference. Thus, these modes do not constrain the tuning of the VSG. The VSHP power output can, therefore, be optimised independently through the VSG controller to damp power oscillations and reduce frequency deviations. [ABSTRACT FROM AUTHOR]

The LLC resonant converter has been widely used in switched power supply covering several kinds of applications. Although it has been the focus of numerous analysis, their general time-domain (TD) solution is not completely enclosed due to its complexity given by the multiple resonance nature and its variable structure behavior. Consequently, the LLC converter design is also impaired by the lack of an enclosed TD solution. To overcome these issues, this article systematically presents a highly accurate TD solution of the LLC converter supplying a light-emitting diode (LED) load, which is obtained from the state-space representation direct TD solution. Dissimilar to preceding analyses, all the converter states are considered and no current and voltage sinusoidal or average value approximations are taken. Finally, supported by the TD analysis, a new LLC LED driver design procedure is introduced, which is oriented by weighted-average-efficiency concept and constraints that ensure zero voltage switching, enough power gain, and practical switching frequency range over a wide operating window. Experimental results show the feasibility of the proposed design procedure as well as the accurate TD behavior prediction of the LLC converter supplying an LED load. This article is accompanied by active content that exemplifies the proposed TD solution and design procedure. [ABSTRACT FROM AUTHOR]

Human-centered artificial intelligence is increasingly deployed in professional workplaces in Industry 4.0 to address various challenges related to the collaboration between the operators and the machines, the augmentation of their capabilities, or the improvement of the quality of their work and life in general. Intelligent systems and autonomous machines need to continuously recognize and follow the professional actions and gestures of the operators in order to collaborate with them and anticipate their trajectories for avoiding potential collisions and accidents. Nevertheless, the recognition of patterns of professional gestures is a very challenging task for both research and the industry. There are various types of human movements that the intelligent systems need to perceive, for example, gestural commands to machines and professional actions with or without the use of tools. Moreover, the interclass and intraclass spatiotemporal variances together with the very limited access to annotated human motion data constitute a major research challenge. In this paper, we introduce the gesture operational model, which describes how gestures are performed based on assumptions that focus on the dynamic association of body entities, their synergies, and their serial and non-serial mediations, as well as their transitioning over time from one state to another. Then, the assumptions of the gesture operational model are translated into a simultaneous equation system for each body entity through state-space modeling. The coefficients of the equation are computed using the maximum likelihood estimation method. The simulation of the model generates a confidence-bounding box for every entity that describes the tolerance of its spatial variance over time. The contribution of our approach is demonstrated for both recognizing gestures and forecasting human motion trajectories. In recognition, it is combined with continuous hidden Markov models to boost the recognition accuracy when the likelihoods are not confident. In forecasting, a motion trajectory can be estimated by taking as minimum input two observations only. The performance of the algorithm has been evaluated using four industrial datasets that contain gestures and actions from a TV assembly line: the glassblowing industry, the gestural commands to automated guided vehicles as well as the human–robot collaboration in the automotive assembly lines. The hybrid approach State-Space and HMMs outperforms standard continuous HMMs and a 3DCNN-based end-to-end deep architecture.

Conduit bursts or leakages present an ongoing problem for hydraulic fluid transport grids, such as oil or water conduit networks. Better monitoring allows for easier identification of burst sites and faster response strategies but heavily relies on sufficient insight in the network’s dynamics, obtained from real-time flow and pressure sensor data. This paper presents a linearized state-space model of hydraulic networks suited for optimal sensor placement. Observability Gramians are used to identify the optimal sensor configuration by maximizing the output energy of network states. This approach does not rely on model simulation of hydraulic burst scenarios or on burst sensitivity matrices, but, instead, it determines optimal sensor placement solely from the model structure, taking into account the pressure dynamics and hydraulics of the network. For a good understanding of the method, it is illustrated by two small water distribution networks. The results show that the best sensor locations for these networks can be accurately determined and explained. A third example is added to demonstrate our method to a more realistic case.

In this article, a set of autonomous ac microgrids, interconnected by back-to-back converters, is taken into account, where they are supplied fully using voltage source converter-based distributed energy resources. A comprehensive and generalized small-signal model of the interconnected autonomous microgrids as a large-scale system is proposed using the interconnection method. The modeling is based on detailed module models to show the impact of each module on the dynamic modes, especially the dominant critical modes. It is generalized and scalable due to separate modeling of modules as well as using unlimited and expandable interconnecting. The proposed interconnection method deals with all electrical and control connections between individual modules including feedback, feed-forward, augmentation, and the order of module inputs and outputs. The model is validated employing Prony analysis method and using output results of an OPAL-RT real-time simulator. Using the proposed modeling method, the small-signal stability analysis and controller design can be realized simply for interconnected microgrids with any number of microgrids and different structures. Typically, for two interconnected microgrids, all dynamic modes and participant state variables in different frequency ranges are identified using the eigenvalue analysis and participation matrix in MATLAB. [ABSTRACT FROM AUTHOR]

This study analyses the dynamic behaviour of a doubly fed induction generator (DFIG)‐based wind integrated power system (WIPS) resulting from a major disturbance. The effects of transient disturbance on WIPS are examined without and with a controller in terms of performance and stability of the system. To enhance the performance of WIPS after a sudden disturbance, an optimally designed linear quadratic regulator (LQR) controller is applied to the system. The wind energy system is described in state‐space representation, whose states and outputs are taken as feedback to the controller for improving their dynamic response. An artificial bee colony (ABC)‐based swarm optimisation technique is used to evaluate the optimal weighting matrices of the LQR controller in parallel with minimising the performance index and dynamic response characteristics of the system. The effectiveness of the proposed ABC–LQR controller in WIPS is verified by comparing their simulation and numerical results with standard proportional–integral and LQR controllers. It indicates that the proposed controller provides better enhancement of dynamic response as compared with other controllers in terms of performance index and dynamic response characteristics. Moreover, the robustness and stability of various system configurations are tested by the eigenvalue analysis. [ABSTRACT FROM AUTHOR]

For a given system with time-invariant affine uncertainties, ranging in a unit hypercube or, equivalently, in a hyper-rectangle, new LMI sufficient conditions for the verification of a given simultaneous static-output-feedback for hypercube nodes, being robust static-output-feedback for the whole system, are proved. The conditions generalise previous results in the sense that we do not assume that the state-to-measurement or the input-to-state matrix is constant. Based on the LMI conditions, a randomised algorithm is suggested. The effectiveness of the method is reinforced through experiments on real-life systems. [ABSTRACT FROM AUTHOR]

In this paper, we study product convolutional codes described by state-space representations. In particular, we investigate how to derive state-space representations of the product code from the horizontal and vertical convolutional codes. We present a systematic procedure to build such representation with minimal dimension, i.e., reachable and observable.

In industry, ergonomists apply heuristic methods to determine workers’ exposure to ergonomic risks; however, current methods are limited to evaluating postures or measuring the duration and frequency of professional tasks. The work described here aims to deepen ergonomic analysis by using joint angles computed from inertial sensors to model the dynamics of professional movements and the collaboration between joints. This work is based on the hypothesis that with these models, it is possible to forecast workers’ posture and identify the joints contributing to the motion, which can later be used for ergonomic risk prevention. The modeling was based on the Gesture Operational Model, which uses autoregressive models to learn the dynamics of the joints by assuming associations between them. Euler angles were used for training to avoid forecasting errors such as bone stretching and invalid skeleton configurations, which commonly occur with models trained with joint positions. The statistical significance of the assumptions of each model was computed to determine the joints most involved in the movements. The forecasting performance of the models was evaluated, and the selection of joints was validated, by achieving a high gesture recognition performance. Finally, a sensitivity analysis was conducted to investigate the response of the system to disturbances and their effect on the posture.

This paper discusses a design method for controlling a single-input single-output linear time-invariant sampled-data multi-rate control system, where the sampling interval of a plant output is longer than the holding interval of a control input. In such a sampled-data control system, the control input can be changed between the sampling instants. Hence, even if the sampled output converges to the reference input, the intersample output may oscillate. Such an intersample oscillation is eliminated when the control input is constant. In a conventional method, a control law is extended using an additional signal which is independent of the reference response in the discrete time, and the additional signal is designed so that the control input is constant in the steady state. The conventional method is designed based on the transfer function model, on the other hand, the proposed method is designed using the state-space model. Furthermore, a new design method of the additional input is proposed using the input redundancy which is defined by strongly input redundant or weakly input redundant. Finally, the effectiveness of the proposed method is demonstrated through numerical examples.

An improved model to express the unsteady aerodynamic characteristics at high angles of attack is presented in this paper. The proposed aerodynamic model is expressed on the basis of a progressive state-space representation and Taylor's series expansion. The state-space expression is a first-order differential equation in which the power item of the angular rate of attack is introduced. The unsteady aerodynamic coefficients are described by Taylor's series expansion in terms of input variables. The approach of minimum mean square error criterion is utilized to identify the unknown parameters of the proposed model by nonlinear least square method from the tunnel data. The given modeling method is experimentally demonstrated by the wind tunnel measurements of NACA 0015 airfoil with constant rate to high angles of attack, F18 aircraft with constant pitch rate ramp motion, and F18 HARV (high alpha research vehicle) configuration with large-amplitude harmonic oscillatory. The results show that it is possible to analyze more complex unsteady aerodynamic problems for an aircraft within the framework of the proposed aerodynamic model and the represented model is directly amenable to the simulation and control system design. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel approach to build real-valued baseband models of linear, time-invariant, passive photonic devices, circuits, and systems, which allows modeling of photonic wavelength filter circuits with their full dispersion effects in an accurate way. The proposed technique starts from the scattering parameters of the photonic systems under study and leverages on the modeling power of the vector-fitting algorithm, thereby leading to both complex- and real-valued baseband state-space models. The modeling procedure is robust and applicable to general linear passive photonic devices and circuits, and the physical properties of the resulting models for the time-domain simulation, such as stability and passivity, can be properly guaranteed. The built models are systems of first-order ordinary differential equations (ODEs), which can be efficiently simulated in a variety of ODE solvers at baseband frequencies rather than in the optical frequency range. We demonstrate the applicability and accuracy of the proposed method on two examples of photonic filter circuits. [ABSTRACT FROM AUTHOR]