Set Of Linear Differential Equations Research Articles

Adaptively Learned Modeling for a Digital Twin of Hydropower Turbines with Application to a Pilot Testing System

In the development of a digital twin (DT) for hydropower turbines, dynamic modeling of the system (e.g., penstock, turbine, speed control) is crucial, along with all the necessary data interface, virtualization, and dashboard designs. Since the DT must mimic the actual dynamics of the hydropower turbine accurately, adaptive learning is required to train these dynamic models online so that the models in the DT can effectively follow the representation of the actual hydropower turbine dynamics accurately and reliably. This study presents an adaptive learning method for obtaining the hydropower turbine models for DT development of hydropower systems using the recursive least squares algorithm. To simplify the formulation, the hydropower turbine under consideration was assumed to operate near a fixed operating point, where the system dynamics can be well represented by a set of linear differential equations with constant parameters. In this context, the well-known six-coefficient model for the Francis turbine was formulated as the starting point to obtain input and output models for the turbine. Then, an adaptive learning mechanism was developed to learn model parameters using real-time data from a hydropower turbine testing system. This led to semi-physical modeling, in which first principles and data-driven modeling are integrated to produce dynamic models for DT development. Applications to a pilot system at the Norwegian University of Science and Technology (NTNU) were made, and the models learned adaptively using the data collected from the university’s pilot system. Desired modeling and validation results were obtained.

The impossible challenge of estimating non-existent moments of the Chemical Master Equation.

The Chemical Master Equation (CME) is a set of linear differential equations that describes the evolution of the probability distribution on all possible configurations of a (bio-)chemical reaction system. Since the number of configurations and therefore the dimension of the CME rapidly increases with the number of molecules, its applicability is restricted to small systems. A widely applied remedy for this challenge is moment-based approaches which consider the evolution of the first few moments of the distribution as summary statistics for the complete distribution. Here, we investigate the performance of two moment-estimation methods for reaction systems whose equilibrium distributions encounter fat-tailedness and do not possess statistical moments. We show that estimation via stochastic simulation algorithm (SSA) trajectories lose consistency over time and estimated moment values span a wide range of values even for large sample sizes. In comparison, the method of moments returns smooth moment estimates but is not able to indicate the non-existence of the allegedly predicted moments. We furthermore analyze the negative effect of a CME solution's fat-tailedness on SSA run times and explain inherent difficulties. While moment-estimation techniques are a commonly applied tool in the simulation of (bio-)chemical reaction networks, we conclude that they should be used with care, as neither the system definition nor the moment-estimation techniques themselves reliably indicate the potential fat-tailedness of the CME's solution.

Linearizing the BPS equations with vector and tensor multiplets

We analyse the BPS equations of mathcal{N} = (1, 0) supergravity theory in six dimensions coupled to a vector and tensor multiplet. We show how these BPS equations can be reduced to a set of linear differential equations. This system is triangular in that each layer of equations, while linear, is quadratically sourced by the solutions of the previous layers. We examine several explicit examples and discuss the construction of new families of microstate geometries. We expect that the result presented here will open up new branches of superstrata in which the momentum is encoded in a new class of charge carriers.

Generalized Model Predictive Pulse Pattern Control Based on Small-Signal Modeling—Part 1: Algorithm

A model predictive controller based on optimized pulse patterns is proposed that is suitable for higher-order linear systems, such as converters with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$LC$</tex-math></inline-formula> filters. The controller manipulates the switching times of an optimized pulse pattern. The switching time modifications are approximated by the strengths of impulses, which are based on a small-signal linearization around the nominal switching instants. With these, the evolution of the state variables over the prediction horizon can be described by a set of linear differential equations. An objective function penalizes the predicted tracking error of the controlled variables, such as the converter currents, filter capacitor voltages, and grid currents, over a prediction horizon. Thanks to the use of impulse strengths, the underlying optimization problem is a convex quadratic program, which can be solved in real time to determine the switching time modifications of the pulse pattern to be applied by the controller.

Dynamic Modeling of Bucket-Soil Interactions Using Koopman-DFL Lifting Linearization for Model Predictive Contouring Control of Autonomous Excavators

A lifting-linearization method based on the Koopman operator and Dual Faceted Linearization is applied to the control of a robotic excavator. In excavation, a bucket interacts with the surrounding soil in a highly nonlinear and complex manner. Here, we propose to represent the nonlinear bucket-soil dynamics with a set of linear state equations in a higher-dimensional space. The space of independent state variables is augmented by adding variables associated with nonlinear elements involved in the bucket-soil dynamics. These include nonlinear resistive forces and moment acting on the bucket from the soil, and the effective inertia of the bucket that varies as the soil is captured into the bucket. Variables associated with these nonlinear resistive and inertia elements are treated as additional state variables, and their time evolution is represented as another set of linear differential equations. The lifted linear dynamic model is then applied to Model Predictive Contouring Control, where a cost functional is minimized as a convex optimization problem thanks to the linear dynamics in the lifted space. The lifted linear model is tuned based on a data-driven method by using a soil dynamics simulator. Simulation experiments on homogeneous soil verify the effectiveness of the proposed lifting linearization compared to its counterpart.

Bending deflection and stress analyses in a thin functionally graded material skew plate with different boundary conditions on the Winkler–Pasternak elastic foundation and under combined in-plane and uniform lateral loads using the extended Kantorovich method

In this study, bending deflection and stress analyses have been conducted for a thin skew plate made of functionally graded material (FGM) with different boundary conditions on the Winkler–Pasternak elastic foundation and under combined loads including uniform transverse load, normal and shear in-plane forces, and planar body forces. The Cartesian partial differential equation governing the bending deflection of the skew plate has been converted into a partial differential equation in oblique coordinates using the conversion relations. Then, by employing the variational principle and residual weighted Galerkin method and using the Extended Kantorovich Method (EKM), the equation has been converted to a set of linear differential equations in terms of two functions in the longitudinal and transverse directions of the oblique plate, and afterward, the equation has been solved using the iterative solution method. Different boundary conditions in a combined form of simply and clamped supports have been investigated and their effects on bending deflection and generated in-plane normal and shear stresses are discussed.

INCEPTION OF GREEN FUNCTION FOR THE THIRD-ORDER LINEAR DIFFERENTIAL EQUATION THAT IS INCONSISTENT WITH THE BOUNDARY PROBLEM CONDITIONS

Regarding the importance of teaching linear differential equations, it should be noted that every physical and technical phenomenon, when expressed in mathematical sciences, is a differential equation. Differential equations are an essential part of contemporary comparative mathematics that covers all disciplines of physics (heat, mechanics, atoms, electricity, magnetism, light and wave), many economic topics, engineering fields, natural issues, population growth and today’s technical issues. Used cases. In this paper, the theory of third-order heterogeneous linear differential equations with boundary problems and transforming coefficients into multiple functions p(x) we will consider. In mathematics, in the field of differential equations, a boundary problem is called a differential equation with a set of additional constraints called boundary problem conditions. A solution to a boundary problem is a solution to the differential equation that also satisfies the boundary conditions. Boundary problem problems are similar to initial value problems. A boundary problem with conditions defined at the boundaries is an independent variable in the equation, while a prime value problem has all the conditions specified in the same value of the independent variable (and that value is below the range, hence the term "initial value"). A limit value is a data value that corresponds to the minimum or maximum input, internal, or output value specified for a system or component. When the boundaries of boundary values in the solution of the equation to obtain constants D1, D2, D3 to lay down Failure to receive constants is called a boundary problem. We solve this problem by considering the conditions given for that true Green expression function. Every real function of the solution of a set of linear differential equations holds, and its boundary values depend on the distances. Key words: Green Function, Boundary Problem, Private Solution, Public Solution, Wronskian Determinant.

Exact Non-Markovian Evolution with Several Reservoirs

The model of a multi-level system interacting with several reservoirs is considered. The exact reduced density matrix evolution could be obtained for this model without Markov approximation. Namely, this evolution is fully defined by the finite set of linear differential equations. In this work the results which were obtained previously for only one Lorentz peak in the spectral density are generalized to the case of an arbitrary number of such peaks. The case of the Ohmic contribution in the spectral density is also taken here into account.

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Trombe wall solar chick brooder was developed for 150-200 birds’ capacity. System evaluation as well as stability and equilibrium analysis were carried out. A set of linear differential equations were formulated that described the dynamic modeling of Trombe wall solar chick brooder for optimal poultry production. The descriptive models were referred to as system control. The model was transformed into Jacobian matrix and solved for stability and equilibrium. Further tests for stability using Routh-Hurwitz criterion were conducted. The solved Jacobian matrix had negative eigenvalues and as such was locally stable. Routh-Hurwitz criterion affirmed that the system model was stable. It implied, the system supported brooding of 200 birds for the 28 days of brooding operation at temperature range of 25-39oC of the brooding room.

A Dynamic Knowledge Model of Project Time-Cost Analysis Based on Trend Modelling

This paper investigates the application of trend quantifiers of project time-cost analysis as a tool for decision-making support in the project management. Practical project management-related problems are solved under information shortages. It means that methods of statistical analysis cannot be easily used as they are based on the law of large numbers of observations. Numbers are information intensive quantifiers. The least information intensive quantifier is a trend; its values are increasing, constant, decreasing. If a derivative cannot be quantified by a trend, then nothing is known and therefore nothing can be analyzed/predicted. For this reason, the trend model M was created. The model M is based on a degraded set of differential equations or heuristics. A trend analysis of the model M is an evaluation of the relevant discrete set of solutions/scenarios S. A trend reconstruction is an evaluation of the model M if a (sub)set of scenarios S is given. The paper studies linear reconstruction, i.e. the model M is a set of linear differential equations. The trend reconstruction is partially reverse process to trend analysis. A case study has 7 variables (e.g. Project duration, Direct personnel costs, Indirect personal costs etc.) and the reconstructed set of linear differential equations has 7 equations. The set of 243 scenarios is obtained if this reconstructed set of trend linear equations is solved. Any future or past behavior of the model M can be described by a sequence of obtained scenarios.

Enhancing the Stability of the Switched Systems Using the Saltation Matrix

Controlling switched systems is a difficult task, even when dealing with piecewise linear systems (CPWLs), which consist of a set of linear differential equations and a set of switching conditions. This difficulty is largely due to the loss of linearity in the entire system, and it is necessary to solve differential and algebraic equations to determine the solution. In this paper, a new method to tune the parameters of the controllers applied to switched systems is derived using information from the saltation matrix, particularly its induced norm. First, the parameters are tuned using classical methods, and then, after analyzing the norm of the saltation matrix, a new set of parameters that guarantees the stability of the period-1 orbit is obtained. The method is validated using analytical solutions for two different systems (boost and boost-flyback power converters) and is also experimentally validated for the boost-flyback power converter.

Similarity Solution of (2+1)-Dimensional Calogero-Bogoyavlenskii-Schiff Equation Lax Pair

In this paper, we discussed and studied the solutions of the (2+1)-dimensional Calogero-Bogoyavlenskii-Schiff (CBS) equation. The Calogero-Bogoyavlenskii-Schiff equation describes the propagation of Riemann waves along the y-axis, with long wave propagating along the x-axis. Lax pair and Backlund transformation of the Calogero-Bogoyavlenskii-Schiff equation are derived by using the singular manifold method (SMM). The optimal Lie infinitesimals of the Lax pair are obtained. The detected Lie infinitesimals contain eight unknown functions. These functions are optimized through the commutator table. The eight unknown functions are evaluated through the solution of a set of linear differential equations, in which solutions lead to optimal Lie vectors. The CBS Lax pair is reduced by using the optimal Lie vectors to a system of ordinary differential equations (ODEs). The solitary wave solutions of Calogero-Bogoyavlenskii-Schiff equation Lax pair’s show soliton and kink waves. The obtained similarity solutions are plotted for different arbitrary functions and compared with previous analytical solutions. The comparison shows that we derive new solutions of Calogero-Bogoyavlenskii-Schiff equation by using the combination of two methods, which is different from the previous findings.

Periodic Trajectory Planning Beyond the Static Workspace for 6-DOF Cable-Suspended Parallel Robots

This paper proposes a dynamic trajectory planning technique for six-degree-of-freedom (6-DOF) cable-suspended parallel robots (CSPRs). First, a passive mechanical system that is equivalent to the CSPR is introduced to provide insight and facilitate the design of trajectories that can extend beyond the robot's static workspace. The tilt-and-torsion angle convention is used to develop the mathematical model and impose restrictions for the rotational component of the trajectories. The dynamic differential equations that govern the translational component of the trajectories are shown to become linear under some conditions. Natural frequencies of an equivalent passive linear system of constant-stiffness springs are, thus, obtained and the set of linear differential equations associated with this system is integrated to produce a general solution for natural, periodic trajectories. This approach is used to produce pure translation trajectories and more complex motion that includes changes in position and orientation. An experimental implementation is also presented using a 6-DOF prototype and a supplementary video file is included to demonstrate the results.

Mass Flow Dynamic Modeling and Residence Time Control of a Continuous Tubular Reactor for Biomass Pretreatment

This work presents a dynamic discrete model that describes the mass flow and residence time behavior in a pretreatment continuous tubular reactor using lignocellulosic biomass as feedstock. The model consists of a set of linear difference equations that accurately describe the output flow as a function of the operation conditions. Model parameters account for mechanical and rheological properties of different lignocellulosic biomass, as well as complex backflow phenomena commonly encountered in these reactors. The proposed dynamic model was experimentally validated for wheat straw and corn stover. Additionally, a control strategy was proposed for the residence time and was correctly validated through simulations.

The analysis of nonlinear systems in the frequency domain using Nonlinear Output Frequency Response Functions

The Nonlinear Output Frequency Response Functions (NOFRFs) are a concept which provides a new extension of the well-known concept of the Frequency Response Function (FRF) of linear systems to the nonlinear case. The present study introduces a NOFRFs based approach for the analysis of nonlinear systems in the frequency domain. It is well known that a nonlinear system can, under rather general conditions, be represented by a polynomial type Nonlinear Auto Regressive with eXogenous input (NARX) model. From the NARX model of a nonlinear system under study, the NOFRFs based approach for the frequency analysis of nonlinear systems involves solving a set of linear difference equations known as the Associated Linear Equations (ALEs) to determine the system nonlinear output responses and then the NOFRFs of the system up to an arbitrary order of nonlinearity of interests. The results enable a representation of the frequency domain characteristics of nonlinear systems by means of a series of Bode diagram like plots that can be used for nonlinear system frequency analyses for various purposes including, for example, condition monitoring, fault diagnosis, and nonlinear modal analysis.

Periodic event-triggered robust output feedback control for nonlinear uncertain systems with time-varying disturbance

This paper investigates the periodic event-triggered robust output feedback control problem for a class of nonlinear uncertain systems subject to time-varying disturbance. By means of the feedback domination approach and disturbance compensation technique, a new framework of periodic event-triggered robust control strategy is developed in the form of output feedback, which encompasses a discrete-time event-triggering transmission scheme that is only intermittently monitored at sampling instants and a discrete-time output feedback controller consisting of a set of linear difference equations. The proposed robust method may reduce the communication resource utilization as compared to the non-event triggering schemes while maintaining a desirable closed-loop system performance even in the presence of a general class of time-varying disturbance and nonlinear uncertainties. The closed-loop system under the proposed control scheme is actually modeled as a hybrid system, and it is shown that the global practical stability of the closed-loop hybrid system is guaranteed by selecting a sufficiently large scaling gain and a sufficiently small sampling period. Finally, the experimental results on a DC–DC buck power converter are presented to illustrate the effectiveness of the proposed control approaches.

Two methods of data reconciliation for pipeline networks

The paper compares the two most common methods of data reconciliation for pipeline networks. The first method, an unscented Kalman filter (UKF), uses a system of nonlinear implicit ordinary differential equations derived from the governing partial differential equations. The second method, a quadratic program, relies on a transformation of the system of nonlinear ordinary differential equations into a set of linear difference equations, with the linearization optimized for known pressure and flow ranges using a novel linearization technique. Both the UKF and the quadratic programming approaches for data reconciliation in gas pipeline networks are viable for networks of small to moderate size. Given the reduced number of simplifying assumptions and the resulting improved accuracy, the UKF may be preferable when the computational problem is tractable. The quadratic programming approach is faster, accepts lower fidelity models, and provides acceptable accuracy.

Solving Equations of Free Vibration for a Cylindrical Shell Rotating on Rollers by the Fourier Method

The small free vibrations of an infinite circular cylindrical shell rotating about its axis at a constant angular velocity are considered. The shell is supported on n absolutely rigid cylindrical rollers equispaced on its circle. The roller-supported shell is a model of an ore benefication centrifugal concentrator with a floating bed. The set of linear differential equations of vibrations is sought in the form of a truncated Fourier series containing N terms along the circumferential coordinate. A system of 2N–n linear homogeneous algebraic equations with 2N–n unknowns is derived for the approximate estimation of vibration frequencies and mode shapes. The frequencies ω k , k = 1, 2, …, 2N–n, are positive roots of the (2N–n)th-order algebraic equation D(ω2) = 0, where D is the determinant of this set. It is shown that the system of 2N–n equations is equivalent to several independent systems with a smaller number of unknowns. As a consequence, the (2N–n)th-order determinant D can be written as a product of lower-order determinants. In particular, the frequencies at N = n are the roots of algebraic equations of an order is lower than 2 and can be found in an explicit form. Some frequency estimation algorithms have been developed for the case of N > n. When N increases, the number of found frequencies also grows, and the frequencies determined at N = n are refined. However, in most cases, the vibration frequencies can not be found for N > n in an explicit form.

M intermediate accumulation analysis of bacteriorhodopsin reconstituted with three partial peptides

Reconstituted bacteriorhodopsin containing helices C-G, A, and B has unique thermal structural change and photoreaction. Time evolution of photo reaction of bacteriorhodopsin reconstituted with three partial peptides in glycerol mixed purple membrane at around 196 K under irradiation by red light was analyzed by a proposed model. The absorption change of 560 nm and 405 nm with irradiation times was analyzed for the purpose of determining reaction rates of photo reaction of reconstituted bacteriorhodopsin and its product M intermediate. In this study it is shown that reaction rates of conversion from bacteriorhodopsin reconstituted with three partial peptides to the M intermediate can be explained by a set of linear differential equations. Although the rate of accumulation of M intermediate is as forty times smaller than that of the native bacteriorhodopsin, the accumulation was achieved, in spite of absence of peptide bond between peptides.

Quantum transport under ac drive from the leads: A Redfield quantum master equation approach

Evaluating the time-dependent dynamics of driven open quantum systems is relevant for a theoretical description of many systems, including molecular junctions, quantum dots, cavity-QED experiments, cold atoms experiments and more. Here, we formulate a rigorous microscopic theory of an out-of-equilibrium open quantum system of non-interacting particles on a lattice weakly coupled to multiple baths and driven by periodically varying thermodynamic parameters like temperature and chemical potential of the bath. The particles can be either bosonic or fermionic and the lattice can be of any dimension and geometry. Based on Redfield quantum master equation under Born-Markov approximation, we derive a complete set of linear differential equations for equal time two-point correlation functions from which various physical observables, for example, current, can be calculated. Various interesting physical effects, such as resonance, can be directly read-off from the equations. Thus, our theory is quite general gives quite transparent and easy-to-calculate results. We validate our theory by comparing with exact numerical simulations. We apply our method to a generic open quantum system, namely a double-quantum dot coupled to leads with modulating chemical potentials. Two most important experimentally relevant insights from this are : (i) time-dependent measurements of current for symmetric oscillating voltages (with zero instantaneous voltage bias) can point to the degree of asymmetry in the system, and (ii) under certain conditions, time-dependent currents can exceed time-averaged currents by several orders of magnitude, and can therefore be detected even when the average current is below the measurement threshold.