Combination Of State Variables Research Articles

Using Different ML Algorithms and Hyperparameter Optimization to Predict Heat Meters’ Failures

The need to increase the energy efficiency of buildings, as well as the use of local renewable heat sources has caused heat meters to be used not only to calculate the consumed energy, but also for the active management of central heating systems. Increasing the reading frequency and the use of measurement data to control the heating system expands the requirements for the reliability of heat meters. The aim of the research is to analyze a large set of meters in the real network and predict their faults to avoid inaccurate readings, incorrect billing, heating system disruption, and unnecessary maintenance. The reliability analysis of heat meters, based on historical data collected over several years, shows some regularities, which cannot be easily described by physics-based models. The failure rate is almost constant and does depend on the past, but is a non-linear combination of state variables. To predict meters’ failures in the next billing period, three independent machine learning models are implemented and compared with selected metrics, because even the high performance of a single model (87% true positive for neural network) may be insufficient to make a maintenance decision. Additionally, performing hyperparameter optimization boosts the models’ performance by a few percent. Finally, three improved models are used to build an ensemble classifier, which outperforms the individual models. The proposed procedure ensures the high efficiency of fault detection (>95%), while maintaining overfitting at the minimum level. The methodology is universal and can be utilized to study the reliability and predict faults of other types of meters and different objects with the constant failure rate.

Synthesis of a Multifunctional Tracking System in Conditions of Uncertainty

Class of affine nonlinear single-input single-output systems, where the relative degree of the equivalent form of the input-output is invariant to the presence of external, unmatched disturbances, is formalized. Methods of synthesis of a multifunctional tracking system in the conditions of parametric uncertainty of the control plant model and incomplete measurements are designed for this class of systems. The original method of synthesis of a low dimension observer for estimating mixed variables (these are combinations of state variables, external influences and their derivatives) by measuring only tracking error is designed for information support of discontinuous control. In this observer, using the linear corrective effects with saturation, the method of separating the movements of observation errors is realized. As an illustration of the developed method, an electromechanical control object is considered-an inverted pendulum controlled by a DC motor. The simulation results for the worst case of varying parameters are given.

A Mathematical Description of the Dynamics of Power Systems Using the Method of State Variables

The possibility of using the method of state variables for mathematical description of the dynamics of an autonomous power supply system is considered. The main advantages of using this approach are noted. The specifics of object construction presented in the form of discrete circuits and elements is taken into account. A system of state equations for the studied element of the system is presented having the form of a linear combination of state variables, input variables, and parameters of the element. The issue of controllability and observability of calculations is taken into account. An iterative calculation algorithm of transient voltage deviations is developed.

Optimization and Validation of Efficient Models for Predicting Polythiophene Self-Assembly.

We develop an optimized force-field for poly(3-hexylthiophene) (P3HT) and demonstrate its utility for predicting thermodynamic self-assembly. In particular, we consider short oligomer chains, model electrostatics and solvent implicitly, and coarsely model solvent evaporation. We quantify the performance of our model to determine what the optimal system sizes are for exploring self-assembly at combinations of state variables. We perform molecular dynamics simulations to predict the self-assembly of P3HT at ∼350 combinations of temperature and solvent quality. Our structural calculations predict that the highest degrees of order are obtained with good solvents just below the melting temperature. We find our model produces the most accurate structural predictions to date, as measured by agreement with grazing incident X-ray scattering experiments.

Particle swarm optimization for problems with variable number of dimensions

ABSTRACTSome real-life optimization problems, apart from dependence on the combination of state variables, also show dependence on the complexity of the model describing the problem. Changing model complexity implies changing the number of decision space dimensions.A new method called Particle Swarm Optimization for Variable Number of Dimensions is developed here. The well-known particle swarm optimization procedure is modified to handle spaces with a variable number of dimensions within a single run. Some well-known benchmark problems are modified to depend on the number of dimensions. Novel performance metrics are defined in the article to evaluate convergence properties of the method. Some recommendations for setting the optimization are made according to results of the method on the proposed benchmark test suite. The method is compared with conventional swarm strategies able to solve problems with variable number of dimensions.

Design of a DSP-Based PD-like Fuzzy Controller for Buck DC–DC Converters

This paper develops the DSP-based (digital signal processor) proportional-derivative-like (PD-like) fuzzy mechanism for a buck DC–DC converters. The computation complexity is one drawback for the fuzzy controller to be realized in real-time systems. To reduce the computational complexity of fuzzy mechanisms for the real-time DSP implementation, the PD-like fuzzy controller is proposed in which the input of the fuzzy controller is designed to be the linear combination of state variables. The stability of the buck DC–DC converters with PD-like fuzzy controller is discussed. Compared to a PD controller, experimental results indicate that the PD-like fuzzy controller achieves fast transient response and is robust to variations.

CHAOS CONTROL AND SYNCHRONIZATION USING SYNERGETIC CONTROLLER WITH FRACTIONAL AND LINEAR EXTENDED MANIFOLD

In this manuscript, for the first time, a fractional-order manifold in a synergetic approach using a fractional order controller is introduced. Furtheremore, in the synergetic theory a macro variable is expended into a linear combination of state variables. An aim is to increase the convergence rate as well as time response of the whole closed loop system. Quality of the proposed controller is investigated to control and synchronize a nonlinear chaotic Coullet system in comparison with an integer order manifold synergetic controller. The stability of the proposed controller is proven using the Lyapunov method. In this regard stabilizing control effort is yielded. Simulation result confirm convergence of states towards zero. This is achieved through a control effort with fewer oscillations and lower amplitude of signls which confirm feasibility of the control effort in practice.KEYWORDS:Â synergetic control theory; fractional order system; synchronization; nonlinear chaotic Coullet system; chaos control

Analytical synthesis of functional observers

A technique for constructing the observers to evaluate a linear combination of state variables is considered. We propose an algorithm for analytical synthesis of the minimum-order functional observers based on the nondegenerate transformation of the object model in the state space using the matrix canonization technology. The applicability limits of the technique and the conditions of problem solvability are defined.

Some Variational Principles for Coupled Thermoelasticity

The nonlinear thermoelasticity of type II proposed by Green and Naghdi is considered. The thermoelastic structural model is formulated in a quasistatic range, and the related thermoelastic variational formulation in the complete set of state variables is recovered. Hence a consistent framework to derive all the variational formulations with different combinations of the state variables is provided, and a family of mixed variational formulations, with different combinations of state variables, is provided starting from the general variational formulation. A uniqueness condition is provided on the basis of a suitable variational formulation.

Novel variational formulations for nonlocal plasticity

A nonlocal structural model of softening plasticity is considered in the framework of the internal variable theories of inelastic behaviours of associative type. The finite-step nonlocal structural problem in a geometrically linear range is formulated according to a backward difference scheme for time integration of the flow rule. The related finite-step variational formulation in the complete set of local and nonlocal state variables is recovered. A family of mixed nonlocal variational formulations, with different combinations of state variables, is provided starting from the general variational formulation. The specialization of a mixed variational formulation to existing nonlocal models of softening plasticity, assuming both linear and nonlinear constitutive behaviour, is provided to show the effectiveness of the theory.

Variational formulations, convergence and stability properties in nonlocal elastoplasticity

A thermodynamically consistent formulation of nonlocal plasticity in the framework of the internal variable theories of inelastic behaviors of associative type is presented. A family of mixed variational formulations, with different combinations of state variables, is provided starting from the finite-step nonlocal elastoplastic structural problem. It is shown that a suitable minimum principles provides a rational basis to exploit the iterative elastic predictor-plastic corrector algorithm in terms of the dissipation functional. A sufficient condition is proved for the convergence of the iterative elastic predictor-plastic corrector algorithm based on a suitable choice of the elastic operator in the prediction phase and a necessary and sufficient condition for the existence of a unique solution (if any) of the nonlocal problem at hand is then provided. The nonlinear stability analysis of the nonlocal problem is carried out following the concept of nonexpansivity proposed in local plasticity.

Consistency tests in guaranteed simulation of nonlinear uncertain systems with application to an activated sludge process

In this paper, interval arithmetic simulation techniques are presented to determine guaranteed enclosures of the state variables of both continuous and discrete-time systems with uncertain but bounded parameters. In nonlinear uncertain systems axis-parallel interval boxes are mapped to complexly shaped regions in the state space that represent sets of possible combinations of state variables. The approximation of each region by a single interval box causes an accumulating overestimation from time-step to time-step, usually called the wrapping effect. The algorithm presented in this paper minimizes the wrapping effect by applying consistency techniques based on interval Newton methods. Subintervals that do not belong to the exact solution at a given time can be eliminated in order to give a tighter but still conservative approximation of the exact solution. Additionally, efficient splitting and merging strategies are employed to limit the number of subintervals. The proposed algorithm is applied to the simulation of an activated sludge process in biological wastewater treatment.

CONSISTENCY TECHNIQUES FOR SIMULATION OF WASTEWATER TREATMENT PROCESSES WITH UNCERTAINTIES

In this paper, interval simulation methods are presented to determine guaranteed enclosures of state variables of an activated sludge process in biological wastewater treatment. This process is characterized by nonlinearities and uncertain but bounded parameters. In uncertain systems an axis-parallel interval box is mapped to a complexly shaped region in the state space that represents sets of possible combinations of state variables. The approximation of this complex region by a single interval box causes accumulation of overestimation over simulation time. The algorithm presented in this paper minimizes this so called wrapping effect by applying consistency techniques, to avoid safety-critical states.

A Method to Interface Linear Subsystem Model to Main System for Stability Simulation of Large Scale Power System

A method to interface linear subsystem model to main power system is shown. First a local reference angle of subsystem is extracted as a linear combination of state variables of the subsystem model. Second the subsystem model is transformed into a quasi-linear form having phasor quantities as its input/output variables. The quasi-linear form can be interfaced to main system within I = YV-type network solution.

CHAOTIC PHASE SHIFT KEYING IN DELAYED CHAOTIC ANTICONTROL SYSTEMS

Based on the delayed feedback chaotic anticontrol systems, a new chaotic phase shift keying (CPSK) scheme is proposed for secure communications in this paper. The chaotic transmitter is a linear system with nonlinear delayed feedback in which a trigonometric function cos(·) is used. Such system can exhibit rich chaotic behavior with the choice of appropriate parameters. For an M-ary communication system where M=2n, each of these M possible symbols (n-bits) is firstly mapped to 2(m-1)π/M (with m=1, 2, …, M) which is used as the phase argument for the cos(·) function in the nonlinear feedback. Two different kinds of signals can be transmitted. In the first one, an appropriate linear combination of state variables is chosen as the transmitting signal based on the observer theory. In another one, a nonlinear component in the transmitter state equation is chosen. In both schemes, only a scalar chaotic signal is transmitted through the channel. Demodulation is based on the synchronization of the transmitter and the receiver, and different decoded phases correspond to different information signals.

Uptake and Processing of Glycoproteins by Hepatic Sinusoidal Cells — Identification of a Mathematical Model

Abstract Glycoproteins terminated with mannose residues are cleared rapidly from plasma by a process of binding to surface receptors on hepatic sinusoidal cells with subsequent internalisation of the receptor ligand complex. The glycoprotein ligand is delivered to the lysosome where it is catabolised. A compartmental model of the uptake and processing system is presented. A typical tracer experiment on an animal system consists of an injection into blood of radioactively-labelled glycoprotein followed by measurements of radioactivity in various sites at sequential times. An identifiability analysis of the model with such an input-output design is performed. Interesting features of this are the presence of time delays and multiple outputs (including one which is an additive combination of state variables). Results of fitting the model to data from a number of. ligands are presented and their physiological significance discussed.

Multi-Parameter Optimization of Damped Linear Continuous Systems

A method is presented for obtaining and optimizing the frequency response of one-dimensional damped linear continuous systems. The systems considered are assumed to contain unknown constant parameters in the boundary conditions and equations of motion which the designer can vary to obtain a minimum resonant response in some selected frequency interval. The unknown parameters need not be strictly dissipative nor unconstrained. No analytic solutions, either exact or approximate, are required for the system response and only initial value numerical integrations of the state and adjoint differential equations are required to obtain the optimal parameter set. The combinations of state variables comprising the response and the response locations are arbitrary.

A Dual Mode Excitation Control of Synchronous Machine for Suppressing its Hunting

To suppress the hunting of synchronous machine caused by stepwise load change, a dual mode field excitation control was investigated for conventional (one-axis) machine and 2-axis machine. For one-axis machine, a dual mode is applied successively, the first one being a bang-bang suboptimal control mode decided by use of energy function instead of Pontryagin's switching function, this mode is applicable to dynamic equation described in nonlinear form. The second one is a linear feedback control mode composed of a linear combination of state variables, and it will be adopted to the range near the steady state operating point where the equation will be linearized. For 2-axis machine at the instant of load change the original excitation introduced by mixing these two controls is efficiently applied. From the results of the investigation it is recognized that the employment of 2-axis synchronous machine is a potential means for the improvement of system stability.

Multiparameter Identification in Linear Continuous Vibratory Systems

A method is presented for identifying unknown parameters in linear continuous vibratory systems from frequency response data. The method is applicable to systems for which the steady-state equations of motion are reducible to a finite set of ordinary differential equations. After assuming a system model of partial differential equations and boundary conditions containing unknown parameters, initial value numerical integrations are performed to identify the unknown parameters. No analytic solution to the system model is required. For the identification of conservative or near conservative systems, only resonant frequency data are used and, for the identification of nonconservative systems, the data may consist of any state variable or combination of state variables at any arbitrary location within the system. The use of multiple response transducers is not required.