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"State-space methods"
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Output controllability of impulsive Boolean control networks based on hybrid‐index model
In biological systems, impulses are often used to model mutations in gene expression. In order to describe the instantaneity of the impulse, this paper employs a hybrid‐index model of impulsive Boolean networks with state‐triggered impulses. Based on this model, the time‐domain output controllability is investigated. Using the quotient mapping method, the hybrid‐domain solutions of this model are mapped to the time‐domain solutions, mathematically. Then a necessary and sufficient condition for output controllability in the time domain is presented. Finally, an example is given to demonstrate the correctness and effectiveness of the obtained results.
Journal Article
Quickest attack detection in smart grid based on sequential Monte Carlo filtering
Quick and accurate detection of cyber-attacks is key to the normal operation of the smart grid system. In this study, joint state estimation and sequential attack detection method for a given bus with grid frequency drift is proposed that utilises the commonly monitored output voltage. In particular, based on a non-linear state-space model derived from the three-phase sinusoidal voltage equations, the authors employ the sequential Monte Carlo (SMC) filtering to estimate the system state. The output of the SMC filter is fed into a cumulative sum control chart test to detect the attack in the fastest way. Moreover, an adaptive sampling strategy is proposed to reduce the rate of taking measurements and communicating with the controller. Extensive simulation results demonstrate that the proposed method achieves high adaptivity and efficient detection of various types of attacks in power systems.
Journal Article
Analysis of physiological signals using state space correlation entropy
In this letter, the authors propose a new entropy measure for analysis of time series. This measure is termed as the state space correlation entropy (SSCE). The state space reconstruction is used to evaluate the embedding vectors of a time series. The SSCE is computed from the probability of the correlations of the embedding vectors. The performance of SSCE measure is evaluated using both synthetic and real valued signals. The experimental results reveal that, the proposed SSCE measure along with SVM classifier have sensitivity value of 91.60%, which is higher than the performance of both sample entropy and permutation entropy features for detection of shockable ventricular arrhythmia.
Journal Article
Linear Modeling and Regulation Quality Analysis for Hydro-Turbine Governing System with an Open Tailrace Channel
On the basis of the state–space method (SSM), a novel linear mathematical model of the unsteady flow for the tailrace system with an open channel is proposed. This novel model is an elastic linearized model of water hammer. The validity of the model has been verified by several examples of numerical simulation, which are based on a finite difference technique. Then, the complete mathematical model for the hydro-turbine governing system of hydropower station with an open tailrace channel, which is used for simulating the transient process of the hydro-turbine governing system under load disturbance, is established by combining the models of hydro-turbine, generator, governor and open tailrace channel. Finally, according to the complete model, the regulation quality for hydro-turbine governing system with an open tailrace channel under load disturbance is studied, and the effects of open tailrace channel and tailrace surge tank on regulation quality are analyzed. The results indicate that: The open tailrace channel has a strong influence on the regulation quality by observing the water level fluctuations in tailrace surge tank. The surge shows a piecewise periodical change along with the variation in the length of an open channel. The open tailrace channel can be used to improve the regulation quality of hydro-turbine governing system.
Journal Article
Forecasting of commodities prices using a multi-factor PDE model and Kalman filtering
This study proposes a method for forecasting commodities prices using Schwartz partial differential equation (PDE) and Kalman filtering. The method is applicable to both the single-factor and the multi-factor Schwartz PDE. Using semi-discretisation and the finite differences method, the Schwartz PDE is transformed into an equivalent state-space description. This latter representation is finally written in a linear matrix form in which the Kalman filter's recursion is applicable. By redesigning the Kalman filter as a m-step ahead predictor it becomes possible to obtain accurate estimates of the future commodities’ price. The prediction scheme analysed in this study can contribute to maximising profits in commodities trading, including also the trading of electric power.
Journal Article
Frequency response analysis for bidirectional series-resonant DC/DC converter in discontinuous mode
This study analyses the frequency response of a bidirectional series-resonant DC/DC converter (SRC) working in a discontinuous mode (DCM). The converter can reach a voltage conversion ratio higher or lower than one, depending on whether the operation mode is step-up or step-down. The analysis is based on a novel mixed technique using both the state-space average method and the Fourier method to obtain a state-space averaged model of the converter. The study presents the model for the two operation modes. It also presents the frequency response of the output voltage as a function of the input voltage and as a function of the off-time, which is the control parameter of the converter. The results of those transfer functions are compared with measurements in a 2000 W prototype. The model provides enough information to properly control the SRC in DCM.
Journal Article
The Response of Nanobeams with Temperature-Dependent Properties Using State-Space Method via Modified Couple Stress Theory
At present, with the development in nanotechnology, nanostructures with temperature-dependent properties have been used in nano-electromechanical systems (NEMS). Thus, introducing an accurate mathematical model of nanobeams with temperature-dependent properties is a major and important topic for the design of NEMS. This paper aims to discuss nonlocal nanobeams analysis depending on the theories of Euler–Bernoulli and modified couple-stress (MCS). It also is assumed that the thermal conductivity of the nanobeam is dependent on the temperature. Physical fields of the nanobeam are obtained utilizing Laplace transform and state-space techniques. The effects of the size and nonlocal parameters, variability of thermal conductivity and couple stress on various distributions are presented graphically and studied in detail. Numerical results are presented as application scales and the design of nanoparticles, nanoscale oscillators, atomic force microscopes, and nanogenerators, in which nanoparticles as nanobeams act as essential and basic elements.
Journal Article
Coloured Petri Nets and CPN Tools for modelling and validation of concurrent systems
Coloured Petri Nets (CPNs) is a language for the modelling and validation of systems in which concurrency, communication, and synchronisation play a major role. Coloured Petri Nets is a discrete-event modelling language combining Petri nets with the functional programming language Standard ML. Petri nets provide the foundation of the graphical notation and the basic primitives for modelling concurrency, communication, and synchronisation. Standard ML provides the primitives for the definition of data types, describing data manipulation, and for creating compact and parameterisable models. A CPN model of a system is an executable model representing the states of the system and the events (transitions) that can cause the system to change state. The CPN language makes it possible to organise a model as a set of modules, and it includes a time concept for representing the time taken to execute events in the modelled system. CPN Tools is an industrial-strength computer tool for constructing and analysing CPN models. Using CPN Tools, it is possible to investigate the behaviour of the modelled system using simulation, to verify properties by means of state space methods and model checking, and to conduct simulation-based performance analysis. User interaction with CPN Tools is based on direct manipulation of the graphical representation of the CPN model using interaction techniques, such as tool palettes and marking menus. A license for CPN Tools can be obtained free of charge, also for commercial use. [PUBLICATION ABSTRACT]
Journal Article
Approximation-based adaptive control of uncertain non-linear pure-feedback systems with full state constraints
This study proposes an adaptive approximation-based control approach for non-linear pure-feedback systems in the presence of full state constraints. Completely non-affine non-linear functions are considered and assumed to be unknown. The dynamic surface design based on integral barrier Lyapunov functionals is provided to achieve both the desired tracking performance and the constraints satisfaction, in consideration of the full-state-constrained non-affine non-linearities. In this design procedure, simple sufficient conditions for choosing control gains, which can be checked off-line, are established to guarantee the feasibility of the controller. The function approximation technique is employed to estimate unknown non-linearities induced from the controller design procedure where the adaptive laws using the projection operator are designed to ensure the boundedness of the function approximators in the feasibility conditions. It is shown that all the signals in the closed-loop system are uniformly ultimately bounded and the tracking error converges to an adjustable neighbourhood of the origin while all state variables always remain in the constrained state space.
Journal Article