8 research outputs found
Applied system and control sciences to social systems: Globalization age paradigms
No full textDimirovski, Georgi M. (Dogus Author) -- Conference full title: 17th World Congress, International Federation of Automatic Control, IFAC; Seoul; South Korea; 6 July 2008 through 11 July 2008.Modern advanced information technologies resulting from automation of control and decision processes along with ubiquitous communications have a multitude of impacts on development of national economies within the global economy. Thus all kinds of social systems, being essentially human centred systems, is a cross-, inter- and multi-disciplinary challenge to systems and control researchers. Social systems in modern civilization are reviewed from the systems science viewpoint and on the grounds of recent developments in control science and technology and with regard to globalization paradigm. The innovative systems approaches employing results from hybrid systems theory and dynamical networks are needed to address the now-old challenges of combined knowledge and technology transfer world wide for sustainable development that may remedy climate change and some of the negative socio economic aspects of globalization
An approximate actual network performance evaluation method
No full textDimirovski, Georgi M. (Dogus Author) -- Conference full title: UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2010; Liverpool; United Kingdom; 27 January 2010 through 29 January 2010Since early eighties, not too many happened in analytical methods of performance valuation for actual computer and communication networks. The methods of the classic queuing theory (the mean value analysis, the convolution method) adopt unrealistic assumptions. The stochastic queuing network methods are not adequate for investigation of actual networks. Therefore, the paper presents an approximate method based on many-year performance evaluation experience and some heuristics. The approach is based on the notion of the closed route within the computer network under investigation; the complete network being described as a collection of such closed routes. The method was successfully validated by simulation and measurements. Some more complex approximations, feasible due to development of the computing tools, are also proposed
Network traffic prediction using variational mode decomposition and multi-reservoirs echo state network
No full textDimirovski, Georgi M.The network traffic prediction is significant for the network load pre-warning and network congestion control. But the nonlinearity and nonstationarity of the actual network traffic data would reduce the prediction accuracy. In this paper, an optimized network traffic prediction method using variational mode decomposition (VMD) and multi-reservoirs echo state network (ESN) is presented. VMD method has advantages of reducing the signal transmission errors, removing the mode aliasing, and decreasing the degree of endpoint effects. However, VMD needs to preset the number of modes and the iterative factor, which are mainly decided by subjective experiences. In order to solve this, an optimized VMD method is proposed, and then a multi-reservoirs echo state network based prediction model is constructed. The main works are as follows: First, VMD is used to decompose the original network traffic data into several subsets; then, multiple subreservoirs are built after the phase space reconstruction (PSR) of each data subset; finally, the training set is used to train the prediction model. Moreover, in the training process, an improved fruit fly optimization algorithm (IFOA) is proposed combined with the levy's flight function and the cloud generator, which is used to optimize some model parameters. Compared with several prediction models, the proposed VMD-IFOA-ESN has better predictive stability and convergence performance. Three WIDE backbone network traffic data sets with different time intervals verify the effectiveness of the proposed prediction model
An aero-engine U-control method based on LPV model
No full text21st IFAC World Congress on Automatic Control - Meeting Societal Challenges -- JUL 11-17, 2020 -- ELECTR NETWORKDue to the harsh working environment and various constraints, the engine control unit (ECU) has very limited computational ability and few control methods can be applied to the real-word ECU maturely. Developing advanced control methods with good performance as well as low computational complexity is the research focus in the control area for the next generation aero-engines. The study reported in this paper combines the LPV model of aero-engine process with U-model control concept, which simplifies solving difficulty and avoids complexity of traditional LPV variable-gain controller. The results of Matlab-Simulink simulations demonstrate clearly this U-control method based on LPV model can be successfully used for designing quality aero-engine speed control system. It ensures a good control performance while guaranteeing stable operation in the proximity of chosen equilibrium steady-state thus demonstrating a considerable application potential. Copyright (C) 2020 The Authors.Int Federat Automat Control, Siemens, Bayer, ABB, MathWorks, Phoenix Contact, Ifak Technol, Berlin Heart, Elsevier, De Gruyter, Tele Medi Gmb
Key nodes mining for complex networks based on local gravity model
No full textIdentification of key nodes in complex networks can effectively speed up the spread of favourable information or prevent the spread of rumours and diseases. An algorithm based on local gravity model is proposed to mine the key spreaders in complex networks. The existing algorithms based on gravity model consider the shortest distance between nodes. However, nodes not only influence each other through the shortest path, which will lead the loss of information between nodes. Different from the existing gravity model, the distance considered in this model is not the shortest distance between nodes, but the reciprocal of the number of feasible paths between nodes. Conveniently, the model is called FPLGM (Local Gravity Model Based on Feasible Paths). Ten different networks are utilised to verify the effectiveness of FPLGM. Results show that the FPLGM performs best in comparison with the well-known state-of-the-art methods.National Natural Science Foundation of China [62276058, 61902057, 41774063]; Fundamental Research Funds for the Central Universities [N2217003]; Joint Fund of Science AMP; Technology Department of Liaoning Province; State Key Laboratory of Robotics, China [2020-KF-12-11]This work was supported by National Natural Science Foundation of China [grant number 62276058, 61902057, 41774063]; Fundamental Research Funds for the Central Universities [grant number N2217003]; Joint Fund of Science & Technology Department of Liaoning Province and State Key Laboratory of Robotics, China [grant number 2020-KF-12-11]
A Bisimulation-Based Foundation for Scale Reductions of Continuous-Time Markov Chains
No full textIn this paper, the scale reduction problem of continuous-time Markov chains (CT-MCs) and continuous-time controlled Markov chains (CT-CMCs) are disserted both from the bisimulation perspective. Based on the features of bisimulation, the reachability, macro-controllability, controllability, and stabilizability of CT-MCs and CT-CMCs, particularly, the large-scale ones, are addressed over the corresponding reduced chains. The bisimulation relations are defined for both CT-MCs and CT-CMCs to establish the equivalence between the original networks and their condensed networks. A computable algorithm is developed to compute the reachability-based maximal bisimulation relation for CMCs, resulting in the smallest bisimulating CMCs. Notably, one advantage of our techniques lies in their efficiency in implementing the existing analysis and control results on MCs and CMCs in a lower amount of time, with wide applications to logical networks, finite-field networks, finite automata, and Petri nets. Compared to their discrete-time counterparts, CT-MCs and CT-CMCs inherit a simplified essential network topology in the discrete-time structures while providing a quantitative description of transient functional kinetics on the micro-time scale level. Besides, all the developed theoretical results for CT-MCs and CT-CMCs are operated based on the transition rate matrices of chains rather than transition probability matrices used in the traditional methods. Finally, the derived theoretical results are validated by investigating the p53-Mdm2 signaling network and a relevant case-study involving a set of randomly generated CT-CMCs.</p
Synchronisation for multi-network with two types of inter-network coupling faults: pinning control effects
No full textInvestigation of simultaneous occurrence of permanent and/or recoverable faults of coupled nodes within different networks in a larger network structure is an appealing timely research topic. For the modelling of such a multi-network structure, the coupling terms in the same network and the coupling terms among different networks are described separately in order to explain clearly the multi-network feature here. The dimension-transformation matrix is used to deal with the mismatched dimensions of nodes in the different networks. Then a synchronisation controller is designed from the underlying theory of pinning control schemes. Furthermore, following the ideas of Lyapunov stability theory, a sufficient stability condition under the pinning control is derived which guarantees nodes in the same network synchronisation. Computer simulation results for a numerical case study of three coupled networks with nodes that possess rather complex non-linear dynamics demonstrate that the proposed controllers can enforce synchronisation despite different types of faults being occurred in the multi-network. It is also shown that the specific pinning control scheme is more effective than the random pinning.National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61473073, 61433014]; Fundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central Universities [N161702001, N182608003, N181706001, N171706003]This work was partially supported by the National Natural Science Foundation of China (61473073, 61433014) and Fundamental Research Funds for the Central Universities (N161702001, N182608003, N181706001, N171706003)
Contribution to the computation of regions of attraction of nonlinear systems based on the extended dynamic mode decomposition - Application to the anaerobic digestion
No full textEl tema principal de la tesis es la identificación basada en datos de la región de atracción (ROA por sus siglas en ingles) de puntos de equilibrio asintóticamente estables. Aunque esta es la principal contribución computacional, la mayoría del trabajo de la tesis constituye en satisfacer las condiciones subyacentes para lograr aproximar la ROA\@. Para obtener una aproximación precisa basada en datos del ROA en sistemas con múltiples puntos fijos o de equilibrio es necesario completar apropiadamente una serie de pasos partiendo de algunas trayectorias del sistema, i.e., asumiendo que no hay ningún acceso al modelo de ecuaciones diferenciales. La condición principal es una aproximación precisa del operador de Koopman ya que proporciona un grupo de eigenfunciones donde una composición particular de las mismas proporciona otra eingenfunción no trivial con eigenvalor asociado unitario. La principal propiedad de esta eingenfunción es que proporciona el ``manifold'' estable de los puntos de silla en el perímetro de la ROA\@. Por esta razón, para todo este procedimiento de trabajo, también es necesario tener una aproximación de la ubicación y estabilidad de los puntos fijos del sistema, recordando que la única entrada al algoritmo es un conjunto de trayectorias del sistema. Por consiguiente, el algoritmo debe ser una aproximación apropiada de las dinámicas del sistema y ser capaz de proporcionar una ecuación de diferencia que pueda proporcionar la ubicación y estabilidad de puntos fijos basándose en el análisis tradicional de sistemas no lineales. El algoritmo que tiene el potencial de alcanzar estos requisitos es el ``extended dynamics mode decomposition'' (EDMD), en donde la mayor parte del trabajo de esta tesis se enfoca en transformar el potencial que tiene este algoritmo en una realidad. En su mayor parte, el enfoque del desarrollo es sobre la estabilidad numérica del algoritmo, reduciendo el esfuerzo computacional y pasos necesarios para llevar a cabo la aproximación. Técnicos como la reducción de los polinomios ortogonales bas\'andose en las casi normas p-q y la eliminaci\'on de elementos polinomiales segur su error, aseguran que bases mas pequeños realicen las aproximaciones garantizando la existencia de soluciones debido a la propiedad de ortogonalidad. Mejoras como la recuperaron del estado a troves de la función inversa de los polinomios de una sola variable reducen el numero necesario de inversiones de matrices. Finalmente, las expansiones a priori del estado con funciones trigonométricas arbitrarias o cualquier otro tipo de funciones elementales, expanden los tipos posibles de sistemas que el algoritmo puede manejar. Como consecuencia de estas mejoras, la tesis logra los objetivos originales de analizar sistemas y controlar conjuntos de sistemas interconectados en un contexto basado en datos. Finalmente, la aplicación principal de la tesis es el análisis de la ROA en el proceso de digestión anaerobia, donde el análisis del fenómeno de multi-estabilidad que garantiza la operación correcta del reactor es de suma importancia.Le sujet principal de cette thèse de doctorat est la détermination de la région d’attraction des points d’équilibre asymptotiquement stables d’un système dynamique non linéaire. Cette détermination est réalisée numériquement sans avoir recours à la connaissance explicite d’un modèle mathématique du système, mais sur base d’un ensemble de trajectoires de celui-ci. Ces trajectoires peuvent être soit collectées expérimentalement au départ du système physique, soit obtenues par simulation numérique d’un modèle de forme arbitraire qui serait déjà disponible mais dont la structure ne doit pas être connue. A cette fin, le système dynamique non linéaire est représenté par un opérateur de Koopman. Cet opérateur est linéaire mais de dimension infinie et en pratique il est nécessaire de procéder à une approximation en dimension finie. Celle-ci est fournie par la méthode ``extended dynamic mode decomposition'' (EDMD), qui permet de construire une matrice de Koopman et de calculer les fonctions propres et les valeurs propres associées à celle-ci. En particulier, les fonctions propres associées à la valeur propre unitaire apparaissent comme étant particulièrement utiles. Ces fonctions propres permettent en effet de déterminer les « manifolds » stables des points selle qui se trouvent à la frontière de la région d’attraction. Outre cette détermination des points d’équilibre et de leur région d’attraction, ce travaille de thèse s’intéresse aux aspects numériques de la méthode EDMD, notamment le choix de bases polynomiales performantes et la réduction de l’ordre de l’approximation en utilisant des techniques telles que les quasi-normes p-q. Le choix des bases polynomiales est aussi important pour la représentation des entrées de commande des systèmes ou de leur couplages, dans le contexte de l’interconnexion de plusieurs systèmes dynamiques. Les dernières considérations théoriques de ce travail concernent donc les systèmes avec des entrées de commande et la possibilité de développer une commande prédictive en relation avec la représentation de Koopman. Enfin ce travail contient plusieurs illustrations dont une application à la détermination des points d’équilibre et des régions d’attraction du processus de digestion anaérobie, ainsi qu’un pendule inversé approximé par la méthode EDMD utilisant des fonctions de base trigonométriques, ainsi que des oscillateurs de Duffing couplés.The main topic of the thesis is the data-driven identification of the region of attraction (ROA) of asymptotically stable equilibrium points. Although this is the main computational contribution, satisfying the underlying conditions to make this possible constitutes most of the work of the thesis. To achieve an accurate data-driven approximation of the ROA in systems with multiple fixed or equilibrium points it is necessary to properly complete a series of steps parting from some trajectories of the system, i.e., assuming there is no access to the differential or difference model equation. The main condition is an accurate approximation of the Koopman operator because it provides a set of eigenfunctions where a particular composition of them gives another non-trivial eigenfunction with an associated eigenvalue that is unitary. The main property of this eigenfunction is that it gives the stable manifold of saddle points in the boundary of the ROA, where this stable manifold is in fact, the actual boundary of the ROA\@. Therefore, for this whole procedure to work, it also necessary to have an approximation of the location and stability of the fixed points of the system, recalling that the only input to the algorithm is a set of trajectories of the system. Consequently, the algorithm must be an appropriate approximation of the dynamics of the system and be able to provide a difference equation able to give the location and stability of fixed points upon further traditional non-linear system analysis. The algorithm that has the potential to achieve these requisites is the extended dynamics mode decomposition (EDMD) algorithm, where most of the work of this thesis focuses in transforming the potential into actual. For the most part, the development focus is on the numerical stability of the algorithm, reducing the computational effort and necessary steps to perform the approximation. Techniques such as the p-q-quasi norm reduction of orthogonal polynomials and polynomial element elimination according to its error, ensures that smaller bases perform the approximations while guaranteeing the existence of solutions because of the orthogonality property. Improvements such as the recovery of the state via the inverse of univariate order-one polynomials reduce the number of necessary matrix inversions. Finally, a priori expansions of the state with arbitrary trigonometric functions or any other kind of elemental functions, expand the possible types of systems that the algorithm can handle. As a consequence of these improvements, the thesis achieves the original objectives of analyzing systems and controlling sets of interconnected systems in a data-driven context. Finally, the main application of the thesis is the analysis of the ROA to the anaerobic digestion process, where the analysis of multi-stability phenomena that guarantees the proper operation of the reactor is of paramount importance. (Text taken from source)DoctoradoDoctor en Ingenierí
