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This paper considers the problem of stabilizing a class of linear time-invariant large-scale systems composed of a number of subsystems using several local dynamic output feedback controllers. For this problem, a sufficient condition on each closed-loop individual subsystem is derived under which the decentralized controller composed of the local controllers designed for individual subsystems, achieves stability for the overall system. This condition is used to convert the decentralized stabilization problem to a set of the H∞ disturbance rejection subproblems  

This paper considers the problem of stabilizing a class of linear time-invariant large-scale systems composed of a number of subsystems using several local dynamic output feedback controllers. For this problem, a sufficient condition on each closed-loop individual subsystem is derived under which the decentralized controller composed of the local controllers designed for individual subsystems, achieves stability for the overall system. This condition is used to convert the decentralized stabilization problem to a set of the H∞ disturbance rejection subproblems  

This paper is concerned with a new method for decomposing large scale systems into disjoint neighborhoods of subsystems with specific size determined a priori for managing communication load of a Jacobi based distributed optimal control method. The proposed decomposition method clusters subsystems into disjoint neighborhoods based on the strength of control inputs interaction between subsystems. The proposed method is a new method and uses the time response of system for decomposition. Using extensive computer simulation it is illustrated that this method finds the best decomposition. © 2017 IEEE  

In this paper a new two-level method for stochastic control of large-scale systems is presented. This two-level approach is based on Interaction Balance Principle (Goal coordination) for optimization problem and a two-level computational algorithm using extended Kalman filter for the estimation one. The two-level optimizer uses a new coordinator which works by the gradient of interaction errors that improves the convergence rate of the solution. The significance and the applicability of the theoretical developments of this paper are also shown by a numerical example. © 2006 IEEE  

The budding yeast Saccharomyces cerevisiae is the first eukaryote whose genome has been completely sequenced. It is also the first eukaryotic cell whose proteome (the set of all proteins) and interactome (the network of all mutual interactions between proteins) has been analyzed. In this paper we study the structure of the yeast protein complex network in which weighted edges between complexes represent the number of shared proteins. It is found that the network of protein complexes is a small world network with scale free behavior for many of its distributions. However we find that there are no strong correlations between the weights and degrees of neighboring complexes. To reveal... 

This paper presents a two-level optimal control for the binary distillation column. From the control point of view, the binary distillation column is a high-order system consisting of several interconnected subsystems (trays) that aim to maximize output purity. Controlling the system in a hierarchical manner not only decreases complexity and solution time but also can improve the control structure's reliability. In this study, the distillation column is decomposed into NT second-order subsystems, each representing one stage (one tray). Accordingly, the cost function is decomposed, and thus, the overall problem is converted into NT lower-order subproblems where each tray has its own... 

In this paper, a new interaction prediction approach is presented for optimal control of nonlinear large-scale systems. The proposed approach uses a new gradient-type coordination scheme which has a larger convergence region with respect to the parameters' variation, and also has a good convergence rate. In this approach, the coordination vector is updated using the gradient of coordination error. This type of coordination considerably reduces the number of iterations. The robustness and the convergence rate of the proposed approach against the best classical interaction prediction approaches are shown through simulations of a benchmark problem. © 2008 IEEE  

In this letter, we study large-scale networks in terms of observability and controllability. In particular, we compare the number of unmatched nodes in two main types of Scale-Free (SF) networks: the Barabási-Albert (BA) model and the Holme-Kim (HK) model. Comparing the two models based on theory and simulation, we discuss the possible relation between clustering coefficient and the number of unmatched nodes. In this direction, we propose a new algorithm to reduce the number of unmatched nodes via link addition. The results are significant as one can reduce the number of unmatched nodes and therefore number of embedded sensors/actuators in, for example, an IoT network. This may significantly... 

Coordination strategies in large-scale systems are mainly based on two principles; Interaction Prediction Principle and Interaction Balance Principle. In this paper, which consists of two parts, the concept of coordination is introduced within the framework of two-level large-scale systems, and two new approaches for coordination based on Interaction Prediction Principle and Interaction Balance Principle have been presented. The new strategies have much faster convergence rate than the previously suggested classical methods. They extremely reduce the number of iterations required for obtaining the overall optimal solutions. The efficacy and advantage of the proposed approaches, in compare to... 

In this paper, which consists of two parts, a new two-level computational algorithm is used for nonlinear optimal control of large-scale systems. The two-level optimizer uses a new coordination strategy which is based on the gradient of interaction errors instead of the gradient of overall performance function. The advantages of the new method can be categorized into two parts: First, the new formulation is applicable to a large class of problems whilst the classical model coordination method is not. Second, it extremely reduces the number of iterations required for obtaining the overall optimal solution. Although the computational burden of the algorithm in the first level increases... 

In this paper, a new approach for optimal control of robot manipulators is presented. For this purpose, the system is considered as a two-level large-scale system where a gradient based coordination strategy is used to coordinate the overall system. This is achieved within a decomposition-coordination framework, where the robot manipulator is first decomposed into several sub-systems in such a way that each sub-system consists of several consecutive links and joints. With the aim of optimization, the control problem is first decomposed into m sub-problems, at the first level, where each sub-problem is solved using a gradient optimization method. Then, by using a new methodology which is... 

This paper is concerned with the disturbance attenuation problem of fuzzy large-scale systems which consist of N interconnected subsystems which are represented by Takagi-Sugeno fuzzy models. Using Lyapunov function and linear matrix inequalities (LMIs), a criterion is proposed to have a prescribed level of disturbance attenuation. A numerical example is given to illustrate the control design procedure and its effectiveness  

We study the metal-insulator transition in one-dimensional Anderson binary alloy with long-range disordered hopping integrals and on-site energies using the transfer matrix method. In this model, the on-site energies and hopping integrals are distributed randomly with long-range correlations characterized by power spectrum of the type S(k)∝1/k(2α-1), with different exponents αε and αt, respectively. We determine the critical value of long-range correlation exponent of hopping integral in the presence of only off-diagonal disorder in which the transition from localized to extended states occurs in thermodynamic limit. When both of the on-site energies and hopping... 

Some fundamental and unique characteristics of space are (1) global perspective, (2) above the atmosphere, (3) gravity-free environment, (4) abundant resources, and (5) exploration of space itself. If the mission doesn't rely on some fundamental and unique characteristics of space, it will likely cost more to do in space than in air or on Earth [1]. On the other hand, design of complex systems like satellites involves selecting design parameters (DPs) to satisfy the required constraints while meeting desired performance objectives. These parameters are often coupled, and their relationships not easily understood, and it makes the design an iterative process with high complexity [2]. But in... 

In this paper, a new approach is presented for optimal control of large-scale chemical processes. In this approach, the chemical process is decomposed into smaller sub-systems at the first level, and a coordinator at the second level, for which a two-level hierarchical control strategy is designed. For this purpose, each sub-system in the first level can be solved separately, by using any conventional optimization algorithm. In the second level, the solutions obtained from the first level are coordinated using a new gradient-type strategy, which is updated by the error of the coordination vector. The proposed algorithm is used to solve the optimal control problem of a complex nonlinear... 

Synchronizability of dynamical networks can be defined as the ease by which the network synchronizes its activity. We propose a method for enhancing the synchronizability of dynamical networks by efficient rewirings. The method is based on the eigenvectors corresponding to the second smallest and the largest eigenvalue of the Laplacian matrix and a modified version of the simulated annealing approach is used to perform the optimization task. Starting from a simple network, i.e. an undirected and unweighted network, and at each step, an edge is selected for disconnection and two non-adjacent nodes for creating at edge in between. The effectiveness of the algorithm is tested on artificially... 

In this paper, we study large-scale networks in terms of observability and controllability. In particular, we compare the number of unmatched nodes in two main types of Scale-Free (SF) networks: the Barabási-Albert (BA) model and the Holme-Kim (HK) model. Comparing the two models based on theory and simulation, we discuss the possible relation between clustering coefficient and the number of unmatched nodes. In this direction, we propose a new algorithm to reduce the number of unmatched nodes via link addition. The results are significant as one can reduce the number of unmatched nodes and therefore number of embedded sensors/actuators in, for example, an IoT network. This may significantly...