A2-1 - Sedma Nacionalna Konferencija so Me|unarodno U~estvo...

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COMPUTATIONAL EFFICIENCY OF NONITERATIVE PREDICTIVE COORDIATION K. Stoilova 1 , T. Stoilov 1 1 Institute of computer and communication systems, Bulgarian academy of sciences, 1113 Sofia, Acad.G.Bontchev str. BL.2, kstoilova@hsi.iccs.bas.bg , todor@hsi.iccs.bas.bg Abstract – It is presented a hierarchical optimization model for solving optimization problem, which apply analytical relations for the problem solution. Thus the optimization problem is solved without iterative and recursive calculations, speeding up the problem solution. Such noniterative computational technique benefits the application of real problem solution, real time system management and on-line decision making. Keywords – Multilevel hierarchical systems, optimization, coordination, real-time control 1. INTRODUCTION The drawback of the hierarchical approaches, applied for solving control problems in hierarchical systems, based on the iterative nature of solving the optimization problems on different levels. This iterative manner of computation insists multiple data transfer of intermediate results between the system levels [1,2]. For the case of distributed control systems, these iterative calculations are related with communication data transfer between the distributed subsystems, without performing any control actions. Thus, the iterative solution delays the implementation of the optimal control decision. This peculiarity of the hierarchical system operation prevents the implementation of the hierarchical system approach for the on-line system control [4, 5]. To overcome the delay in hierarchical system management a noniterative goal control strategy for the hierarchical systems has been developed [8]. Its peculiarity is based on the reduced data transfer between the subsystems and the coordinator in restricted sequence: prepositions of the local subsystems to the coordinator and approval or correction by the coordinator. The Multilevel hierarchical theory is based on decomposition approaches for solving the multilevel optimization problems. The decomposition technique allows the original complex optimization problem to be reduced to a set of low order optimization subproblems, coordinated by the coordination problem to generate the components of the global solution of the original problem. Thus, instead of direct solution of a high ordered and complex optimization problem, the multilevel theory manages and coordinates the solutions of low order optimization subproblems giving solutions to the initial global optimization problem. The positive influences of the hierarchical approach address the large-scale systems by decomposition and decentralization of the decision-making and control processes. Hence, a complex high dimensional distributed system operates under the control of a set of low-ordered control units hierarchically connected.
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A2-1 - Sedma Nacionalna Konferencija so Me|unarodno U~estvo...

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