Research On Controllability Analysis And Optimization Method Of Distributed Operational Network

With the extensive application of information and network technology in war system, great changes take place in the form of war, which converts the combat mode in traditional centralized industrial era. As a result, the Distributed Networked Operation Model(DNOM) is born at this time. DNOM is an extraction of Network Centric Warfare(NCW) and an advanced combat pattern of combat in the information era. In DNOM, combat units are distributed disposed in the whole combat space. The combat units could investigate the whole combat environment and receive real-time intelligence by interactions of information networks. According to the intelligence, the combat units could react spontaneously and execute networked command and control so that they could combat effectively in more flexible combat organization. In the meanwhile, the above characters of DNOM have caused the revolution of combat command and control, and networked command and control have become the inevitable trend. The characters like distribution, autonomy, flexibility, and complexity of DNOM and the limited cognitive degree of complexity science and control theory have lead researches about networked control of distributed operation network(DON) a challenging topic.The core of distributed operation system is its structure of network. Thus, the investigation of networked control of distributed operation system could start form the control of combat network. The primary question of combat system control is the answer of whether the system could be controlled, namely, the controllability of DON. Therefore, Research on controllability analysis and optimization method of DON would have profound theoretical and practical effects on the combat, command, and control in the information-based warfare.This work is based on the novel needs of combat pattern in the information era and the revolution of control methods, and focus on the analysis of controllability and optimization of DON. Through the existed researches about complex science, complex network theory and control theory, we reveal the essence and internal mechanism of the networked control of DON in the information age.The main contributions are as follows:1. We construct models of combat system based on complex network theory and method, and make a detailed analysis and the conceptual definition of combat entities and their interaction in DON. In the constructed network of DON, the node denotes the combat entity while the edge describes the interaction relationship. Based on the solution of maximum-matching networked controllability, combined with the complex network model of DON, we build the controllability analysis frame of DON, and provide fundamental supports for the controllability optimization method and robustness research of combat system.2. For the variety structures of DON, we propose the controllability method of DOS based on topology structure. Firstly, we make a formal description of the problem of DON controllability optimization. Then we investigate the controllability optimization algorithm of redundancy edge rewire based on complex network model and controllability analysis frame of DON. The method gets the redundancy edges by classifying the edges in the nework, and then based on the control path in the network, sets the priority of the location of the rewired edges, which set the rule for the edges to rewire. The method could optimize the network whose average degree is over 2 to the state of optimal control, and at last three types of statistical characters of optimal control network are compared with the simulated experiments.3. For the situation that the network topology can not be changed, we propose optimize controllability strategies of DON based on the direction of edges. Considering different applicated background, we propose three methods of optimize controllability through the direction of edges respectively, including the optimization method based on the redundancy of nodes, the optimization method based on the control path, and optimization method based on the local structure information. The first one is direct, convenient, and easy to use. We analyze the affection of direction of edges for controllability of organized structure and propose a heuristic method which analyzes and designs the edge direction in the network by defining the redundancy of nodes. Then, for the topological structure and edge direction of existing organization structure, we analyze the detail control path in the network, which optimizes controllability of command and control structure. Considering the optimization method based on the redundancy of nodes neglect the original direction of edges, we propose another optimization method based on controlled paths. The method is based on the original direction of edges, revert minimum number of edges’ direction aim to optimizing controllability. To reach the goal, we classify the nodes according to the controlled path to get the candidate edge set, and then reverse the edges. Considering unavailability of complete network topology structure information in some special combat environment, we investigate to utilize local structure feature to perform the controllability optimization method through statistics of local structure feature of candidate edges and then propose an advanced simulated annealing algorithm to reverse edge direction.4. In the paper, we also propose the the controllability analysis model of DON, in which the nodes overloaded failure. In the meanwhile, we also define the index of controlled robustness and propose the dynamic optimization method of conrolled robustness in DON. For the nodes overloaded failure phenomenon in the network of DON, we firstly analyze control robustness of nodes overloaded failure and define the concept of failure nodes. Then, we introduce two types of overloaded failure models to analyze the network controlled robustness. Furthermore, we investigate the optimization of controlled robustness in DON. Firstly, we define an index of controlled robustness based on nodes attacking strategy. Then, we propose a dynamical optimization method of controlled robustness in DON and compare it with the existing static optimization methods. Finally, we use two network statistical feature, heterogeneity and degree correlation coefficient, to research the variety law of controlled robustness in DON before and after optimization.In the end of paper, we design a specific case, perform a simultaneous analysis based on the system of system combat simulation, and verify the correctness and effectiveness of the constructed models and methods.