Cooperative game theory-based steering law design of a CMG system

Spacecraft require a large-angle manoeuvre when performing agile manoeuvring tasks, therefore a control moment gyroscope(CMG) is employed to provide a strong moment.However, the control of the CMG system easily falls into singularity, which renders the actuator unable to output the required moment. To solve the singularity problem of CMGs, the control law design of a CMG system based on a cooperative game is proposed. First, the cooperative game model is constructed according to the quadratic programming problem, and the cooperative strategy is constructed. When the strategy falls into singularity, the weighting coefficient is introduced to carry out the strategy game to achieve the optimal strategy. In theory, it is proven that the cooperative game manipulation law of the CMG system converges, the sum of the CMG frame angular velocities is minimized, the energy consumption is small, and there is no output torque error. Then, the CMG group system is simulated.When the CMG system is near the singular point, it can quickly escape the singularity. When the CMG system falls into the singularity, it can also escape the singularity. Considering the optimization of angular momentum and energy consumption, the feasibility of the CMG system steering law based on a cooperative game is proven.

Game Analysis of Interfirm Cooperation with Three Modes of Supply Chains

In this paper we propose three modes of alliance structures of supply chains and discuss the cooperation mechanisms among enterprises firstly, and by analyzing the dyadic supply chains we apply the game theory to the research on cooperative relation among enterprises respectively for the three modes of alliance structures of supply chains, point out the conditions on which the supply chains can be set up and steadily keep up for a long time, and scientifically interpret the cooperative relation among enterprises.

Diffusion mechanism simulation of cloud manufacturing complex network based on cooperative game theory

Cloud manufacturing is a specific implementation form of the "Internet + manufacturing" strategy. Why and how to develop cloud manufacturing platform(CMP), however, remains the key concern of both platform operators and users. A microscopic model is proposed to investigate advantages and diffusion forces of CMP through exploration of its diffusion process and mechanism. Specifically, a three-stage basic evolution process of CMP is innovatively proposed. Then, based on this basic process, a more complex CMP evolution model has been established in virtue of complex network theory, with five diffusion forces identified. Thereafter, simulations on CMP diffusion have been conducted. The results indicate that, CMP possesses better resource utilization,user satisfaction, and enterprise utility. Results of simulation on impacts of different diffusion forces show that both the time required for CMP to reach an equilibrium state and the final network size are affected simultaneously by the five diffusion forces. All these analyses indicate that CMP could create an open online cooperation environment and turns out to be an effective implementation of the "Internet + manufacturing" strategy.

A NOVEL COOPERATIVE SPECTRUM SENSING METHOD BASED ON COOPERATIVE GAME THEORY

A novel cooperative sensing method is proposed in this paper. The proposed scheme adopts sensing creditability degree to characterize the impact of the distance and the channel parameters on the sensing result,and considers that each user has different average SNR and different decision threshold,by using General Nash Bargaining Solution (GNBS) strategy in Cooperative Game Theory (CGT),the detection performance for two-user case are derived. For multi-user case,the sensing performance is obtained with Hungarian method. Compared with the traditional schemes such as Nash Bargaining Solution (NBS) and AND,the proposed scheme covers all the factors mentioned above,and enhances the sensing rationality and reliability. Simulation results show that the proposed scheme can further improve the sensing performance and creditability.

A Game Theory Approach Using Excel

Understanding the behavior of companies in market conditions has been an important topic of studies for the economists and mathematicians. Many companies have treated their relationship of service providers as a game. Thus, the attitudes of the players can be endowed with rational thinking, which leads to the conclusion that the use of game theory as a tool to understand such behavior is of great importance. Based on the previous studies, this paper presents a study on the cooperative game theory, discussing the Nash equilibrium in pure and mixed strategies, treating solutions using the minimax John Von Neumarm theorem and illustrating a mathematical modeling of a game theory problem. Furthermore, a solution of linear programming using Microsoft Excel is also proposed and presented. The methodology adopted to model the problem may help students to familiarize themselves to game theory.

Cooperative Differential Game for Model Energy-Bandwidth Efficiency Tradeoff in the Internet of Things

Internet of Things （IoT） refers to an infrastructure which enables the forms of com- munication and collaboration between people and things, and between things themselves. In order to improve its performance, we present a tradeoff between bandwidth and energy con- sumption in the loT in this paper. A service providing model is built to find the relation- ship between bandwidth and energy consump- tion using a cooperative differential game mo- del. The game solution is gotten in the condi- tion of grand coalition, feedback Nash equili- brium and intermediate coalitions and an allo- cation policy is obtain by Shapley theory. The results are shown as follows. Firstly, the per- formance of IoT decreases with the increasing of bandwidth cost or with the decreasing of en- ergy cost; secondly, all the nodes in the IoT com- posing a grand coalition can save bandwidth and energy consumption; thirdly, when the fac- tors of bandwidth cost and energy cost are eq- ual, the obtained number of provided services is an optimised value which is the trade-off between energy and bandwidth consumption.

Cooperative Game Approach for Scheduling in Two-Virtual-Antenna Cellular Networks with Relay Stations Fairness Consideration

In thsssse cellular network, Relay Stations (RSs) help to improve the system performance; however, little work has been done considering the fairness of RSs. In this paper, we study the cooperative game approaches for scheduling in the wireless relay networks with two-virtual-antenna array mode. After defining the metric of relay channel capacity, we form a cooperative game for scheduling and present the interpretation of three different utilization objectives physically and mathematically. Then, a Nash Bargaining Solution (NBS) is utilized for resource allocation considering the traffic load fairness for relays. After proving the existence and uniqueness of NBS in Cooperative Game (CG-NBS), we are able to resolve the resource allocation problem in the cellular relay network by the relay selection and subcarrier assignment policy and the power allocation algorithm for both RSs and UEs. Simulation results reveal that the proposed CG-NBS scheme achieves better tradeoff between relay fairness and system throughput than the conventional Maximal Rate Optimization and Maximal Minimal Fairness methods.

Bargaining Game Theoretic Power Control in Selfish Cooperative Relay Networks

Wireless cooperative communications require appropriate power allocation （PA） between the source and relay nodes. In selfish cooperative communication networks, two partner user nodes could help relaying information for each other, but each user node has the incentive to consume his power solely to decrease its own symbol error rate （SER） at the receiver. In this paper, we propose a fair and efficient PA scheme for the decode-and-forward cooperation protocol in selfish cooperative relay networks. We formulate this PA problem as a two-user cooperative bargaining game, and use Nash bargaining solution （NBS） to achieve a win-win strategy for both partner users. Simulation results indicate that the NBS is fair in that the degree of cooperation of a user only depends on how much contribution its partner can make to decrease its SER at the receiver, and efficient in the sense that the SER performance of both users could be improved through the game.

Strategically supported cooperation in dynamic games with coalition structures

The problem of strategic stability of long-range cooperative agreements in dynamic games with coalition structures is investigated. Based on imputation distribution procedures, a general theoretical framework of the differential game with a coalition structure is proposed. A few assumptions about the deviation instant for a coalition are made concerning the behavior of a group of many individuals in certain dynamic environments.From these, the time-consistent cooperative agreement can be strategically supported by ε-Nash or strong ε-Nash equilibria. While in games in the extensive form with perfect information, it is somewhat surprising that without the assumptions of deviation instant for a coalition, Nash or strong Nash equilibria can be constructed.

A Combination Method for Wind Power Prediction Based on Cooperative Game Theory

Accurate prediction of wind power is significant for power system dispatching as well as safe and stable operation. By means of BP neural network, radial basis function neural network and support vector machine, a new combined method of wind power prediction based on cooperative game theory is proposed. In the method, every single forecasting model is regarded as a member of the cooperative games, and the sum of square error of combination forecasting is taken as the result of cooperation. The result is divided among the members according to Shapley values, and then weights of combination forecasting can be obtained. Application results in an actual wind farm show that the proposed method can effectively improve prediction precision.

Shapley value cooperative game theory-based locational marginal price computation for loss and emission reduction

An iterative method based on Shapley Value Cooperative Game Theory is proposed for the calculation of local marginal price (LMP) for each Distributed Generator (DG) bus on a network. The LMP value is determined for each DG on the basis of its contribution to reduce loss and emission reduction, which is assessed using the Shapley Value approach. The proposed approach enables the Distribution Company (DISCO) decision-maker to operate the network optimally in terms of loss and emission. The proposed method is implemented in the Taiwan Power Company distribution network 7 warnings consisting of 84 buses and 11 feeders in the MATLAB environment. The results show that the proposed approach allows DISCO to operate the network on the basis of its priority between the reduction of active power loss and emission in the network.

Benefit-based cost allocation for residentially distributed photovoltaic systems in China:A cooperative game theory approach

Distributed photovoltaic(PV)systems have constantly been the key to achieve a low-carbon economy in China.However,the development of Chinese distributed PV systems has failed to meet expectations because of their irrational profit and cost allocations.In this study,the methodology for calculating the levelized cost of energy(LCOE)for PV is thoroughly discussed to address this issue.A mixed-integer linear programming model is built to determine the optimal system operation strategy with a benefit analysis.An externality-corrected mathematical model based on Shapley value is established to allocate the cost of distributed PV systems in 15 Chinese cities between the government,utility grid and residents.Results show that(i)an inverse relationship exists between the LCOEs and solar radiation levels;(ii)the government and residents gain extra benefits from the utility grid through net metering policies,and the utility grid should be the highly subsidized participant;(iii)the percentage of cost assigned to the utility grid and government should increase with the expansion of battery bank to weaken the impact of demand response on increasing theoretical subsidies;and(iv)apart from the LCOE,the local residential electricity prices remarkably impact the subsidy calculation results.

A bargaining game theoretic method for virtual resource allocation in LTE-based cellular networks

In this paper, we study the virtual resource(VR) allocation problem in LTE-based wireless network virtualization(WNV). A practical network scenario, where multiple virtual wireless service providers(WSPs)request the VR from a unique mobile network operator(MNO) is considered. Our objective is two folds. The first is to guarantee the minimum rate requirements of the MNO and the WSPs. The second is to distribute the system rate among the MNO and the WSPs in the Pareto optimal manner. To this end, an efficient VR allocation scheme based on bargaining game theory is proposed, and the Nash bargaining solution(NBS) method is used to solve the proposed game problem. The proposed game problem is proved to be a convex optimization problem. By using standard convex optimization method, the global optimal NBS of the game is obtained in closed form. The effectiveness of the proposed VR allocation game is testified through numerical results.

Game Theoretic Subcarrier and Power Allocation for Wireless OFDMA Networks

This paper proposes a bargaining game theoretic resource(including the subcarrier and the power) allocation scheme for wireless orthogonal frequency division multiple access(OFDMA) networks.We define a wireless user s payoff as a function of the achieved data-rate.The fairness resource allocation problem can then be modeled as a cooperative bargaining game.The objective of the game is to maximize the aggregate payoffs for the users.To search for the Nash bargaining solution(NBS) of the game,a suboptimal subcarrier allocation is performed by assuming an equal power allocation.Thereafter,an optimal power allocation is performed to maximize the sum payoff for the users.By comparing with the max-rate and the max-min algorithms,simulation results show that the proposed game could achieve a good tradeoff between the user fairness and the overall system performance.

Optimization of energy exchange in microgrid networks: a coalition formation approach

In this paper, we elaborate a new strategy based on cooperative game theory models to encourage and manage the interactions in a MicroGrid network. The proposed strategy optimizes the cooperation and the energy exchange in a distributed μGrid network. The strategy consists of a two stage algorithm: Coalition formation algorithm which was specifically created to approximate the optimal set of coalitions that return considerable savings. And the Matching game to manage the energy exchange inside each coalition. The performance of our strategy was verified through simulations. These latter show that the losses can be considerably decreased by the use of the proposed strategy: the rate of the loss reduction can reach up to 20% if the two stages are applied on the network. Moreover, the strategy proved to have a fast convergence which makes it operational for real implemented networks.

Conflict resolution for connected automated vehicles at unsignalized roundabouts considering personalized driving behaviours

To address the driving conflicts of connected automated vehicles(CAVs)at unsignalized roundabouts,a cooperative decision-making framework is proposed.The personalized driving preferences of CAVs are considered in the decision-making algorithm,which are reflected by different driving styles.A motion prediction algorithm is used to improve the decision-making performance.The effect of the motion prediction algorithm on the decisionmaking performance is evaluated,including the advancement of driving safety and the computational load for the hardware.The cooperative game theoretic approach is applied to the interaction modelling and collaborative decision making of CAVs.Finally,hardware-in-the-loop(HIL)tests are carried out to evaluate the feasibility and real-time performance of the proposed algorithm.