In this paper, we investigate a model-free design of decentralized event-triggered mechanism for networked control systems (NCSs). The approach aims at simultaneously tuning the optimal parameters for the controller and the event-triggered condition, such that a prescribed cost function can be minimized. To achieve this goal, we employ the Bayesian optimization (BO), which is known to be an automatic tuning framework for finding the optimal solution to the black-box optimization problem. Thanks to its efficient search strategy for the global optimum, the BO allows us to design the event-triggered mechanism with relatively a small number of experimental evaluations. This is particularly suited for NCSs where network resources such as the limited life-time of battery powered devices are limited. Some simulation examples illustrate the effectiveness of the approach.

A composite system consists of many subsystems, which have interconnections with other subsystems. For such a system, in general, we utilize decentralized control, where each subsystem is controlled by a local controller. On the other hand, event-triggered control is one of useful approaches to reduce the amount of communications between a controller and a plant. In the event-triggered control, an event triggering mechanism (ETM) monitors the information of the plant, and determines the time to transmit the data. In this paper, we propose a design of ETMs for the decentralized event-triggered control of nonlinear composite systems using an M-matrix. We consider the composite system where there is an ETM for each subsystem, and ETMs monitor local states of the corresponding subsystems. Each ETM is designed so that the composite system is stabilized. Moreover, we deal with the case of linear systems. Finally, we perform simulation to show that the proposed triggering rules are useful for decentralized control.

We consider a decentralized similarity control problem for composite nondeterministic discrete event systems, where each subsystem has its own local specification and the entire specification is described as the synchronous composition of local specifications. We present necessary and sufficient conditions for the existence of a complete decentralized supervisor that solves a similarity control problem under the assumption that any locally uncontrollable event is not shared by other subsystems. We also show that the system controlled by the complete decentralized supervisor that consists of maximally permissive local supervisors is bisimilar to the one controlled by the maximally permissive monolithic supervisor under the same assumption.

It is not easy to provide energy supply based on renewable energy enough to satisfy energy demand anytime and anywhere because the amount of renewable energy depends on geographical conditions and the time of day. In order to maximize the satisfaction of energy demand by renewable energy, surplus energy generated with renewable energy should be stored in batteries, and transmitted to electric loads with high demand somewhere in the electricity system. This paper proposes a novel autonomous decentralized mechanism of energy interchanges between distributed batteries on the basis of the diffusion equation and MCMC (Markov Chain Monte Carlo) for realizing energy supply appropriately for energy demand. Experimental results show that the proposed mechanism effectively works under several situations. Moreover, we discuss a method to easily estimate the behavior of the entire system by each node with the proposed mechanism, and the application potentiality of this estimating method to an efficient method working with non-renewable generators while minimizing the dependence of non-renewable energy, and an incentive mechanism to prevent monopolizing energy in systems.

Mobile ad hoc networks (MANETs) consist of mobile terminals that directly connect with one another to communicate without a network infrastructure, such as base stations and/or access points of wireless local area networks (LANs) connected to wired backbone networks. Large-scale disasters such as tsunamis and earthquakes can cause serious damage to life, property as well as any network infrastructure. However, MANETs can function even after severe disasters have destroyed regular network infrastructure. We have proposed an autonomous decentralized structure formation technology based on local interaction, and have applied it to implement autonomous decentralized clustering on MANETs. This method is known to configure clusters that reflect the network condition, such as residual battery power and the degree of each node. However, the effect of clusters that reflect the network condition has not been evaluated. In this study, we configure clusters using our method, the back-diffusion method, and a bio-inspired method, which is a kind of autonomous decentralized clustering that cannot reflect the network condition. We also clarify the importance of clustering that reflects the network condition, with regard to power consumption and data transfer efficiency.

Differential games are considered an extension of optimal control problems, which are used to formulate centralized control problems in smart grids. Optimal control theory is used to study systems consisting of one agent with one objective, whereas differential games are used to formulate systems consisting of multiple agents with multiple objectives. Therefore, a differential-game-theoretic approach is appropriate for formulating decentralized demand-side energy management systems where there are multiple decision-making entities interacting with each other. Moreover, in many smart grid applications, we need to obtain information for control via communication systems. To formulate the influence of communication availability, differential game theory is also promising because the availability of communication is considered as part of an information structure (i.e., feedback or open-loop) in differential games. The feedback information structure is adopted when information for control can be obtained, whereas the open-loop information structure is applied when the information cannot be obtained because of communication failure. This paper proposes a comprehensive framework for evaluating the performance of demand-side actors in a demand-side management system using each control scheme according to both communication availability and sampling frequency. Numerical analysis shows that the proposed comprehensive framework allows for an analysis of trade-off for decentralized and centralized control schemes.

As wireless LAN systems become more widespread, the number of access points (APs) is increasing. A large number of APs cause overlapping cells where nearby cells utilize the same frequency channel. In the overlapping cells, inter-cell interference (ICI) degrades the throughput. This paper proposes an interference-aware multi-cell beamforming (IMB) technique to reduce the throughput degradation in the overlapping cells. The IMB technique improves transmission performance better than conventional multi-cell beamforming based on a decentralized control scheme. The conventional technique mitigates ICI by nullifying all the interference signal space (ISS) by beamforming, but the signal spaces to the user terminal (UT) is also limited because the degree of freedom (DoF) at the AP is limited. On the other hand, the IMB technique increases the signal space to the UT because the DoF at the AP is increased by selecting the ISS by allowing a small amount of ICI. In addition, we introduce a method of selecting the ISS in a decentralized control scheme. In our work, we analyze the interference channel state information (CSI) and evaluate the transmission performance of the IMB technique by using a measured CSI in an actual indoor environment. As a result, we find that the IMB technique becomes more effective as the number of UT antennas in nearby cells increases.

In this paper, we study decentralized supervisory control of timed discrete event systems, where we adopt the OR rule for fusing local enablement decisions and the AND rule for fusing local enforcement decisions. For any specification language satisfying a certain assumption, we propose a method for constructing a decentralized supervisor that achieves its sublanguage. The proposed method does not require computing the achieved sublanguage.

In this paper, we study decentralized supervisory control of timed discrete event systems, where we adopt the OR rule for fusing local enablement decisions and the AND rule for fusing local enforcement decisions. Under these rules, necessary and sufficient conditions for the existence of a decentralized supervisor that achieves a given specification language are easily obtained from the result of literature. If a given specification language does not satisfy these existence conditions, we must compute its sublanguage satisfying them. The main contribution of this paper is proposing a method for computing such a sublanguage.

In the framework of decentralized supervisory control of timed discrete event systems (TDESs), each local supervisor decides the set of events to be enabled to occur and the set of events to be forced to occur under its own local observation in order for a given specification to be satisfied. In this paper, we focus on fusion rules for the enforcement decisions and adopt the combined fusion rule using the AND rule and the OR rule. We first derive necessary and sufficient conditions for the existence of a decentralized supervisor under the combined fusion rule for a given partition of the set of forcible events. We next study how to find a suitable partition.

Clustering technology is very important in ad hoc networks and sensor networks from the view point of reducing the traffic load and energy consumption. In this paper, we propose a new structure formation mechanism as a tool for clustering. It meets the key clustering requirements including the use of an autonomous decentralized algorithm and a consideration of the situation of individual nodes. The proposed mechanism follows the framework of autonomous decentralized control based on local interaction, in which the behavior of the whole system is indirectly controlled by appropriately designing the autonomous actions of the subsystems. As an application example, we demonstrate autonomous decentralized clustering for a two-dimensional lattice network model, and the characteristics and adaptability of the proposed method are shown. In particular, the clusters produced can reflect the environmental situation of each node given by the initial condition.

In the framework of supervisory control of timed discrete event systems (TDESs), a supervisor decides the set of events to be enabled to occur and the set of events to be forced to occur in order for a given specification to be satisfied. In this paper, we consider decentralized supervisory control of TDESs where enforcement decisions of local supervisors are fused by the AND rule or the OR rule. We derive existence conditions of a decentralized supervisor under these decision fusion rules.

We have previously proposed a diffusion-type flow control mechanism as a solution for severely time-sensitive flow control required for high-speed networks. In this mechanism, each node in a network manages its local traffic flow using the basis of only the local information directly available to it, by using predetermined rules. In addition, the implementation of decision-making at each node can lead to optimal performance for the whole network. Our previous studies show that our flow control mechanism with certain parameter settings works well in high-speed networks. However, to apply this mechanism to actual networks, it is necessary to clarify how to design a parameter in our control mechanism. In this paper, we investigate the range of the parameter and derive its optimal value enabling the diffusion-type flow control to work effectively.

We have proposed a diffusion-type flow control mechanism to achieve the extremely time-sensitive flow control required for high-speed networks. In this mechanism, each node in a network manages its local traffic flow only on the basis of the local information directly available to it, by using predetermined rules. In this way, the implementation of decision-making at each node can lead to optimal performance for the whole network. Our previous studies concentrated on the flow control for a single flow. In this paper, we propose a diffusion-type flow control mechanism for multiple flows. The proposed scheme enables a network to quickly recover from a state of congestion and to achieve fairness among flows.

In current IP-based networks, the application of window-based end-to-end flow control, including TCP, to ensure reliable flows is an essential factor. However, since such a flow control is provided by the end hosts, end-to-end control cannot be applied to decision-making in a time-scale shorter than the round-trip delay. We have previously proposed a diffusion-type flow control mechanism to realize the extremely time sensitive flow control that is required for high-speed networks. In this mechanism, each network node manages its own traffic only on the basis of the local information directly available to it, by using predetermined rules. The implementation of decision-making at each node can lead to optimal performance for the whole network. Our previous studies showed that the mechanism works well, by itself, in high-speed networks. However, to apply this mechanism to actual networks, it needs to be able to coexist with other existing protocols. In this paper, we investigate the performance of diffusion-type flow control coexisting with TCP. We show that diffusion-type flow control can coexist with TCP and the two can be complementary. Then, we show that a combination of both controls achieves higher network performance than TCP alone in high-speed networks.

A supervisor proposed by Ramadge and Wonham controls a discrete event system (DES) so as to satisfy logical control specifications. However a precise description of both the specifications and the DES is needed for the control. This paper proposes a synthesis method of the supervisor for decentralized DESs based on reinforcement learning. In decentralized DESs, several local supervisors exist and control the DES jointly. Costs for disabling and occurrence of events as well as control specifications are considered. By using reinforcement learning, the proposed method is applicable under imprecise specifications and uncertain environment.

We have proposed diffusion-type flow control as a solution for the extremely time-sensitive flow control required for high-speed networks. In our method of flow control, we design in advance simple and appropriate rules for action at the nodes, and these automatically result in stable and efficient network-wide performance through local interactions between nodes. Specifically, we design the rules for the flow control action of each node that simulates the local interaction of a diffusion phenomenon, in order that the packet density is diffused throughout the network as soon as possible. However, in order to make a comparison with other flow control methods under the same conditions, the evaluations in our previous studies used a closed network model, in which the number of packets was unchanged. This paper investigates the performance of our flow control method for an end-to-end flow, in order to show that it is still effective in more realistic networks. We identify the key issues associated with our flow control method when applied to an open network model, and demonstrate a two-step solution. First, we consider the rule for flow control action at the boundary node, which is the ingress node in the network, and propose a rule to achieve smooth diffusion of the packet density. Secondly, we introduce a shaping mechanism, which keeps the number of packets in the network at an appropriate level.

A game-theoretic analysis is applied to the evaluation of capacity and stability of a wireless ad hoc network in which each source node independently chooses a route to the destination node so as to enhance throughput. First, the throughput of individual multihop transmission with rate adaptation is evaluated. Observations from this evaluation indicate that the optimal number of hops in terms of the achievable end-to-end throughput depends on the received signal-to-noise ratio. Next, the decentralized adaptive route selection problem in which each source node competes for resources over arbitrary topologies is defined as a game. Numerical results reveal that in some cases this game has no Nash equilibria; i.e., each rational source node cannot determine a unique route. The occurrence of such cases depends on both the transmit power and spatial arrangement of the nodes. Then, the obtained network throughput under the equilibrium conditions is compared to the capacity under centralized scheduling. Numerical results reveal that when the transmit power is low, decentralized adaptive route selection may attain throughput near the capacity.

The traffic congestion problem in urban areas is worsening since traditional traffic signal control systems cannot provide] efficient traffic regulation. Therefore, dynamic traffic signal control in Intelligent Transportation System (ITS) recently has received increasing attention. This study devised a multi-agent architecture, the Adaptive and Cooperative Traffic light Agent Model (ACTAM), for a decentralized traffic signal control system. The proposed architecture comprises a data storage and communication layer, a traffic regulation factor processing layer, and a decision-making layer. This study focused on utilizing the cooperation of multi-agents and the prediction mechanism of our architecture, the Forecast Module, to forecast future traffic volume in each individual intersection. The Forecast Module is designed to forecast traffic volume in an intersection via multi-agent cooperation by exchanging traffic volume information for adjacent intersections, since vehicles passing through nearby intersections were believed to significantly influence the traffic volume of specific intersections. The proposed architecture can achieve dynamic traffic signal control. Thus, total delay time of the traffic network under ACTAM can be reduced by 37% compared to the conventional fixed sequence traffic signal control strategy. Consequently, traffic congestion in urban areas can be alleviated by adopting ACTAM.

The available bit rate (ABR) is an ATM service category that provides an economical support of connections having vague requirements. An ABR session may specify its peak cell rate (PCR) and minimum cell rate (MCR), and available bandwidth is allocated to competing sessions based on the max-min policy. In this paper, we investigate the ABR traffic control from a different point of view: Based on the decentralized bandwidth allocation model studied in [9], we prove that the max-min rate vector is the equilibrium of a certain system of noncooperative optimizations. This interpretation suggests a new framework for ABR traffic control that allows the max-min optimality to be achieved and maintained by end-systems, and not by network switches. Moreover, in the discussion, we consider the constrained version of max-min fairness and develop an efficient algorithm with theoretical justification to determine the optimal rate vector.