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One of the main approaches for wetlands rehabilitation is improving water management in the agricultural sector and reallocation of stored water to the environmental sector. Due to the over-water harvesting from the Zayandehrud River (mainly for agricultural purposes), the Gavkhuni wetland in central Iran is facing serious water stress. Hence, the aim of this study is to rehabilitate the Gavkhuni wetland by considering the water management scenarios in the agricultural sector. These scenarios are modernization and upgrading the operation of agricultural water distribution systems (A), upgrading in-farm irrigation systems (B), optimizing the cultivation pattern (C) and reducing the utilization of groundwater resources (D), and combining these scenarios together as strategic scenarios to provide ecological water right. In order to evaluate the strategic scenarios for allocating water resources to the wetland, the Zayandehrud basin was simulated using the WEAP model by considering the water resources and uses. For evaluating the presented scenarios based on the sustainable development indicators and due to the uncertainty and intuitive judgment of decision-makers, the fuzzy-CP model was applied. The results showed that water consumption management in the agricultural sector plays a significant role in increasing the inflow to the wetland. This is achieved through the modernization and upgrading of agricultural water distribution systems using two approaches: centralized control (model predictive control) and decentralized control system (proportional-integral), which improve irrigation efficiency by 13.1%, modify cropping patterns by 18.8%, and reduce groundwater extraction by 30%, resulting in a 49.1 and 19.1% increase in inflow to the wetland, respectively. Additionally, the combination of four scenarios indicated a more than 100% increase in the inflow volume to the wetland. The prioritization of scenarios based on a fuzzy agreement multi-criteria decision-making model demonstrated that scenarios ABCD, ACD, and A have a higher priority in increasing the inflow to the wetland compared to other scenarios. [ABSTRACT FROM AUTHOR]

In this contribution, we generalize existing methods for decentralized control design, providing a unified methodological framework that applies to linear continuous and discrete-time complex systems, as well as certain classes of nonlinear complex systems. Our approach leverages the direct connection between the stability properties of the overall complex system and those of its individual subsystems. By conducting the entire controller design process at the subsystem level, we circumvent the need for explicit interconnection values. Through numerical examples, we demonstrate that the proposed method ensures asymptotic stability of the full complex system within a specified region, and also guarantees stability of the isolated subsystems. In particular, we obtain quantifiable stability margins (e.g., γ c bounds) and closed-loop eigenvalue placements that verify the effectiveness of the design. These results highlight not only the method's theoretical robustness, but also its practical significance in simplifying the design process, reducing computational overheads, and enhancing scalability for large and interconnected engineering systems. [ABSTRACT FROM AUTHOR]

Decentralized control systems are frequently employed to tackle control challenges in multi-input multi-output (MIMO) systems. Hence, this paper proposes a decentralized PID controller that relies on frequency domain specifications. This controller is designed to minimize the loop interactions and fulfill the design criteria of the MIMO system. The PID parameters are calculated based on gain and phase margin specifications. Additionally, a first-order plus dead time model is derived for each of the decoupled subsystems. Furthermore, robust stability is analysed using disc margin analysis, which overcomes the constraints of traditional margins. Moreover, the paper determines a secure range of uncertainty for various levels of gain and phase uncertainties. The findings suggest that the proposed controller achieves robust stability over a broader range of margins when compared to alternative control methods. [ABSTRACT FROM AUTHOR]

The development and study of an optimal control method for the problem of controlling the formation of a group of mobile robots is still a current and popular theme of work. However, there are few works that take into account the issues of time synchronization of units in a decentralized group. The motivation for taking up this topic was the possibility of improving the accuracy of the movement of a group of robots by including dynamic time synchronization in the control algorithm. The aim of this work was to develop a two-layer synchronous motion control system for a decentralized group of mobile robots. The system consists of a master layer and a sublayer. The sublayer of the control system performs the task of tracking the reference trajectory using a single robot with a kinematic and dynamic controller. In this layer, the input and output signals are linear and angular velocity. The master layer realizes the maintenance of the desired group formation and synchronization of robots during movement. Consensus tracking and virtual structure algorithms were used to implement this level of control. To verify the correctness of operation and evaluate the quality of control for the proposed proprietary approach, simulation studies were conducted in the MATLAB/Simulink environment, followed by laboratory tests using real robots under ROS. The developed system can successfully find application in transportation and logistics tasks in both civilian and military areas. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for designing a decentralized control law for higher-order systems using the H ∞ complementary sensitivity function (CSF) framework. Higher-order systems often exhibit complex dynamics and interactions between the variables, and hence, sophisticated control strategies are required to attain the desired performance. The proposed method exploits the robustness properties of the H ∞ CSF to achieve effective decentralized control for higher-order systems. The CSF approach focuses on shaping the sensitivity of the system to disturbances, thereby minimizing the impact on system performance. The decentralized nature of the control law allows for independent control of each subsystem, reducing the complexity associated with higher-order systems. Furthermore, the controller parameters are determined graphically by enforcing the H ∞ robust criterion. The effectiveness of the proposed methodology is demonstrated through simulations on higher-order systems from various domains, including process control and other systems. Comparative evaluations against existing control methods highlight the superiority of the H ∞ CSF-based decentralized control law in terms of robustness and performance. [ABSTRACT FROM AUTHOR]

Centralized access control systems are unsuitable for IoT due to their resource-constrained, heterogeneous, and dynamic nature. Blockchain-assisted decentralized access control systems exist for IoT, but those approaches are tokenization-based. In some cases, IoT devices are not part of the blockchain network due to which they cannot interact with the access control system directly. Instead, they need a trusted admin, management hub, or a fog node for permissions verification and access to resources. This paper presents a smart contract and blockchain-assisted framework for the access control systems in the IoT enterprise environment, called ACS-IoT. In the proposed framework, resource-constrained IoT devices belong to the blockchain network. Therefore, these devices can directly access the permitted resources without any centrally administered authority and management hub's verification. We used smart contract and Ethereum blockchain for the new framework. Smart contract allows automated enforcement of access policies and serves as an autonomous agent running exactly as programmed. The proposed framework is validated through implementation of the proof of concept, and implemented prototype is deployed and tested on the Ethereum test network. The obtained results confirm that usage of blockchain and smart contract can be used as access management technology in the IoT enterprise environment. [ABSTRACT FROM AUTHOR]

We address the determination of bitcoin prices and decentralized security. Users forecast the transactional and resale values of holdings, pricing the risk of systemic attacks. Miners contribute resources to protect against attackers and compete for block rewards. Bitcoin's design leads to multiple equilibria: the same blockchain technology is consistent with sharply different price and security levels. Bitcoin's monetary policy can lead to welfare losses and deviations from quantity theory. Price-security feedback amplifies fundamental shocks' volatility impact and leads to boom and busts unconnected to fundamentals. We characterize how viability versus fiat currency depends on bitcoin's relative acceptability and inflation protection. [ABSTRACT FROM AUTHOR]

This paper provided a robust strategy for controlling nonlinear interconnected large-scale systems subject to a sensor fault. The inherent challenge in controlling such systems is to sustain robust closed-loop stability and performance in nonlinear interactions, faults, and exogenous inputs. A new closed-loop structure has been devised to tackle this challenge by integrating the sliding mode controller with the unknown input observer. By exploiting the decoupling capability of the controller and observer, this integration ensures the robustness of the closed-loop system against the simultaneous effect of interaction, fault, and disturbance. In this context, the unknown input observer has been constructed to supply the controller with an accurate sensor fault assessment despite additional unknown inputs. A novel approach is proposed for designing a decentralized fault-tolerant control system that utilizes sliding mode control and proportional-integral-derivative controller tuning via a bacterial foraging optimization algorithm to compensate for the fault effect, leading to a robust output performance. The observer and controller gains are accomplished by utilizing the H∞ performance and linear matrix inequality formulation. The Lyapunov technique is used to demonstrate stability. A power system model emphasizes the proposed approach's robustness and effectiveness. The system performance with and without the proposed controller was compared, where the simulation results show a fast reaction to offset undesirable impacts, whereas the state estimation error approaches to zero in each subsystem. [ABSTRACT FROM AUTHOR]

The article delves into the intricate legal complexities surrounding the perfection of security interests in digital assets, with a particular emphasis on cryptocurrency, amidst the rapid advancement of emerging technologies. It explores the challenges faced by lenders in perfecting security interests against intangible digital assets like cryptocurrency, which lack physical presence and are governed by decentralized systems.

Architecting a self-adaptive system with decentralized control is challenging. Indeed, architects shall consider several different and interdependent design dimensions and devise multiple control loops to coordinate and timely perform the correct adaptations. To support this task, we propose Decor, a reasoning framework for architecting and evaluating decentralized control. Decor provides (i) multi-paradigm modeling support, (ii) a modeling environment for MAPE-K style decentralized control, and (iii) a co-simulation environment for simulating the decentralized control together with the managed system and estimating the quality attributes of interest. We apply the Decor in three case studies: an intelligent transportation system, a smart power grid, and a cloud computing application. The studies demonstrate the framework's capabilities to support informed architectural decisions on decentralized control and adaptation strategies. [ABSTRACT FROM AUTHOR]

Despite the lack of blockchain systems being utilized in modern IoT environments, the prevalence of blockchain technology is increasing, due to its high level of security and accountability. The integration of blockchain technology and access control in a decentralized system for smart home networks is a promising solution to this issue. This paper compares the implementation of attribute-based access control (ABAC) with two popular blockchain platforms, Ethereum and Hyperledger Fabric, for a smart home internet of things (IoT) environment. We present a comprehensive summary of access-control and blockchain-access-control methods, to provide the necessary background for this study. Additionally, we present an original ABAC smart contract for Ethereum, and the modification of a pre-existing Hyperledger Fabric ABAC smart contract, for this comparison. Through the simulation of both implementations, the advantages and limitations will be considered, to determine which is better suited for a smart home IoT environment. [ABSTRACT FROM AUTHOR]

In order to effectively improve the path‐finding capability of a multirobot system in a decentralized control approach, a dynamic motion planning model based on graph neural networks and historical information (GNNHIM) is proposed. Due to the limited sensing range of the robot's onboard sensors, GNNHIM uses convolutional neural networks to extract features from the heterogeneous environmental information collected and analyzes the motion trends of other robots in conjunction with the historical path information stored locally. After finishing feature fusion, each robot exchanges its feature vectors with other robots still within sensing range to obtain the next action by the graph neural network model processing. Herein, imitation learning is used to train robots to choose behavioral strategies to maximize team benefit. The experimental results show that GNNHIM can make path planning for multirobot systems more efficient and reliable, enabling all robots to reach their own goal within a limited time in 95.1% of the experimental dataset. Moreover, GNNHIM still has great generalization when applied to unseen scenarios and larger scale robot systems. GNNHIM in unseen scenarios has improved the success rate by 6%‐34% and reduced the detour percentage by 3.8% on average compared to the other scheduling model. [ABSTRACT FROM AUTHOR]

An important legacy of Nathan Rosenberg's work is the notion of general purpose technologies (GPTs). This paper studies whether and when firms specialize in developing GPTs and trading them in intermediate markets, a strategy we call "specialization in generality." In particular, we address whether and under what contingencies this is a long-term strategy adopted by firms as they age—against the "common wisdom" that aging firms specialize in downstream product markets. [ABSTRACT FROM AUTHOR]

In recent years, low-voltage direct current (LVDC) microgrids are becoming more attractive because they represent a solution to integrate renewable sources, storage, and electronic loads bringing some advantages in comparison with traditional AC grids. However, the protection of such a network involves many challenges, especially in the case of LVDC microgrids with more than one feeder and multiple energy sources. Indeed, the traditional protection breakers used for an AC grid cannot isolate the faults and protect the components of a DC grid, while the use of solid-state circuit breakers increases energy losses. This paper deals with the analysis and design of the protection schemes for LVDC microgrids through the combination of mechanical circuit breakers and hybrid circuit breakers. This solution has the advantage of energy loss reduction but introduces further issues due to the slow transition times of the mechanical circuit breakers. Thus, a completely decentralized control system capable of overcoming the fast fault-clearing time, cost-effectiveness, and selectivity issues is designed to protect from pole-to-pole faults. The proposed control strategy is compared with a centralized protection scheme available in the literature through numerical simulation. The two algorithms show similar performances, with a mean voltage dip duration of less than 30 ms and a maximum voltage dip duration of about 100 ms in the most severe fault condition, but the proposed solution is more reliable and flexible since it does not depend on the communication system. [ABSTRACT FROM AUTHOR]

Due to the difficulty in adopting the conventional centralized control method for seismic response control of high-rise buildings with complex structures and large sizes, the decentralized control method is applied. The challenge is that the control model of the high-rise structure divided into multiple subsystems changes as large nonlinear deformation under strong earthquakes. Therefore, with an application of the long short-term memory neural network, the long short-term memory intelligent decentralized control method is proposed for seismic response control of high-rise buildings. On the basis of the decentralized control theory for high-rise buildings, a long short-term memory network deep-learning framework is established to construct different types of decentralized controllers, and to determine the sufficient conditions for the stability of the decentralized controllers using the Lyapunov stability theory. The long short-term memory intelligent decentralized control system of a 20-story benchmark building mode is simulated, and its fault tolerance is studied. The simulation results show that the decentralized control method can reduce the complexity of the structure model by dividing the high-rise building structure into multiple subsystems. Compared with the centralized control method, the long short-term memory intelligent decentralized control method can effectively avoid the overall failure of the control system. The long short-term memory intelligent decentralized control method can still have a satisfactory performance under sensor noise and control devices failures. This verifies that the long short-term memory intelligent decentralized control system has a better fault tolerance and can provide an innovative solution for the decentralized control of high-rise buildings. [ABSTRACT FROM AUTHOR]

Here, a new energy management strategy based on a multi‐agent structure is presented by introducing hybrid control of AC micro‐grid (MG), where current harmonics compensation is also considered. This energy management strategy is based on Mealy machine in a multi‐agent system (MAS), which is implemented by generating coordination signals and sending them to the renewable energy sources (RES). In RES, maximum power point tracking (MPPT) or reverse of Hill‐climbing (RHC) is used based on these received coordination signals to limit the exchange power between the MG and the grid. Also, the multi‐agent structure of shunt active power filters (SAPFs) and passive filters have been studied in power MGs. The comparison of MG current harmonic compensation by these filters by fast Fourier transform (FFT) algorithm has been investigated in the proposed network. The simulation results show that the proposed energy management system (EMS) with proper management of MG different agents has been able to have a suitable performance for hybrid distributed generation (DG) systems. Also, the SAPF with better and more appropriate harmonic compensation than the SC‐RC‐LCL passive filter can eliminate the harmonic pollution of MG and be used with high performance in hybrid DG systems. [ABSTRACT FROM AUTHOR]

Control of large-scale networks can be challenging due to difficulties in implementation of high-order control systems, data collection, and actuation. Distributed and decentralized control systems are therefore commonly used. This paper proposes an optimization-based partitioning approach for use in decentralized and distributed control. It factors in both computational and communication costs, while also taking into consideration the controllability of the subsystems. An efficient algorithm for solving the optimization problem is also provided. The proposed approach is demonstrated on case studies from water distribution systems. • A new optimization-based formulation of the network partitioning problem. • Considering the number of partitions as one of the decision variables. • The use of controllability of subsystems as a constraint in the partitioning algorithm. • An algorithm for solving the partitioning problem. [ABSTRACT FROM AUTHOR]

The article focuses on the intricate relationship between Franz Kafka's works and French theorists in the 20th century, examining the multifaceted interactions that have significantly shaped Kafka's reception in France. Topics include the translation and contextualization of Kafka's writings, ideological battles among Marxist intellectuals, and the poststructuralist and psychoanalytic readings that reconfigured the understanding of Kafka in a decentralized, labyrinthine manner.

In many structures, undesired noise and vibrations generated by external sources represent a huge problem in terms of structural damage and comfort. Active vibration absorbers can be used to dynamically suppress vibrations, by increasing the damping of the system. A wireless smart active damper has been developed to perform this task and some automated functionalities have been implemented to perform the identification of the structure on which it is mounted on. The sharing of information between wireless sensors represents one of the most interesting features of this kind of control system. In this work, a procedure to estimate the nondimensional damping and modal amplitude for each wireless sensor location and each vibration mode is studied. Then, the information obtained by each sensor in the identification phase are used to implement a coordinated control strategy, which is based on a modified version of the Efficient Modal Control (EMC). Such control strategy implements the low level Selective Negative Derivative Feedback control law and modulates the control gains of each actuator and controlled mode pair in order to get an effective vibration reduction. The tuning procedure represents the next step of the algorithm, in which the evaluation of the introduced damping and the maximum applicable gains are derived; finally, the proposed solution is validated with experimental results on a simply-supported beam. [ABSTRACT FROM AUTHOR]

Mineral processing plants remain nowadays infamous for their low energy efficiency. Economic model predictive control (EMPC), by directly considering the energy costs, could possibly help reduce their footprint, but its environmental benefits are yet to be clearly quantified. In an attempt to cast some light on this topic, this paper compares the response to a given ore feed size and hardness disturbance sequence of an EMPC to that of basic and advanced regulatory control systems using the profits and the specific energy (power draw/ore feed rate) as metrics. The simulated circuit comprises a high-pressure grinding rolls (HPGR), a ball mill, and a flotation circuit. It is based on population balance modeling and is an extension of previous works. The basic regulatory control (BRC) system comprises only single-input–single-output control loops with proportional–integral (PI) controllers and operates at a fixed feed rate. The advanced regulatory control (ARC) system consists of PI controllers maximizing the plant feed rate with override constraint handling. The results show that (1) ARC generates more revenue and maintains a lower circuit specific energy consumption than BRC, (2) ARC can produce the same economic performance as EMPC because the constraints of the system define the economic optimum, and (3) EMPC can trade revenues for a lower circuit specific energy with a hybrid criterion that penalizes power draw. • The work compares different control systems on an HPGR grinding circuit. • A decentralized PI control system can generate equivalent revenues to an EMPC. • EMPC can trade revenues for a lower circuit specific energy. [ABSTRACT FROM AUTHOR]

This current work proposes a refined investigation on the improved sequential relay autotuning method to compute the optimal parameters of the decentralized PI controller for Two Input Two Output (TITO) system using relay feedback method. The sustained oscillation occurring in the relay response with the sequential relay autotuning and the simultaneous relay autotuning method is analyzed by taking the higher-order harmonics into consideration and the efficient performance results of the decentralized PI control systems are obtained. These methods have been applied to an Industrial-Scale Polymerization (ISP) reactor transfer function model. In closed-loop studies, comparative analysis of autotuning methods has been carried out using simulation. The effect of measurement noise and robustness are studied in the proposed work. The robustness performance of the system using improved sequential relay autotuning is enhanced by 5–25% for servo operation and 11–40% for regulatory operation. The performance of the systems with the effect of measurement noise using improved sequential relay autotuning is enhanced by 2–24% for servo operation. Comparative analysis has been carried out with the improved sequential relay autotuning and the simultaneous relay autotuning method. It is observed that the proposed method provides improved closed-loop performances and less sum of Integral square error even in presence of robustness and effect of measurement noise. [ABSTRACT FROM AUTHOR]

The overlapping decentralized control strategy is a solution to the decentralized control of large-scale systems based on the inclusion principle. Its design process can be summarized as three stages of expansion-decoupling-contraction. In this paper, the subsystem division scheme of the overlapping decentralized control strategy is studied for building structure systems under earthquake. Using the energy-to-peak algorithm, we mainly analyse the influences of the location of the overlapping layer, the number of overlapping layers and the number of subsystems on the control effect of the structural system, and compare them with the traditional energy-to-peak centralized control method. The numerical results indicate that the dynamic response of the structure can be effectively suppressed by raising the location of the overlapping layer, increasing the number of overlapping layers, and increasing the number of subsystems. Compared with the centralized control strategy, the control effect is equivalent, or even better, verifying the feasibility of this research scheme. [ABSTRACT FROM AUTHOR]

In this article, the dynamic event‐triggered decentralized control (DETDC) problem is investigated for a class of interconnected systems. In order to reduce the communication frequency between the interconnected subsystem and local controller, we first design a dynamic event‐triggered mechanism (ETM) for each interconnected subsystem, which can effectively reduce the communication frequency compared with static ETM. Hereafter, under the proposed dynamic event‐triggered strategy, the local dynamic event‐triggered controller is developed, which only uses the state information of the corresponding interconnected subsystem. Furthermore, it is proven that the interconnected system is asymptotically stable under the proposed DETDC scheme. Moreover, the trigger interval is proven to be strictly positive, which means that Zeno behavior is avoided. Finally, a multi‐machine power system is provided to demonstrate the effectiveness of the proposed DETDC scheme. [ABSTRACT FROM AUTHOR]

The paper aims to develop a new method for the design of hybrid multivariable automatic control systems. We determine a hybrid control system as a system that includes two different types of parallel operating controllers. The paper's aim is achieved by solving the following tasks. The first task is to develop a method for the design of hybrid control systems. Investigated systems include PI controllers and a linear-quadratic controller. The second task is to investigate the resulting control system. The investigation is based on direct quality indicators, robustness, and fragility analyses. The most significant result of the paper is the development of a method for the tuning of a linear-quadratic controller, which should work with the decentralized control system in parallel. BLT (Biggest Log Modulus) method is used for decentralized control system tuning. BLT is a well-known method of PI controller detuning. The idea of BLT is to ensure the robustness of multivariable control systems tuned by Ziegler Nichols's rules. The proposed method for the design of the control system is not complicated. The possibility of correcting the tunings of decentralized controllers remains. Design of the new hybrid automatic control system for the distillation plant made using the developed method. The analysis of the dynamic properties of the designed control system showed that the use of a parallel linear-quadratic controller provides a small percentage of overshoot in the control by the reference and high accuracy of stabilizing the values of controlled variables at the largest disturbances. At the same time, the robustness does not decrease and the control system remains fragile, i.e., it is possible to change the settings of the controllers without significant loss of robustness. [ABSTRACT FROM AUTHOR]

Decentralized social networks like Mastodon and BlueSky are trending topics that have drawn much attention and discussion in recent years. By devolving powers from the central node to the end users, decentralized social networks aim to cure existing pathologies on the centralized platforms and have been viewed by many as the future of the Internet. This article critically and systematically assesses the decentralization project's prospect for communications online. It uses normative theories of free speech to examine whether and how the decentralization design could facilitate users' freedom of expression online. The analysis shows that both promises and pitfalls exist, highlighting the importance of value-based design in this area. Two most salient issues for the design of the decentralized networks are: how to balance the decentralization ideal with constant needs of centralization on the network, and how to empower users to make them truly capable of exercising their control. The article then uses some design examples, such as the shared blocklist and the opt-in search function, to illustrate the value considerations underlying the design choices. Some tentative proposals for law and policy interventions are offered to better facilitate the design of the new network. Rather than providing clear answers, the article seeks to map the value implications of the design choices, highlight the stakes, and point directions for future research. [ABSTRACT FROM AUTHOR]

Decentralized stochastic control problems with local information involve problems where multiple agents and subsystems which are coupled via dynamics and/or cost are present. Typically, however, the dynamics of such couplings is complex and difficult to precisely model, leading to questions on robustness in control design. Additionally, when such a coupling can be modeled, the problem arrived at is typically challenging and non-convex, due to decentralization of information. In this paper, we develop a robustness framework for optimal decentralized control of interacting agents, where we show that a decentralized control problem with interacting agents can be robustly designed by considering a risk-sensitive version of non-interacting agents/particles. This leads to a tractable robust formulation where we give a bound on the value of the cost function in terms of the risk-sensitive cost function for the non-interacting case plus a term involving the "strength" of the interaction as measured by relative entropy. We will build on Gaussian measure theory and an associated variational equality. A particular application includes mean-field models consisting of (a generally large number of) interacting agents which are often hard to solve for the case with small or moderate numbers of agents, leading to an interest in effective approximations and robustness. By adapting a risk-sensitivity parameter, we also robustly control a non-symmetrically interacting problem with mean-field cost by one which is symmetric with a risk-sensitive criterion, and in the limit of small interactions, show the stability of optimal solutions to perturbations. [ABSTRACT FROM AUTHOR]

In this article, the stability analysis problem of networked linear systems with decentralized sampled‐data controllers is considered. The networks under consideration are composed of interconnected identical systems. A dissipativity‐based approach is utilized to analyze stability, grounded in an interconnection interpretation. A structure exploiting and scalable approach is employed to derive a sufficient stability condition for large‐scale linear systems, which is independent of the number of subsystems. In the analysis, the effects of uncertainty on the system models, which include uncertainties that render the coupled systems nonidentical, aperiodic sampling, and a switching network topology, are taken into account. Numerical examples are presented to demonstrate the main result and simulate the sampled‐data system. [ABSTRACT FROM AUTHOR]

In this article, we develop synthesis methods for decentralized control of switched systems with mode-dependent (more generally, path-dependent) performance specifications and apply them to an experimental vehicular testbed. This specification flexibility is important when achievable system performance varies greatly between modes, as a mode-independent specification will lead to designs that do not extract all the system performance available in each mode. More specifically, under these specifications, we derive exact conditions for the existence of block lower triangular path-dependent controllers with $\ell _{2}$ -induced-norm performance. The synthesis conditions are given in the form of a semidefinite program (SDP) for both uniform and path-dependent performance bounds. Building on previous results, we also introduce a basis-based approach that allows computational complexity to be more carefully controlled. We apply the resulting design methods to a group of miniature quadcopters, illustrating different features of the presented methods, along with some practical engineering considerations. [ABSTRACT FROM AUTHOR]

In this paper, the decentralized learning scheme for nonlinear systems with mismatched interconnections is developed by using the off-policy integral reinforcement leaning algorithm. First, the decentralized control of the overall system is transformed into the optimal control of each subsystem by introducing an auxiliary control. In order to relax the knowledge of system dynamics, a model-free policy iteration algorithm is derived based on the off-policy integral reinforcement learning. Then, the model-free policy iteration algorithm is used to solve the related Hamilton–Jacobi-Bellman equations, where only the collected system data is required. For implementation purpose, neural networks are employed to approximate the optimal cost functions and the optimal control policies, respectively. Moreover, the least squares method and the experience replay technique are combined to learn neural network weights. Finally, a mismatched interconnected system and a photovoltaic power system are presented to verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

We study a decentralized admission control problem with capacity borrowing. In this problem, the admission decision is made by each server who is assigned dedicated capacity. However, a server can borrow capacity from other servers if his dedicated capacity is exhausted. The borrower compensates the lender by a payment equal to the "borrowing cost." Hence, the servers share their capacities via borrowing, but they also compete against each other for their pooled capacities. We formulate this problem as a stochastic dynamic game and characterize the equilibrium strategic admission behavior of servers. We show that the critical factors that affect the equilibrium behavior and the system revenue are the magnitude of the borrowing cost, the arrival rate of customers and the revenue difference between different classes of customers. We have identified conditions under which servers maximizing their own payoffs end up making decisions that benefit the system. Our study highlights the important roles that the borrowing cost plays in shaping servers' behavior in service systems and provides concrete guidance for practitioners to design a decentralized admission control system. [ABSTRACT FROM AUTHOR]

We describe a method for decentralized control of route-based material handling systems in which devices have no central controller (by definition), no common source of information, and no synchronized or common clocks with which to plan and execute their activities. The control scheme is based on the concept of logical time, which is a means of partially ordering events in computer operating systems. We modify the concept to the domain of material handling systems and prove system liveness. We conclude by describing GridSorter, a conveyance-based sorter that uses decentralized control and logical time to sort packages. A prototype has been successfully built and tested at the Institute for Material Handling and Logistics, Karlsruhe Institute of Technology. Note to Practitioners—Decentralized control is a means of distributing the control of a complex system away from a central computing source toward individual devices and subsystems. In material handling, complex systems can malfunction due to deadlock, livelock, or starvation. This article presents a new method for controlling decentralized material handling systems based on logical time, a method from computer operating systems describing a sequence of activities at each resource. We modify logical time for material handling and show that the system is deadlock-free, thus giving engineers an easy-to-implement method of controlling route-based material handling systems such as automated guided vehicles (AGVs) or conveyors. [ABSTRACT FROM AUTHOR]

This paper aims at modelling decentralised planning at the tactical level, with minimal-information sharing coordination, in a 2-echelon supply chain with multiple actors at each echelon. Suppliers manage production and storage at the upstream echelon, while retailers manage transportation and storage at the downstream echelon. The main features of the planning process are (1) decentralisation and coordination using contracts and sharing of only order/supply proposals, and (2) iteration on a rolling horizon. Actor planning is modelled as a capacitated lot-sizing problem on a finite horizon, with the focus on quality of service. The objective is to minimise costs, with a high lost sales penalty if demand is not met. Two other decision problems are pointed out and modelled with Mixed Integer Programming: (1) lost sales allocation between the retailers when their demands cannot be satisfied; and (2) allocation of orders between the suppliers. A multi-agent system combines simulation of the planning process and optimisation of the local decision processes. Several strategies, including retailers’ beliefs about suppliers’ production capacity are proposed and experimentally tested, with two patterns of production capacities. The results compare the proposed allocation strategies and highlight the relevance of the proposed framework for the studied planning problem. [ABSTRACT FROM PUBLISHER]

This paper presents an optimal decentralized control system for an isolated, networked dc microgrid with multiple sources and composite loads. The key feature of the proposed controller is that it requires only locally measurable states for controlling the local generation while achieving global stability. The controller is designed to minimize a performance index accounting for voltage regulation and branch current regulation with improved dynamics and stability. Decentralized control guarantees high reliability and modularity of the microgrid enabling plug-and-play operations of new units with little modifications. The solution of optimal decentralized control is obtained through constrained parameter optimization technique. The designed controller ensures stability over extended operating conditions of load and droop changes. This leads to a unique robust control law for the dc microgrid that obviates the need for frequent change of controller settings for any change in system parameters. Modal analysis and time-domain simulation of the controlled system substantiate robustness and effectiveness of the proposed decentralized control system in improving the system dynamic performance and optimal set point tracking with a unique controller configuration. [ABSTRACT FROM AUTHOR]

This article examines a decentralized event‐triggered robust model predictive control (MPC) for a class of networked large‐scale non‐linear Lipchitz systems. It is assumed that the subsystems are geographically distributed and the connections can be made over a communication network and therefore local event generator modules are used. An event‐triggering condition is then proposed for each module, which only uses local information to trigger data via the communication channel. In this way, the information exchange between subsystems can be reduced significantly compared to time‐triggered conventional control approaches, while the asymptotic stability of the closed‐loop is maintained. In contrast to the reported event‐triggered MPC results, the optimized controller is calculated based on state feedback control law for individual subsystems, which minimizes the upper limit on the infinite horizon cost function subject to constraints on the control inputs. The validness of the proposed scheme is demonstrated by simulation results. [ABSTRACT FROM AUTHOR]

The emergence of the graphon theory of large networks and their infinite limits has enabled the formulation of a theory of the centralized control of dynamical systems distributed on asymptotically infinite networks. Furthermore, the study of the decentralized control of such systems has been initiated in which graphon mean field games (GMFG) and the GMFG equations have been formulated for the analysis of noncooperative dynamic games on unbounded networks; in that work, existence and uniqueness results have been introduced for the GMFG equations, together with an ∈-Nash theory for GMFG systems which relates infinite population equilibria on infinite networks to finite population equilibria on finite networks. Those results are rigorously established in this paper. [ABSTRACT FROM AUTHOR]

In the era of automatic task processing or designing complex algorithms, to analyse data, it is always pertinent to find real‐life solutions using cutting‐edge tools and techniques to generate insights into the data. The data‐driven machine learning models are now offering more or less worthy results when they are certainly balanced in the input data sets. Imbalanced data occurs when an unequal distribution of classes occurs in the input datasets. Building a predictive model on the imbalanced data set would cause a model that appears to yield high accuracy but does not generalize well to the new data in the minority class. Now the time has come to look into the datasets which are not so‐called 'balanced' in nature but such datasets are generally encountered frequently in a workspace. To prevent creating models with false levels of accuracy, the imbalanced data should be rearranged before creating a predictive model. Those data are, sometimes, voluminous, heterogeneous and complex in nature and generate from different autonomous sources with distributed and decentralized control. The driving force is to efficiently handle these data sets using latest tools and techniques for research and commercial insights. The present article provides different such tools and techniques, in different computing frameworks, to handle such Internet of Things and other related datasets to review common techniques for handling imbalanced data in data ecosystems and offers a comparative data modelling framework in Keras for balanced and imbalanced datasets. [ABSTRACT FROM AUTHOR]

In this paper, we propose the development of a new strategy for the synthesis of a decentralized robust control for multiple-input–multiple-output (MIMO) nonlinear systems. The proposed method takes into account system's loop interactions to synthesize a MIMO robust control stabilizing the system facing parametric uncertainties. The use of RGA theory is proposed to define the structure of the robust controller, synthesized by the loop shaping design procedure (LSDP), with the most effective input/output pairing. Then, an extension of an existing transition technique to the nonlinear multivariable case is proposed to decide the equilibrium points. The transition from an equilibrium point to another is ensured by the variation in the scheduling parameter (SP) while monitoring the variation in the gap metric compared to the maximum stability margin of the LSDP. We note that the new developed transition approach exploits during its execution the RGA theory whose purpose is to impose a common input/output pairing. Furthermore, for each equilibrium point a local full-order robust controller is obtained based on the LSDP approach, whose configuration is simplified also by exploiting RGA theory by proposing a selection matrix to deduce a local final robust controller. In this case, the overall decentralized robust control system is obtained by switching between local final robust controllers, where the maximum stability margin is used as an indicator of robustness in terms of stability and precision against parametric uncertainties. The proposed algorithm, for the synthesis of the decentralized robust multivariable control of uncertain nonlinear MIMO systems, is validated for the regulation of a benchmark of type continuous stirred tank reactor in the presence of parametric uncertainties. Moreover, the efficiency of the proposed decentralized robust control is validated on an experimental communicating two tank system. [ABSTRACT FROM AUTHOR]

The problem of distillation columns control systems design is actual for many years. When solving the problem of automatic control systems design for distillation columns, the problem of cross-coupling is always relevant. This problem becomes only more severe with increasing the distillation column structure complexity. The column complexity is connected, for example, with number of components, number of additional thermal flows, usage of the built-in column reactor, etc. Standard approach for design of distillation columns automatic control systems is to develop control systems of decentralized structure. Such systems contain autonomous SISO controllers. These can be both controllers, developed within the framework of classical control theory and controllers of other types (adaptive, fuzzy, nonlinear, etc.), assuming that they are SISO. The problem of selecting control pairings (configuration selection) is important within the framework of the decentralized approach for control system design. From the solution of this problem depends the stability of the control system as a whole, its quality indicators and potential compliance with the technological production operating protocol. Methods of choosing the decentralized control system configuration on the basis of distillation columns steady state and dynamics models are considered. Advantages and disadvantages of configuration choosing methods such as RGA, RIA, ERGA, RRA are considered. The features and limitations of each method is shown on the examples of distillation columns models. Additionally, attention is drawn to the methods of selecting a configuration that is resistant to disconnection of individual controllers. The method of calculation of the Niederlinski NI index and the LII index is considered. The application of PRGA matrices for complex plants and the calculation of the ICI integration on PRGA basis are presented on an example. [ABSTRACT FROM AUTHOR]