Intelligent Distributed Control Research Articles

Enhancing microgrid performance with AI‐based predictive control: Establishing an intelligent distributed control system

Enhancing microgrid performance with AI‐based predictive control: Establishing an intelligent distributed control system

Neural network-based distributed intelligent supervisory control for multi-agent systems with unknown input powers

In this paper, a synchronisation problem is studied for a class of nonlinear leader-following systems. Based on adaptive control with some algebra lemmas, we propose a distributed control scheme. This scheme ensures each follower to asymptotically synchronise with the leader. Compared with the existing works where system input powers are assumed one, the input powers considered in this paper are unknown but larger than one. Based on Graph theory, Lyapunov theory and radial basis function (RBF) networks, we design a distributed adaptive supervisory control method. It is proven that the consensus among the leader and followers are achieved and all the signals including tracking errors asymptotically converge to a small neighbourhood of the origin. Finally, simulation results are displayed to demonstrate the effectiveness of control scheme.

A Fairness-Enhanced Intelligent MAC Scheme Using Q-Learning-Based Bidirectional Backoff for Distributed Vehicular Communication Networks

With the increasing attention to front-edge vehicular communication applications, distributed resource allocation is beneficial to the direct communications between vehicle nodes. However, in highly dynamic distributed vehicular networks, quality of service (QoS) of the systems would degrade dramatically because of serious packet collisions in the absence of sufficient link knowledge. Focusing on the fairness optimization, a Q-learning-based collision avoidance (QCA) scheme, which is characterized by an ingenious bidirectional backoff reward model R <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">QCA</inf> corresponding to arbitrary backoff stage transitions, has been proposed in an intelligent distributed media access control protocol. In QCA, an intelligent bidirectional backoff agent based on the Markov decision process model can actively motivate each vehicle agent to update itself toward an optimal backoff sub-intervel BSI <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">opt</inf> through either positive or negative bidirectional transition individually, resulting in the distinct fair communication with a proper balance of the resource allocation. According to the reinforcement learning theory, the problem of goodness evaluation on the backoff stage self-selection policy is equal to the problem of maximizing Q function of the vehicle in the current environment. The final decision on BSI <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">opt</inf> related to an optimal contention window range was solved through maximizing the Q value or <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$Q_{\max}$</tex> . The ε-qreedy algorithm was used to keep a reasonable convergence of the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$Q_{\max}$</tex> solution. For the fairness evaluation of QCA, four kinds of dynamic impacts on the vehicular networks were investigated: mobility, density, payload size, and data rate with a network simulator NS2. Consequently, QCA can achieve fair communication efficiently and robustly, with advantages of superior Jain's fairness index, relatively high packet delivery ratio, and low time delay.

Distributed topology identification algorithm of distribution network based on neighboring interaction

Intelligent distributed control and protection is a promising route towards flexible and safety operation of distribution network with widespread access of distributed energy resources A fundamental premise of the distributed decision-making is that each smart terminal can identify the topological structure of the feeder and track its changes. This paper proposes a distributed topology identification algorithm with high fault tolerance based on peer-to-peer communication. The smart terminal units (STU) installed on the nodes can dynamiclly track and identify the network topology through local measurement and information exchange with neighboring STUs. The proposed algorithm combines local measurement mutual check with contralateral connectivity predictive correction, and significantly improves the tolerance of measurement errors in topology identification. Test examples are presented to verify the effectiveness of the method.

Application of deep reinforcement learning to intelligent distributed humidity control system

Application of deep reinforcement learning to intelligent distributed humidity control system

FogChain: A Blockchain-Based Peer-to-Peer Solar Power Trading System Powered by Fog AI

Microgrids, gaining traction from rising distributed generation for carbon reduction, demand novel solutions to regulate on- and off-grid operations, as well as both energy and monetary transfers between the microgrid and the central grid and among different microgrid participants. This research aims to develop and validate an intelligent microgrid management system to secure the competitiveness of Singapore’s energy market, by leveraging the inherent synergy between two emerging technologies, i.e., blockchain for Peer-to-Peer (P2P) solar power trading and fog computing for grid infrastructure management. For this vision, we have developed FogChain, an integrative, cost-effective, and scalable microgrid operating system (MGOS), consisting of three technical service layers: 1) a novel microgrid information infrastructure based on the fog-computing paradigm (i.e., intelligence on edge); 2) a blockchain-based microgrid service layer, providing smart contract and decentralized control capabilities for grid application development; and 3) a microgrid application layer (i.e., P2P energy trading) over the blockchain-based grid service. This MGOS would fundamentally transform how solar power is traded among participating electricity prosumers, leading to potentially new operational and business models. We have implemented the FogChain system and conducted extensive experiments to verify its performance advantages. Our results demonstrate that FogChain can efficiently process energy auction among 1000 participants with 1.1 s delay on average, reduce transmission cost up to 20% under the loss-aware trading mechanism, and reduce the solar yield prediction error to 0.11. Our system prototype suggests that FogChain provides a promising solution for efficient decentralized energy trading and intelligent distributed control for microgrids.

Research on Ship Fire Monitoring and Alarm System

This paper analyzed the application status of land fire protection system and the characteristics of ship fire protection, and analyzed the functional requirements of ship fire protection system according to the ship special environment with crowded escape routes and complex structure. Using distributed intelligent control mode and modular structure design, a monitoring and alarm system composed of sensor acquisition module, microprocessor, central server, audible and visual alarm module, liquid crystal display module and CAN bus communication is constructed. The designed system has simple structure, stable performance and high cost performance, and has certain application and promotion value.

Topology Identification Method of Urban Power Grid Based on 5G Communication

With the development of 5G communication technology and intelligent terminal technology of urban power grid, intelligent distributed control mode independent of master station will become the trend of intelligent distribution network in the future. The characteristics of flexible configuration and strong scalability make 5G communication technology provide a wireless solution, which greatly gets rid of the constraints of communication cables and promotes the popularization and application of intelligent distributed control technology. Based on 5G communication technology, this paper proposes a distributed topology identification method. In this solution, each Smart Terminal Unit (STU) only needs to configure its associated static network topology information, and each STU forms dynamic network topology information according to certain topology identification rules. The purpose of identifying topological information is to use the information to provide topological information support for advanced functions of the distribution network, such as reclosing, identification of distributed power islands, and restoration of non-faulty section power supply.

Convergence and Interoperability for the Energy Internet: From Ubiquitous Connection to Distributed Automation

The Energy Internet is proposed to enhance the collaborative utilization of distributed renewable energy resources; enable a flexible, customer-engaged energy transaction network; and achieve real-time balancing of supply and demand. This allows integrating advanced Internet of Things (IoT)-based architectures, information and communications technology (ICT)-based end-to-end digital energy chains; customer-centric energy efficiency programs; energy-aware, realtime platforms; and intelligent distributed control algorithms.

A biologically-inspired reinforcement learning based intelligent distributed flocking control for Multi-Agent Systems in presence of uncertain system and dynamic environment

In this paper, we investigate the real-time flocking control of Multi-Agent Systems (MAS) in the presence of system uncertainties and dynamic environment. To handle the impacts from system uncertainties and dynamic environment, a novel reinforcement learning technique, which is appropriate for real-time implementation, has been integrated with multi-agent flocking control in this paper. The Brain Emotional Learning Based Intelligent Controller (BELBIC) is a biologically-inspired reinforcement learning-based controller relying on a computational model of emotional learning in the mammalian limbic system. The learning capabilities, multi-objective properties, and low computational complexity of BELBIC make it a very promising learning technique for implementation in real-time applications. Firstly, a novel brain emotional learning-based flocking control structure is proposed. Then, the real-time update laws are developed to tune the emotional signals based on real-time operational data. It is important to note that this data-driven reinforcement learning approach relaxes the requirement for system dynamics and effectively handle the uncertain impacts of the environment. Using the tuned emotional signals, the optimal flocking control can be obtained. The Lyapunov analysis has been used to prove the convergence of the proposed design. The effectiveness of the proposed design is also demonstrated through numerical and experimental results based on the coordination of multiple Unmanned Aerial Vehicles (UAVs).

Research on multi-agent control system for concrete distribution

A concrete distributor is the key equipment in the production of precast concrete, abbreviated PC, components. Due to the lack of the automatic and intelligent distribution control system for the most domestic concrete distributor, the quality index is poor and the efficiency is low in the concrete distributing process. In order to solve the above problem, the method of constructing a control system is proposed in this paper. This method is based on the theory of multi-agent and the production technology of PC components. The model structure of complex control systems of multi-agent is studied, and the partition mechanism and coordination mechanism of multi-agent for concrete distribution are analysed. Then, the new model of a multi-agent control system for concrete distribution is designed, and the simulation platform of the system is built. The model of the multi-agent control system for concrete distribution designed is beneficial to theory research in the process control of concrete distribution and its application in the field bus control system. Therefore, the foundation for realizing the automation and intelligence of production in concrete distributing is established.

Distributed multi‐agent control for combined AC/DC grids with wind power plant clusters

The combined AC/DC grids have, due to their technological features of high voltage and large capacity as well as operating flexibility and reliability, become one of the most potential solutions to connect large-scale wind farms to power systems. The traditional centralised control lacks flexibility and robustness. In contrast, the distributed control is unable to simultaneously consider global optimum and response speed. A scheme of intelligent distributed control for combined AC/DC grids is proposed to constitute a multi-agent system by equipping each terminal with an agent. While adopting the proposed control method, the optimisation of the upper layer is similar to the traditional grid dispatch and the lower layer system achieves the group compromise through the interaction and coordination among the agents and between the agents and the system. Based on the state information such as the voltage and the frequency of the neighbouring converter stations, the combined AC/DC grids can allocate the active power reasonably through the consistency control and provide the frequency support of the AC grid. Finally, four operating scenarios, including wind speed jump, wind power plant cluster disconnection, converter station failure and load demand response, are verified in a typical model of combined AC/DC grids by using the PSCAD/EMTDC software.

IMPLEMENTATION AND TUNING OF A FUZZY-PID CONTROL SYSTEM VIA FIELDBUS COMMUNICATION

In research applications is very important to have a flexible automation structure for different plant conditions with a large flow of information. To satisfy real-time requirements a communication technique based in fieldbus network was used to interconnect devices in an intelligent distributed control system. Using this structure, an experimental tuning for fuzzy-PID controller based in scaling gains from a well-tuned conventional PID controller was studied in this work. Due to difficulties involving fuzzy controllers tuning (expert knowledge, adjustments in rules, membership functions and gains) it is recommended to develop a tuning procedure, which will greatly reduce the time of design. From the gains of a well-tuned conventional PID controller a hybrid velocity/position fuzzy-PID controller was designed. Experimental tests were carried out for level control in a tank system under different disturbances in set point values. Tuning performance of different conventional and fuzzy-PID structures were evaluated with respect to their functional behaviors (overshoot, rise time and ISE criterion). Results obtained showed that fuzzy controller structure has a great potential for application even when it is possible to implement a conventional PID controller. It is also observed that there is saturation of the manipulated variable for the conventional PID controller which does not occur in the fuzzy-PID controller.

A FRAMEWORK FOR STRUCTURAL MODELLING OF AN RFID-ENABLED INTELLIGENT DISTRIBUTED MANUFACTURING CONTROL SYSTEM

A modern manufacturing facility typically contains several distributed control systems, such as machining stations, assembly stations, and material handling and storage systems. Integrating Radio Frequency Identification (RFID) technology into these control systems provides a basis for monitoring and configuring their components in real-time. With the right structural modelling, it is then possible to evaluate designs and translate them into new operational applications almost immediately. This paper proposes an architecture for the structural modelling of an intelligent distributed control system for a manufacturing facility, by utilising RFID technology. Emphasis is placed on a requirements analysis of the manufacturing system, the design of RFID-enabled intelligent distributed control systems using Unified Modelling Language (UML) diagrams, and the use of efficient algorithms and tools for the implementation of these systems.

Study on Distributed Intelligent Control Model of the Ships Pipe Network

A MAS-based distributed intelligent pipeline leakage control model, ship pipe network through the intelligent valve control system for automatic, independent isolate damaged sections, thereby enhancing ship in wartime circumstances viability. According to distributed intelligent control pipe network model composed of properties, the Agent is divided into sensor Agent, processors and actuators Agent. Agent of the processor by the sensor data collected Agent independent judgment pipe segment status judgment method and control rules proposed intelligent valve leakage indicator to determine the logic of the other characteristic parameters for a comparative study. Pipeline leakage numerical simulation results show that: the model and control logic to isolate leakage pipe sections, using the model can improve the vitality of ship pipe network.

Based on the Electronic Commerce Environment of Intelligent Logistics System Construction

Based on e-commerce environment, the establishment of intelligent logistics system is the new requirement of today's economic development. Through the study of the system design of intelligent logistics system, the system of mutual cooperation, automatically cohesion, intelligent logistics system throughout the supply chain cycle short, cost savings. In the process of implementation, logistics tracking technology to provide clients with the whole process of tracking services, integrated logistics design simulation technology provides intelligent e-commerce logistics simulation test. Logistics transportation scheduling optimization system using GPS technology, GIS was carried out on the vehicle route reasonable planning. Network distributed warehousing and inventory control system for each user to provide comprehensive intelligent distribution, warehousing and inventory control system. Intelligent logistics system dynamic precise management of logistics activities promotes the vigorous development of electronic commerce.

Measurement Platform for Developing the Paragliders' Motion Simulation and Control

The design of remotely controlled and unmanned aerial system (UAS) is an important direction in modern aeronautics. Paragliders and powered paragliders, as UAS may use successfully in applications where stable, low speed flying and mobility are required. This paper introduces a UAS test platform developing for testing the different paragliders that is planned to apply to different purposes: (i) sensor investigation and calibration, (ii) measuring the aerodynamic characteristics, (iii) developing and testing the UAS subsystems, (iv) investigation and parameter and state identification of the paraglider motion equation for developing the paraglider motion simulation and controls. The developing unmanned measurement platform is equipped by (i) sensors for air data collection, positioning, local force components/tress, etc., (ii) control sub-systems containing power and control forces' actuators and control unit as well as (iii) the info-communication system. The most challenging solutions as electronic system, a robust, fail safe remote control system, basic intelligent distributed control system with control forces' actuatorsare described.

A MULTIAGENTS SYSTEM TO CREATE CONTROL AGENTS

The main goal of this work is the development of a multiagents system that would allow the creation of control agents for the intelligent distributed control system based on agents (SCDIA), including the creation of an agent's source code, its compilation, and incorporation to the SCDIA. The SCDIA has a control agents community consisting of five agents that resemble the elements of a closed control loop: coordinator agent, controller agent, measurement agent, acting agent, and specialized agent. Agent development platform JADE was used for developing this system. The system has three main agents: central agent, code generator agent, and behavior agent. These agents communicate with each other to generate the control agents of the SCDIA through the use of a code generation ontology.

Intelligent distributed control systems

Context The paper 2 This work is done in the research laboratory of Prof. Dr. Hans-Michael Hanisch at Martin Luther University in Germany, and supported by the Alexander Von Humboldt foundation under the reference TUN1127196STP. 2 deals with distributed reconfigurable embedded control systems following the component-based International Industrial Standard IEC61499 in which a Function Block (abbreviated by FB) is an event-triggered software component owning data and a control application is a distributed network of Function Blocks. Nowadays, limited related works have been proposed to address particular cases of reconfigurations without considering distributed architectures. Our first problem is to be able to handle all possible forms of reconfigurations that can be applied at run-time to distributed Function Blocks. In this case, a coordination between devices of the execution environment should be applied to guarantee safe and coherent distributed reconfigurations. A second problem is to find the sufficient solutions for the correct implementation of this reconfigurable distributed architecture. Objective The paper defines an implementable multi-agent architecture for automatic and coherent reconfigurations of distributed Function Blocks. Method To address all possible industrial forms, we classify the reconfiguration scenarios into three levels. The first level deals with additions–removals of Function Blocks to-from the system’s implementation. The second deals with updates of compositions of blocks, and the third deals with updates of data. We define a Reconfiguration Agent for each device of the execution environment, and a unique Coordination Agent for coordinations between devices. Each Reconfiguration Agent to be modelled by nested state machines applies local reconfiguration scenarios in the corresponding device after coordinations with the Coordination Agent. We propose an Inter-Agents Communication Protocol to support correct and coherent reconfigurations of distributed devices. This protocol is based on Coordination Matrices to be handled by the Coordination Agent in order to define all reconfiguration scenarios that should be simultaneously applied in distributed devices. We propose XML-based implementations for both kinds of agents where XML code blocks are exchanged between devices to guarantee safety distributed reconfigurations. The contributions of the paper are applied to two Benchmark Production Systems available in our research laboratory. Results The communication protocol is successfully applied to our platforms where simulations are executed to check distributed and coherent reconfiguration scenarios. The Reconfiguration and Coordination Agents are implemented in this platform by following the International Standard IEC61499. We show in addition XML-based successful interactions between devices when distributed reconfigurations are applied. Conclusion The paper successfully defines a multi-agent architecture for IEC61499 distributed reconfigurable embedded systems where Coordination and Reconfiguration agents are proposed to allow feasible and coherent distributed reconfigurations by using a defined communication protocol. This architecture is implemented in XML and applied to real industrial platforms.

A MULTI-AGENT SYSTEM FOR THE MANAGEMENT OF ABNORMAL SITUATIONS IN AN ARTIFICIALLY GAS-LIFTED WELL

Concerning industrial automation, the management of abnormal situations becomes more important everyday. The ability to detect, isolate, and handle abnormal situations in industrial installations, could save huge amounts of money which is normally invested in reparations and/or wasted because of unjustified stoppage of processing plants. In this work, a system for the management of abnormal situations in an artificially gas-lifted well based on agents Abnormal Situations Management System (ASMS) is developed, which is part of the architecture of the industrial automation based on multi-agents systems (SADIA) proposed in Bravo, Aguilar, and Rivas (2004). This agent is based on the intelligent distributed control system based on agents (IDCSBA) reference model proposed in Aguilar, Cerrada, Mousalli, Rivas, and Hidrobo (2005). The MASINA methodology (Aguilar, Hidrobo, and Cerrada 2007) is used in matters of analysis, design, and implementation.