Centralized Control Method Research Articles

A decentralized algorithm for optimal distribution in HVAC systems

This paper introduces a novel decentralized method as a solution to a typical problem in HVAC systems, the optimal distribution problem, which can be described as the optimal control of equipment groups such as the pump and chiller groups, with the goal of attaining optimum allocation in response to a given demand under actual constraints. In this decentralized control system, each unit is fitted with a decentralized controller such that it becomes a smart unit, such as a smart pump or a smart chiller, which can communicate with the other units and thus operate collaboratively to satisfy the control requirements and be energy efficient. The concept of decentralized control is introduced first, then a decentralized optimal control algorithm, which could be applied to the group operation of both pumps and chillers, is developed and validated through the simulation of different cases, and further demonstrated through application to actual hardware. Compared with the traditional centralized control method, this decentralized control method is much more flexible and scalable.

A MPCP-Based Centralized Rate Control Method for Mobile Stations in FiWi Access Networks

Fiber Wireless (FiWi) access networks is widely used to connect users to the core network. The FiWi access networks consist of the edge router, the Passive Optical Networks (PONs), and the wireless networks. In this environment, the edge router, which is the terminal to the core network, can have heavy congestion. To cope with this problem, we propose a Multi Point Control Protocol (MPCP)-based centralized rate control method to centrally control the traffic rate at each Home GateWay (HGW) so as to avoid congestion at the edge router. In the proposed scheme, the transmission delay due to rate control overhead can be mitigated. The performance of the proposed scheme is verified by numerical analysis and computer simulations.

Multi‐agent model‐based predictive control for large‐scale urban traffic networks using a serial scheme

Urban traffic networks are large-scale systems, consisting of many intersections controlled by traffic lights and interacting connected links. For efficiently regulating the traffic flows and mitigating the traffic congestion in cities, a network-wide control strategy should be implemented. Control of large-scale traffic networks is often infeasible by only using a single controller, that is, in a centralised way, because of the high dimension, complicated dynamics and uncertainties of the system. In this study, the authors propose a multi-agent control approach using a congestion-degree-based serial scheme. Each agent employs a model-based predictive control approach and communicates with its neighbours. The congestion-degree-based serial scheme helps the agents to reach an agreement on their decisions regarding traffic control actions as soon as possible. A simulation study is carried out on a hypothetical large-scale urban traffic network based on the presented control strategy. The results illustrate that this approach has a better performance with regard to computation time compared with the centralised control method and a faster convergence speed compared with the classical parallel scheme.

Challenges in the Modelling and Operation of Physically Coupled Systems of Systems

The DYMASOS project focuses on the control of large-scale “System of Systems” that are coupled by exchange of matter and energy. A key challenge with regard to control is that each system has some degree of autonomy in its respective decisions and behavior, which disallows centralized control methods. This paper provides an overview on modeling and optimization techniques that are applied in DYMASOS and points out the general challenges that arise when applying them to real-world case studies.

Interference Minimization and Dynamic Sub-Carrier Allocation in Broadband Wireless Networks

Efficient channel allocation is the key to fully exploit the signal diversity presented in the multi-carrier physical link in today's broadband wireless access networks. There are mounting evidences that the 4G and future-generation systems will take advantage of two opposite types of access methods, one using centralized control method and the other using a distributed approach. The authors study the distributed channel allocation problem in this article, formulated as a non-linear optimization problem, in broadband wireless networks. The signal properties of the multi-carrier radio interface in 3G and 4G networks are discussed to comprehend the complexity of the channel allocation problem. The authors propose a novel distributed heuristic algorithm based on the particle-swarm searching method. The distributed approach allows user stations to quickly switch sub-carriers with minimum intervention from the base station. The work presented in this paper shows an effective method to allocate a large number of channels while minimizing the possible interference. Extensive numerical experiments are conducted to evaluate several versions of distributed channel allocation algorithm for these new problem settings. The authors' results show that PSO-based method converges quickly in all our numerical experiments despite the high-dimensional searching space. The proposed technologies will eventually allow the true mobile steaming video/audio experience anywhere and anytime, which will have the huge impact to business, entertainment and people's quality of life.

Centralized PI/PID Controller Design for Multivariable Processes

A novel centralized controller design method is proposed for multivariable systems, whether square or nonsquare processes. First, the relationship between equivalent transfer function (ETF) and the pseudo-inverse of multivariable transfer matrix is derived. Second, the relative normalized gain array (RNGA)-based ETF parametrization method is extended to the nonsquare processes. Finally, a centralized proportional integral/proportional integral derivative (PI/PID) multivariable controller is obtained from the Maclaurin expansion. The effectiveness of the proposed approach is verified by analysis of several multivariable industrial processes; better overall performance is demonstrated compared with other centralized control methods.

A Design of Novel Intelligent System of Single Phase Electric Meter for Building

According to the number of users and the electricity measurement requirements for building, a novel intelligent system of single phase electric meter for building has been proposed in this paper. It is aiming at the application status and existing problems of watt-hour meter used in China. It has been designed by using the decentralized power parameter detection and centralized control method. The following designs of the intelligent system have been done in the study: the topological structure, hardware and software. According to the design of the intelligent system, the intelligent system of single phase electric meter for building can be developed. The electricity signal processing module, memory, GUI and the communication module are controlled by MCU. The intelligent system can easily measure various parameters, record data safety, calibrate meter with software, and it has more communication interface. The system can be realized functions, such as the monitoring, management, protection, wireless transmission and so on. It can be widely used in ordinary households, residential users, student apartments, office buildings, etc. to achieve the electricity detection, monitoring and controlling intelligently.

Distributed Key Figure Optimization Approaches for Global Goal Coordination in Multi-agent Systems for Production Control

Performance measurement by means of key performance indicators (KPIs) is a widespread device for communicating qualitative and quantitative business objectives throughout an organization and monitoring their achievement. It seems desirable to also apply this concept to dependably influencing the operational behaviour of distributed agent controlled processes, which have progressively gained in importance in production logistics and control over recent years as compared to centralized control methods. However, planning and scheduling with numeric goal systems at present still poses a challenging task within the field of computational intelligence.In this paper, a framework is presented that enables global coordination of agents in a multi-agent system through user-configurable numeric key performance indicators and associated objectives. A practical approach to distributed control based on periodical mathematical optimization of the defined KPI goal system is described that focuses on how automatic key figure aggregation over changing groups and hierarchies of agents and other business objects can be appropriately managed when proactive modification of these organizational structures, e.g., agents deliberately forming and disbanding groups, is an integral part of the control problem. Five variants of this approach are compared in a case study with a simulated shop floor where incoming manufacturing orders need to be assigned to different machine tools.

Design of Distributed Indoor Air Quality Remote Monitoring Network

Aimed at the characteristics of indoor application environment, a real-time wireless monitoring system for indoor air quality based the nRF24L01 and GSM network was proposed. The system built the star subnet structure with nRF24L01 wireless module, used GSM module SIM300 to complete wireless communication between the subnet and GSM network, and achieved GSM network users to remotely monitor indoor air quality. The subnets with master-slave structure mode, which was constituted by the control terminal and multiple data collection terminals, implemented indoor air quality concentration and temperature and humidity data real-time acquisition with the centralized control method. The experimental results show that the subnets can real-time finish wireless data transmission within a distance of 700 meters, and the system with simple structure and stable work can realizes real-time monitoring of indoor air quality.

Request–Response Distributed Power Management in Cloud Data Centers

AbstractPower provision is coming to be the most important constraint to data center development. The efficient management of power consumption according to the loads of the data center is urgent. As the load for every application hosted in every server node (SN) of the data center and corresponding Service Level Agreement (SLA) requirements can be quite different, it is hard to deploy a power strategy at application. The asynchronies and abruptness characteristics of workload fluctuation make power management policymaking using periodic resource scheduling method invalid. In this article, the design and implementation of the request–response distributed power management scheme is elaborated. Bound by linear time complexity, the method proposed integrates dynamic voltage/frequency scaling, power-on–power-off, and virtual machine migration mechanisms and dynamically optimizes the power consumption of a cloud data center. The significant advantage of the scheme is that it does not need synchronous scheduling between all SNs. Simulation results showed that the scheme could effectively decrease the power consumption of the data center, with a tiny reduction in performance as centralized control methods.

Proportional-integral-derivative control of rigid rotor-active magnetic bearing system via eigenvalue assignment for decoupled translational and conical modes

Proportional-integral-derivative (PID) control has been widely adopted for stable and reliable operation of rigid rotors supported by a pair of active magnetic bearing systems. Conventional centralized PID control methods manipulate the feedback gains in prescribed forms until they achieve the desired control performance. In this study, an eigenvalue assignment for decoupled translational and conical modes is proposed in the complex domain to yield a unique PID controller in a closed form, preserving the isotropic bearing characteristics. The eigenvalue assignment necessitates the constraints required for decoupling of the translational and conical whirl motions from the complex equation of motion written in the center of gravity coordinates of the rigid rotor. The complex equation of motion integrates the rigid rotor and electro-magnetic control force models defined in two different coordinate systems by utilizing complex coordinate transformation relations. A flywheel energy storage system is taken as a simulation example in order to demonstrate the validity and effectiveness of the proposed eigenvalue assignment. The simulation results show that the eigenvalue assignment algorithm is superior to conventional control methods at systematically ensuring sufficient stability margins for the lightly-damped and unstable conical modes.

Ant-Based Swarm Algorithm for Charging Coordination of Electric Vehicles

Uncontrolled charging of large-scale electric vehicles (EVs) can affect the safe and economic operation of power systems, especially at the distribution level. The centralized EVs charging optimization methods require complete information of physical appliances and using habits, which will cause problems of high dimensionality and communication block. Given this, an ant-based swarm algorithm (ASA) is proposed to realize the EVs charging coordination at the transformer level, which can overcome the drawbacks of centralized control method. First, the EV charging load model is developed, and the charging management structure based on swarm intelligence is presented. Second, basic data of the EV using habit is sampled by the Monte Carlo method, and the ASA is applied to realize the load valley filling. The load fluctuation and the transformer capacity are also considered in the algorithm. Finally, the charging coordination of 500 EVs under a 12.47 KV transformer is simulated to demonstrate the validity of the proposed method.

Study on Voltage Regulation in a Distribution System Using Electric Vehicles—Optimal Real and Reactive Power Dispatch by Centralized Control

A surge of needs for the low carbon society promotes a spread of electric vehicle (EV). EVs could be charged at night simultaneously. That could cause severe voltage drop. Typical charger for EV employs the self-commutated inverter, which can control both active and reactive powers in principle. The authors have investigated potential availability of EVs for the distribution system operation qualitatively, and have concluded that the utilization of reactive power from EV charger could provide great potential for voltage regulation in the distribution system without loss of EV owner's convenience. The authors have proposed some voltage regulation algorithms using EVs. This paper proposes a new algorithm - a centralized control method in which the distribution system operator collects information of each EV in the distribution system and controls them.

Local Versus Centralized Charging Strategies for Electric Vehicles in Low Voltage Distribution Systems

Controlled charging of electric vehicles offers a potential solution to accommodating large numbers of such vehicles on existing distribution networks without the need for widespread upgrading of network infrastructure. Here, a local control technique is proposed whereby individual electric vehicle charging units attempt to maximise their own charging rate for their vehicle while maintaining local network conditions within acceptable limits. Simulations are performed to demonstrate the benefits of the technique on a test distribution network. The results of the method are also compared to those from a centralized control method whereby EV charging is controlled by a central controller. The paper outlines the advantages and disadvantages of both strategies in terms of capacity utilization and total energy delivered to charging EVs.

The Study for the Electronic Control Technology of the Electric Power Traction System in the Bridge/Shipping Crash Testing Laboratory

The electric power traction system in the Bridge/Shipping Crash Testing Laboratory, is the foundation of the crash test between the shipping and the bridge. In order to make sure the process more quickly, stably, accurately, centralized-control method has been applied in the electric power traction system of the Bridge/Shipping Crash Testing Laboratory in The Changsha University of Science and Technology, so the test flow has been controlled and finished automatically, the test data could be collected and recorded automatically, safety alarm, protect automatically and the history data could be recorded on the real-time, the test report form could been formed automatically and the manage function will be worked and so on. The problem of complexity of the test flow, the difficulty of the induction about the logic relationship, the strong electromagnetism interfere in the big current equipment, the machine shock is strong and so on would be solved, the traction system in the crash test would be made more real and mature.

Route Choice Control of Automated Baggage Handling Systems

State-of-the-art baggage handling systems transport luggage in an automated way by using destination-coded vehicles (DCVs). These vehicles transport the bags at high speeds on a minirailway network. Currently, the networks are simple, with only a few junctions; otherwise bottlenecks would be created at the junctions. Bottlenecks make the system inefficient. More complex networks were considered. To optimize the performance of the system, centralized and decentralized control methods that could be used to route the DCVs through the track network were developed and compared. The proposed centralized control method is model predictive control (MPC). Because of the large computation effort that centralized MPC required, decentralized MPC and a fast decentralized heuristic approach were also proposed. When the decentralized approaches are implemented, each junction has its own local controller for positioning the switch going into the junction and the switch going out of the junction. To assess the advantages and disadvantages of centralized MPC, decentralized MPC, and the decentralized heuristic approach, a simple benchmark case study was studied. The considered control methods were compared for several scenarios. Centralized MPC becomes intractable when a large stream of bags must be handled, whereas decentralized MPC can still be used to solve the problem suboptimally. Moreover, the decentralized heuristic approach usually gives worse results than those obtained when using decentralized MPC but with very low computation time.

Decentralized Sliding Mode Control for a Spacecraft Flexible Appendage Based on Finite Element Method

This paper is devoted to study the application of the decentralized sliding mode control method, which is used to reduce the vibration of large spacecraft flexible appendage. In the process of control design, the sliding surface of sliding mode control is determined by minimizing the optimal cost function, and the controller is the saturation controller. The controlled structure is subject to arbitrary, unmeasurable and uncertainty disturbance forces and initial displacement. The decentralized control method and the centralized control method are used to control vibration of the structure respectively. When the system is subjected to the initial displacement or external disturbance, the computer simulation shows that both of these control methods perform effectively, but the number of Riccati equation of the decentralized method is far smaller than that of centralized control method, especially in a large system.

Simplified power control method for cellular mobile communication

The centralised power control (CPC) method measures the gain of the communication links between every mobile and every base station in the cochannel cells and determines optimal transmitter power to maximise the minimum carrier-to-interference ratio. The authors propose a simplified power control method which has nearly the same performance as the CPC method but which involves much smaller measurement overhead.

Hierarchical Approach to Robot Control System Synthesis

A new approach to the robot dynamical control synthesis is proposed, based on the hierarchical principles of decomposition and coordination. A two-level stabilizing control structure is obtained, which consists of subcontrollers on the lower level and coordinator on the upper one. Independent local linear-quadratic control problems are solved by the subcontrollcrs for subsystems, corresponding to each robot arm joint. The interactions between these subsystems are taken into account via coordination procedure on the upper level. Simulation results are given and comparison between the hierarchical and centralized control methods is made.