Software-Defined Congestion Control Algorithm for IP Networks
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Yao Hu
2017-01-01
Full Text Available The rapid evolution of computer networks, increase in the number of Internet users, and popularity of multimedia applications have exacerbated the congestion control problem. Congestion control is a key factor in ensuring network stability and robustness. When the underlying network and flow information are unknown, the transmission control protocol (TCP must increase or reduce the size of the congestion window to adjust to the changes of traffic in the Internet Protocol (IP network. However, it is possible that a software-defined approach can relieve the network congestion problem more efficiently. This approach has the characteristic of centralized control and can obtain a global topology for unified network management. In this paper, we propose a software-defined congestion control (SDCC algorithm for an IP network. We consider the difference between TCP and the user datagram protocol (UDP and propose a new method to judge node congestion. We initially apply the congestion control mechanism in the congested nodes and then optimize the link utilization to control network congestion.
Design and simulation of airport congestion control algorithms
Simaiakis, Ioannis; Balakrishnan, Hamsa
2014-01-01
This paper proposes a stochastic model of runway departures and a dynamic programming algorithm for their control at congested airports. Using a multi-variable state description that includes the capacity forecast, the runway system is modeled as a semi-Markov process. The paper then introduces a queuing system for modeling the controlled departure process that enables the efficient calculation of optimal pushback policies using decomposition techniques. The developed algorithm is simulated a...
Varma, Subir
2015-01-01
Internet Congestion Control provides a description of some of the most important topics in the area of congestion control in computer networks, with special emphasis on the analytical modeling of congestion control algorithms. The field of congestion control has seen many notable advances in recent years and the purpose of this book, which is targeted towards the advanced and intermediate reader, is to inform about the most important developments in this area. The book should enable the reader to gain a good understanding of the application of congestion control theory to a number of applic
Directory of Open Access Journals (Sweden)
Wei Zhang
2012-01-01
Full Text Available This paper presents the model and algorithms for traffic flow data monitoring and optimal traffic light control based on wireless sensor networks. Given the scenario that sensor nodes are sparsely deployed along the segments between signalized intersections, an analytical model is built using continuum traffic equation and develops the method to estimate traffic parameter with the scattered sensor data. Based on the traffic data and principle of traffic congestion formation, we introduce the congestion factor which can be used to evaluate the real-time traffic congestion status along the segment and to predict the subcritical state of traffic jams. The result is expected to support the timing phase optimization of traffic light control for the purpose of avoiding traffic congestion before its formation. We simulate the traffic monitoring based on the Mobile Century dataset and analyze the performance of traffic light control on VISSIM platform when congestion factor is introduced into the signal timing optimization model. The simulation result shows that this method can improve the spatial-temporal resolution of traffic data monitoring and evaluate traffic congestion status with high precision. It is helpful to remarkably alleviate urban traffic congestion and decrease the average traffic delays and maximum queue length.
The congestion control algorithm based on queue management of each node in mobile ad hoc networks
Wei, Yifei; Chang, Lin; Wang, Yali; Wang, Gaoping
2016-12-01
This paper proposes an active queue management mechanism, considering the node's own ability and its importance in the network to set the queue threshold. As the network load increases, local congestion of mobile ad hoc network may lead to network performance degradation, hot node's energy consumption increase even failure. If small energy nodes congested because of forwarding data packets, then when it is used as the source node will cause a lot of packet loss. This paper proposes an active queue management mechanism, considering the node's own ability and its importance in the network to set the queue threshold. Controlling nodes buffer queue in different levels of congestion area probability by adjusting the upper limits and lower limits, thus nodes can adjust responsibility of forwarding data packets according to their own situation. The proposed algorithm will slow down the send rate hop by hop along the data package transmission direction from congestion node to source node so that to prevent further congestion from the source node. The simulation results show that, the algorithm can better play the data forwarding ability of strong nodes, protect the weak nodes, can effectively alleviate the network congestion situation.
Evaluation of TCP Congestion Control Algorithms on the Windows Vista Platform
Energy Technology Data Exchange (ETDEWEB)
Li, Yee-Ting; /SLAC
2006-07-07
CTCP, an innovative TCP congestion control algorithm developed by Microsoft, is evaluated and compared to HSTCP and StandardTCP. Tests were performed on the production Internet from Stanford Linear Accelerator Center (SLAC) to various geographically located hosts to give a broad overview of the performances. We find that certain issues were apparent during testing (not directly related to the congestion control algorithms) which may skew results. With this in mind, we find that CTCP performed similarly to HSTCP across a multitude of different network environments. However, to improve the fairness and to reduce the impact of CTCP upon existing StandardTCP traffic, two areas of further research were investigated. Algorithmic additions to CTCP for burst control to reduce the aggressiveness of its cwnd increments demonstrated beneficial improvements in both fairness and throughput over the original CTCP algorithm. Similarly, {gamma} auto-tuning algorithms were investigated to dynamically adapt CTCP flows to their network conditions for optimal performance. While the effects of these auto-tuning algorithms when used in addition to burst control showed little to no benefit to fairness nor throughput for the limited number of network paths tested, one of the auto-tuning algorithms performed such that there was negligible impact upon StandardTCP. With these improvements, CTCP was found to perform better than HSTCP in terms of fairness and similarly in terms of throughput under the production environments tested.
Evaluation of TCP Congestion Control Algorithms on the Windows Vista Platform
International Nuclear Information System (INIS)
Li, Y
2006-01-01
CTCP, an innovative TCP congestion control algorithm developed by Microsoft, is evaluated and compared to HSTCP and StandardTCP. Tests were performed on the production Internet from Stanford Linear Accelerator Center (SLAC) to various geographically located hosts to give a broad overview of the performances. We find that certain issues were apparent during testing (not directly related to the congestion control algorithms) which may skew results. With this in mind, we find that CTCP performed similarly to HSTCP across a multitude of different network environments. However, to improve the fairness and to reduce the impact of CTCP upon existing StandardTCP traffic, two areas of further research were investigated. Algorithmic additions to CTCP for burst control to reduce the aggressiveness of its cwnd increments demonstrated beneficial improvements in both fairness and throughput over the original CTCP algorithm. Similarly, auto-tuning algorithms were investigated to dynamically adapt CTCP flows to their network conditions for optimal performance. Whilst the effects of these auto-tuning algorithms when used in addition to burst control showed little to no benefit to fairness nor throughput for the limited number of network paths tested, one of the auto-tuning algorithms performed such that there was negligible impact upon StandardTCP. With these improvements, CTCP was found to perform better than HSTCP in terms of fairness and similarly in terms of throughput under the production environments tested
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Tine L. Vandoorn
2015-06-01
Full Text Available The increasing share of distributed energy resources poses a challenge to the distribution network operator (DNO to maintain the current availability of the system while limiting the investment costs. Related to this, there is a clear trend in DNOs trying to better monitor their grid by installing a distribution management system (DMS. This DMS enables the DNOs to remotely switch their network or better localize and solve faults. Moreover, the DMS can be used to centrally control the grid assets. Therefore, in this paper, a control strategy is discussed that can be implemented in the DMS for solving current congestion problems posed by the increasing share of renewables in the grid. This control strategy controls wind turbines in order to avoid congestion while mitigating the required investment costs in order to achieve a global cost-efficient solution. Next to the application and objective of the control, the parameter tuning of the control algorithm is discussed.
Internet Congestion Control System
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Pranoto Rusmin
2010-10-01
Full Text Available Internet congestion occurs when resource demands exceeds the network capacity. But, it is not the only reason. Congestion can happen on some users because some others user has higher sending rate. Then some users with lower sending rate will experience congestion. This partial congestion is caused by inexactly feedback. At this moment congestion are solved by the involvement of two controlling mechanisms. These mechanisms are flow/congestion control in the TCP source and Active Queue Management (AQM in the router. AQM will provide feedback to the source a kind of indication for the occurrence of the congestion in the router, whereas the source will adapt the sending rate appropriate with the feedback. These mechanisms are not enough to solve internet congestion problem completely. Therefore, this paper will explain internet congestion causes, weakness, and congestion control technique that researchers have been developed. To describe congestion system mechanisms and responses, the system will be simulated by Matlab.
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Akanksha Mishra
2017-05-01
Full Text Available In a deregulated electricity market it may at times become difficult to dispatch all the required power that is scheduled to flow due to congestion in transmission lines. An Interline Power Flow Controller (IPFC can be used to reduce the system loss and power flow in the heavily loaded line, improve stability and loadability of the system. This paper proposes a Disparity Line Utilization Factor for the optimal placement and Gravitational Search algorithm based optimal tuning of IPFC to control the congestion in transmission lines. DLUF ranks the transmission lines in terms of relative line congestion. The IPFC is accordingly placed in the most congested and the least congested line connected to the same bus. Optimal sizing of IPFC is carried using Gravitational Search algorithm. A multi-objective function has been chosen for tuning the parameters of the IPFC. The proposed method is implemented on an IEEE-30 bus test system. Graphical representations have been included in the paper showing reduction in LUF of the transmission lines after the placement of an IPFC. A reduction in active power and reactive power loss of the system by about 6% is observed after an optimally tuned IPFC has been included in the power system. The effectiveness of the proposed tuning method has also been shown in the paper through the reduction in the values of the objective functions.
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Liuhui Zhao
2017-01-01
Full Text Available A shockwave-based speed harmonization algorithm for the longitudinal movement of automated vehicles is presented in this paper. In the advent of Connected/Automated Vehicle (C/AV environment, the proposed algorithm can be applied to capture instantaneous shockwaves constructed from vehicular speed profiles shared by individual equipped vehicles. With a continuous wavelet transform (CWT method, the algorithm detects abnormal speed drops in real-time and optimizes speed to prevent the shockwave propagating to the upstream traffic. A traffic simulation model is calibrated to evaluate the applicability and efficiency of the proposed algorithm. Based on 100% C/AV market penetration, the simulation results show that the CWT-based algorithm accurately detects abnormal speed drops. With the improved accuracy of abnormal speed drop detection, the simulation results also demonstrate that the congestion can be mitigated by reducing travel time and delay up to approximately 9% and 18%, respectively. It is also found that the shockwave caused by nonrecurrent congestion is quickly dissipated even with low market penetration.
Rerouting algorithms solving the air traffic congestion
Adacher, Ludovica; Flamini, Marta; Romano, Elpidio
2017-06-01
Congestion in the air traffic network is a problem with an increasing relevance for airlines costs as well as airspace safety. One of the major issue is the limited operative capacity of the air network. In this work an Autonomous Agent approach is proposed to solve in real time the problem of air traffic congestion. The air traffic infrastructures are modeled with a graph and are considered partitioned in different sectors. Each sector has its own decision agent dealing with the air traffic control involved in it. Each agent sector imposes a real time aircraft scheduling to respect both delay and capacity constrains. When a congestion is predicted, a new aircraft scheduling is computed. Congestion is solved when the capacity constrains are satisfied once again. This can be done by delaying on ground aircraft or/and rerouting aircraft and/or postponing the congestion. We have tested two different algorithms that calculate K feasible paths for each aircraft involved in the congestion. Some results are reported on North Italian air space.
Reducing a congestion with introduce the greedy algorithm on traffic light control
Catur Siswipraptini, Puji; Hendro Martono, Wisnu; Hartanti, Dian
2018-03-01
The density of vehicles causes congestion seen at every junction in the city of jakarta due to the static or manual traffic timing lamp system consequently the length of the queue at the junction is uncertain. The research has been aimed at designing a sensor based traffic system based on the queue length detection of the vehicle to optimize the duration of the green light. In detecting the length of the queue of vehicles using infrared sensor assistance placed in each intersection path, then apply Greedy algorithm to help accelerate the movement of green light duration for the path that requires, while to apply the traffic lights regulation program based on greedy algorithm which is then stored on microcontroller with Arduino Mega 2560 type. Where a developed system implements the greedy algorithm with the help of the infrared sensor it will extend the duration of the green light on the long vehicle queue and accelerate the duration of the green light at the intersection that has the queue not too dense. Furthermore, the design is made to form an artificial form of the actual situation of the scale model or simple simulator (next we just called as scale model of simulator) of the intersection then tested. Sensors used are infrared sensors, where the placement of sensors in each intersection on the scale model is placed within 10 cm of each sensor and serves as a queue detector. From the results of the test process on the scale model with a longer queue obtained longer green light time so it will fix the problem of long queue of vehicles. Using greedy algorithms can add long green lights for 2 seconds on tracks that have long queues at least three sensor levels and accelerate time at other intersections that have longer queue sensor levels less than level three.
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Li Wang
2017-01-01
Full Text Available Traffic congestion is a common problem in many countries, especially in big cities. At present, China’s urban road traffic accidents occur frequently, the occurrence frequency is high, the accident causes traffic congestion, and accidents cause traffic congestion and vice versa. The occurrence of traffic accidents usually leads to the reduction of road traffic capacity and the formation of traffic bottlenecks, causing the traffic congestion. In this paper, the formation and propagation of traffic congestion are simulated by using the improved medium traffic model, and the control strategy of congestion dissipation is studied. From the point of view of quantitative traffic congestion, the paper provides the fact that the simulation platform of urban traffic integration is constructed, and a feasible data analysis, learning, and parameter calibration method based on RBF neural network is proposed, which is used to determine the corresponding decision support system. The simulation results prove that the control strategy proposed in this paper is effective and feasible. According to the temporal and spatial evolution of the paper, we can see that the network has been improved on the whole.
Controlling chaos in Internet congestion control model
International Nuclear Information System (INIS)
Chen Liang; Wang Xiaofan; Han Zhengzhi
2004-01-01
The TCP end-to-end congestion control plus RED router queue management can be modeled as a discrete-time dynamical system, which may create complex bifurcating and chaotic behavior. Based on the basic features of the TCP-RED model, we propose a time-dependent delayed feedback control algorithm to control chaos in the system by perturbing the accessible RED parameter p max . This method is able to stabilized a router queue occupancy at a level without knowing the exact knowledge of the network. Further, we study the situation of the presence of the UDP traffic
Controlling chaos in Internet congestion control model
Energy Technology Data Exchange (ETDEWEB)
Chen Liang E-mail: chenmoon110@yahoo.com.cn; Wang Xiaofan; Han Zhengzhi
2004-07-01
The TCP end-to-end congestion control plus RED router queue management can be modeled as a discrete-time dynamical system, which may create complex bifurcating and chaotic behavior. Based on the basic features of the TCP-RED model, we propose a time-dependent delayed feedback control algorithm to control chaos in the system by perturbing the accessible RED parameter p{sub max}. This method is able to stabilized a router queue occupancy at a level without knowing the exact knowledge of the network. Further, we study the situation of the presence of the UDP traffic.
Congestion control and routing over satellite networks
Cao, Jinhua
Satellite networks and transmissions find their application in fields of computer communications, telephone communications, television broadcasting, transportation, space situational awareness systems and so on. This thesis mainly focuses on two networking issues affecting satellite networking: network congestion control and network routing optimization. Congestion, which leads to long queueing delays, packet losses or both, is a networking problem that has drawn the attention of many researchers. The goal of congestion control mechanisms is to ensure high bandwidth utilization while avoiding network congestion by regulating the rate at which traffic sources inject packets into a network. In this thesis, we propose a stable congestion controller using data-driven, safe switching control theory to improve the dynamic performance of satellite Transmission Control Protocol/Active Queue Management (TCP/AQM) networks. First, the stable region of the Proportional-Integral (PI) parameters for a nominal model is explored. Then, a PI controller, whose parameters are adaptively tuned by switching among members of a given candidate set, using observed plant data, is presented and compared with some classical AQM policy examples, such as Random Early Detection (RED) and fixed PI control. A new cost detectable switching law with an interval cost function switching algorithm, which improves the performance and also saves the computational cost, is developed and compared with a law commonly used in the switching control literature. Finite-gain stability of the system is proved. A fuzzy logic PI controller is incorporated as a special candidate to achieve good performance at all nominal points with the available set of candidate controllers. Simulations are presented to validate the theory. An effocient routing algorithm plays a key role in optimizing network resources. In this thesis, we briefly analyze Low Earth Orbit (LEO) satellite networks, review the Cross Entropy (CE
V2X application-reliability analysis of data-rate and message-rate congestion control algorithms
Math, C. Belagal; Li, H.; Heemstra de Groot, S.M.; Niemegeers, I.G.M.M.
2017-01-01
Intelligent Transportation Systems (ITS) require Vehicle-to-Everything (V2X) communication. In dense traffic, the communication channel may become congested, impairing the reliability of the ITS safety applications. Therefore, European Telecommunications Standard Institute (ETSI) demands
Fair and efficient network congestion control based on minority game
Wang, Zuxi; Wang, Wen; Hu, Hanping; Deng, Zhaozhang
2011-12-01
Low link utility, RTT unfairness and unfairness of Multi-Bottleneck network are the existing problems in the present network congestion control algorithms at large. Through the analogy of network congestion control with the "El Farol Bar" problem, we establish a congestion control model based on minority game(MG), and then present a novel network congestion control algorithm based on the model. The result of simulations indicates that the proposed algorithm can make the achievements of link utility closing to 100%, zero packet lose rate, and small of queue size. Besides, the RTT unfairness and the unfairness of Multi-Bottleneck network can be solved, to achieve the max-min fairness in Multi-Bottleneck network, while efficiently weaken the "ping-pong" oscillation caused by the overall synchronization.
Comparative Study on New AQM Mechanisms for Congestion Control
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Ramakrishna B B
2013-09-01
Full Text Available As usage of network goes increasing day by day, managing network traffic becomes a very difficult task. It is important to avoid high packet loss rates in the Internet. Congestion is the one of the major issue in the present networks. Congestion Control is one of the solutions adopted to solve the congestion issue and to control it. Numbers of queue management algorithms are proposed for congestion control and to reduce high packet loss rates. Active Queue Management (AQM is one such mechanism which provides better control over congestion. In this paper a study is made on recent load based AQM techniques that are proposed and its merits and shortfall is presented.
Congested Link Inference Algorithms in Dynamic Routing IP Network
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Yu Chen
2017-01-01
Full Text Available The performance descending of current congested link inference algorithms is obviously in dynamic routing IP network, such as the most classical algorithm CLINK. To overcome this problem, based on the assumptions of Markov property and time homogeneity, we build a kind of Variable Structure Discrete Dynamic Bayesian (VSDDB network simplified model of dynamic routing IP network. Under the simplified VSDDB model, based on the Bayesian Maximum A Posteriori (BMAP and Rest Bayesian Network Model (RBNM, we proposed an Improved CLINK (ICLINK algorithm. Considering the concurrent phenomenon of multiple link congestion usually happens, we also proposed algorithm CLILRS (Congested Link Inference algorithm based on Lagrangian Relaxation Subgradient to infer the set of congested links. We validated our results by the experiments of analogy, simulation, and actual Internet.
Delay-based virtual congestion control in multi-tenant datacenters
Liu, Yuxin; Zhu, Danhong; Zhang, Dong
2018-03-01
With the evolution of cloud computing and virtualization, the congestion control of virtual datacenters has become the basic issue for multi-tenant datacenters transmission. Regarding to the friendly conflict of heterogeneous congestion control among multi-tenant, this paper proposes a delay-based virtual congestion control, which translates the multi-tenant heterogeneous congestion control into delay-based feedback uniformly by setting the hypervisor translation layer, modifying three-way handshake of explicit feedback and packet loss feedback and throttling receive window. The simulation results show that the delay-based virtual congestion control can effectively solve the unfairness of heterogeneous feedback congestion control algorithms.
Mean Field Type Control with Congestion
Energy Technology Data Exchange (ETDEWEB)
Achdou, Yves, E-mail: achdou@ljll.univ-paris-diderot.fr; Laurière, Mathieu [Univ. Paris Diderot, Sorbonne Paris Cité, Laboratoire Jacques-Louis Lions, UMR 7598, UPMC, CNRS (France)
2016-06-15
We analyze some systems of partial differential equations arising in the theory of mean field type control with congestion effects. We look for weak solutions. Our main result is the existence and uniqueness of suitably defined weak solutions, which are characterized as the optima of two optimal control problems in duality.
Adaptive mechanism-based congestion control for networked systems
Liu, Zhi; Zhang, Yun; Chen, C. L. Philip
2013-03-01
In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.
Signalling and obfuscation for congestion control
Mareček, Jakub; Shorten, Robert; Yu, Jia Yuan
2015-10-01
We aim to reduce the social cost of congestion in many smart city applications. In our model of congestion, agents interact over limited resources after receiving signals from a central agent that observes the state of congestion in real time. Under natural models of agent populations, we develop new signalling schemes and show that by introducing a non-trivial amount of uncertainty in the signals, we reduce the social cost of congestion, i.e., improve social welfare. The signalling schemes are efficient in terms of both communication and computation, and are consistent with past observations of the congestion. Moreover, the resulting population dynamics converge under reasonable assumptions.
A novel symbiotic organisms search algorithm for congestion management in deregulated environment
Verma, Sumit; Saha, Subhodip; Mukherjee, V.
2017-01-01
In today's competitive electricity market, managing transmission congestion in deregulated power system has created challenges for independent system operators to operate the transmission lines reliably within the limits. This paper proposes a new meta-heuristic algorithm, called as symbiotic organisms search (SOS) algorithm, for congestion management (CM) problem in pool based electricity market by real power rescheduling of generators. Inspired by interactions among organisms in ecosystem, SOS algorithm is a recent population based algorithm which does not require any algorithm specific control parameters unlike other algorithms. Various security constraints such as load bus voltage and line loading are taken into account while dealing with the CM problem. In this paper, the proposed SOS algorithm is applied on modified IEEE 30- and 57-bus test power system for the solution of CM problem. The results, thus, obtained are compared to those reported in the recent state-of-the-art literature. The efficacy of the proposed SOS algorithm for obtaining the higher quality solution is also established.
Effective Road Model for Congestion Control in VANETs
Dongre, Manoj M.; Bawane, Narendra G.
2016-01-01
Congestion on the roads is a key problem to deal with, which wastes valuable time.. Due to high mobility rate and relative speed link failure occur very often. VANET is used to tackle the problem of congestion, and make decisions well in advance to avoid traffic congestion. In this paper we proposed a solution to detect and control the traffic congestion by using of both (V2V) and (V2I), as a result the drivers become aware of the location of congestion as well as way to avoid getting stuck i...
End to end adaptive congestion control in TCP/IP networks
Houmkozlis, Christos N
2012-01-01
This book provides an adaptive control theory perspective on designing congestion controls for packet-switching networks. Relevant to a wide range of disciplines and industries, including the music industry, computers, image trading, and virtual groups, the text extensively discusses source oriented, or end to end, congestion control algorithms. The book empowers readers with clear understanding of the characteristics of packet-switching networks and their effects on system stability and performance. It provides schemes capable of controlling congestion and fairness and presents real-world app
A NEW PREDICTIVE MODEL FOR CONGESTION CONTROL IN WIRELESS SENSOR NETWORKS
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NAJME TANZADE PANAH
2017-06-01
Full Text Available With the increase of various applications in the domain of wireless sensor networks, the tendency to use wireless sensors has gradually increased in different applications. On the other hand, diverse traffic with different priorities generated by these sensors requires providing adaptive quality of services based on users` needs. In this paper, a congestion control predictor model is proposed for wireless sensor networks, which considers parameters like network energy consumption, packet loss rate and percentage of delivered high and medium priority packets to the destination. This method consists of congestion prevention, congestion control, and energy control plans using shortest path selection algorithm. In the congestion prevention plan, congestion is prevented by investigating the queues length. In the congestion control plan, the congestion is controlled by reducing the transmission rate. Finally, the energy control plan aims to partially balance the energy of nodes to prevent network failures due to node energy outage. Simulation results indicated that the proposed method has a higher efficiency regarding the aforementioned parameters. In addition, comparisons with other well-known methods showed the effectiveness of the proposed method.
Yang, Xiaoping; Chen, Xueying; Xia, Riting; Qian, Zhihong
2018-04-19
Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm⁻neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS.
Autonomous Congestion Control in Delay-Tolerant Networks
Burleigh, Scott; Jennings, Esther; Schoolcraft, Joshua
2006-01-01
This presentation highlights communication congestion control in delay-tolerant networks (DTNs). Large-scale future space exploration will offer complex communication challenges that may be best addressed by establishing a network infrastructure. However, current internet techniques for congestion control are not well suited for operation of a network over interplanetary distances. An alternative, delay-tolerant technique for congestion control in a delay-tolerant network is presented. A simple DTN was constructed and an experimental congestion control mechanism was applied. The mechanism appeared to be effective and each router was able to make its bundle acceptance decisions autonomously. Future research will examine more complex topologies and alternative bundle acceptance rules that might enhance performance.
Receiver-Assisted Congestion Control to Achieve High Throughput in Lossy Wireless Networks
Shi, Kai; Shu, Yantai; Yang, Oliver; Luo, Jiarong
2010-04-01
Many applications would require fast data transfer in high-speed wireless networks nowadays. However, due to its conservative congestion control algorithm, Transmission Control Protocol (TCP) cannot effectively utilize the network capacity in lossy wireless networks. In this paper, we propose a receiver-assisted congestion control mechanism (RACC) in which the sender performs loss-based control, while the receiver is performing delay-based control. The receiver measures the network bandwidth based on the packet interarrival interval and uses it to compute a congestion window size deemed appropriate for the sender. After receiving the advertised value feedback from the receiver, the sender then uses the additive increase and multiplicative decrease (AIMD) mechanism to compute the correct congestion window size to be used. By integrating the loss-based and the delay-based congestion controls, our mechanism can mitigate the effect of wireless losses, alleviate the timeout effect, and therefore make better use of network bandwidth. Simulation and experiment results in various scenarios show that our mechanism can outperform conventional TCP in high-speed and lossy wireless environments.
Performance analysis of SS7 congestion controls under sustained overload
Manfield, David R.; Millsteed, Gregory K.; Zukerman, Moshe
1994-04-01
Congestion controls are a key factor in achieving the robust performance required of common channel signaling (CCS) networks in the face of partial network failures and extreme traffic loads, especially as networks become large and carry high traffic volume. The CCITT recommendations define a number of types of congestion control, and the parameters of the controls must be well set in order to ensure their efficacy under transient and sustained signalling network overload. The objective of this paper is to present a modeling approach to the determination of the network parameters that govern the performance of the SS7 congestion controls under sustained overload. Results of the investigation by simulation are presented and discussed.
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Bouassida MohamedSalah
2010-01-01
Full Text Available The main objective of congestion control is to best exploit the available network resources while preventing sustained overloads of network nodes and links. Appropriate congestion control mechanisms are essential to provide effcient operation of a network. Ensuring congestion control within vehicular ad hoc networks faces special challenges, due to the specificities of such environment (High mobility of nodes, high rate of topology changes, high variability in nodes density and neighborhood configuration, broadcast/geocast communication nature, etc.. In this context, we present in this paper a cooperative and fully distributed congestion control approach, based on dynamic scheduling and transmission of priority-based messages, to ensure reliable and safe communication architecture within VANET. Messages priorities are dynamically evaluated according to their types, the network context, and the neighboring nodes configuration. Considering the context of high reliability and real-time response required for intervehicular communications (including emergency breaking notification for example, we propose a complete validation method of our congestion control algorithms, taking into account reliability, temporal, and operational aspects.
TCP Congestion Control for the Networks with Markovian Jump Parameters
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MOMENI, H. R.
2011-05-01
Full Text Available This paper is concerned with the problem of TCP congestion control for the class of communication networks with random parameters. The linear dynamic model of TCP New Reno in congestion avoidance mode is considered which contains round trip delays in both state and input. The randomness of link capacity, round trip time delay and the number of TCP sessions is modeled with a continuous-time finite state Markov process. An Active Queue Management (AQM technique is then used to adjust the queue level of the congested link to a predefined value. For this purpose, a dynamic output feedback controller with mode dependent parameters is synthesized to stochastically stabilize the TCP/AQM dynamics. The procedure of the control synthesis is implemented by solving a linear matrix inequality (LMI. The results are tested within a simulation example and the effectiveness of the proposed design method is verified.
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Dawei Shen
2018-01-01
Full Text Available Currently, a number of crowdsourcing-based mobile applications have been implemented in mobile networks and Internet of Things (IoT, targeted at real-time services and recommendation. The frequent information exchanges and data transmissions in collaborative crowdsourcing are heavily injected into the current communication networks, which poses great challenges for Mobile Wireless Networks (MWN. This paper focuses on the traffic scheduling and load balancing problem in software-defined MWN and designs a hybrid routing forwarding scheme as well as a congestion control algorithm to achieve the feasible solution. The traffic scheduling algorithm first sorts the tasks in an ascending order depending on the amount of tasks and then solves it using a greedy scheme. In the proposed congestion control scheme, the traffic assignment is first transformed into a multiknapsack problem, and then the Artificial Fish Swarm Algorithm (AFSA is utilized to solve this problem. Numerical results on practical network topology reveal that, compared with the traditional schemes, the proposed congestion control and traffic scheduling schemes can achieve load balancing, reduce the probability of network congestion, and improve the network throughput.
Analysis of the algorithms for congestion management in computer networks
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S. Szilágyi
2013-06-01
Full Text Available This paper presents one of the features of DS (Differentiated Services architecture, namely the queuing or congestion management. Packets can be placed into separate buffer queues, on the basis of the DS value. Several forwarding policies can be used to favor high priority packets in different ways. The major reason for queuing is that the router must hold the packet in its memory while the outgoing interface is busy with sending another packet. Our main goal is to compare the performance of the following queuing mechanisms: FIFO (First- In First-Out, CQ (Custom Queuing, PQ (Priority Queuing, WFQ (Weighted Fair Queuing, CBWFQ (Class Based Weighted Fair Queuing and LLQ (Low Latency Queuing.
PI Stabilization for Congestion Control of AQM Routers with Tuning Parameter Optimization
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S. Chebli
2016-09-01
Full Text Available In this paper, we consider the problem of stabilizing network using a new proportional- integral (PI based congestion controller in active queue management (AQM router; with appropriate model approximation in the first order delay systems, we seek a stability region of the controller by using the Hermite- Biehler theorem, which isapplicable to quasipolynomials. A Genetic Algorithm technique is employed to derive optimal or near optimal PI controller parameters.
A New TCP Congestion Control Supporting RTT-Fairness
Ogura, Kazumine; Nemoto, Yohei; Su, Zhou; Katto, Jiro
This paper focuses on RTT-fairness of multiple TCP flows over the Internet, and proposes a new TCP congestion control named “HRF (Hybrid RTT-Fair)-TCP”. Today, it is a serious problem that the flows having smaller RTT utilize more bandwidth than others when multiple flows having different RTT values compete in the same network. This means that a user with longer RTT may not be able to obtain sufficient bandwidth by the current methods. This RTT fairness issue has been discussed in many TCP papers. An example is CR (Constant Rate) algorithm, which achieves RTT-fairness by multiplying the square of RTT value in its window increment phase against TCP-Reno. However, the method halves its windows size same as TCP-Reno when a packet loss is detected. This makes worse its efficiency in certain network cases. On the other hand, recent proposed TCP versions essentially require throughput efficiency and TCP-friendliness with TCP-Reno. Therefore, we try to keep these advantages in our TCP design in addition to RTT-fairness. In this paper, we make intuitive analytical models in which we separate resource utilization processes into two cases: utilization of bottleneck link capacity and that of buffer space at the bottleneck link router. These models take into account three characteristic algorithms (Reno, Constant Rate, Constant Increase) in window increment phase where a sender receives an acknowledgement successfully. Their validity is proved by both simulations and implementations. From these analyses, we propose HRF-TCP which switches two modes according to observed RTT values and achieves RTT fairness. Experiments are carried out to validate the proposed method. Finally, HRF-TCP outperforms conventional methods in RTT-fairness, efficiency and friendliness with TCP-Reno.
Energy Effective Congestion Control for Multicast with Network Coding in Wireless Ad Hoc Network
Directory of Open Access Journals (Sweden)
Chuanxin Zhao
2014-01-01
Full Text Available In order to improve network throughput and reduce energy consumption, we propose in this paper a cross-layer optimization design that is able to achieve multicast utility maximization and energy consumption minimization. The joint optimization of congestion control and power allocation is formulated to be a nonlinear nonconvex problem. Using dual decomposition, a distributed optimization algorithm is proposed to avoid the congestion by control flow rate at the source node and eliminate the bottleneck by allocating the power at the intermediate node. Simulation results show that the cross-layer algorithm can increase network performance, reduce the energy consumption of wireless nodes and prolong the network lifetime, while keeping network throughput basically unchanged.
Yang, Xiaoping; Chen, Xueying; Xia, Riting; Qian, Zhihong
2018-01-01
Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm–neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS. PMID:29671822
Novel methods of utilizing Jitter for Network Congestion Control
Directory of Open Access Journals (Sweden)
Ivan
2013-12-01
Full Text Available This paper proposes a novel paradigm for network congestion control. Instead of perpetual conflict as in TCP, a proof-of-concept first-ever protocol enabling inter-flow communication without infrastructure support thru a side channel constructed on generic FIFO queue behaviour is presented. This enables independent flows passing thru the same bottleneck queue to communicate and achieve fair capacity sharing and a stable equilibrium state in a rapid fashion.
Fair decentralized data-rate congestion control for V2V communications
Belagal Math, C.; Li, H.; Heemstra De Groot, S.M.; Niemegeers, I.G.M.M.
2017-01-01
Channel congestion is one of the most critical issues in IEEE 802.11p-based vehicular ad hoc networks because congestion may lead to unreliability of applications. As a counter measure, the European Telecommunications Standard Institute (ETSI), proposes a mandatory Decentralized Congestion Control
Congestion control for vehicular delay tolerant network routing protocols
Oham, Chuka Finbars
2014-01-01
The Vehicular Delay Tolerant Network (VDTN) is a special and challenging type of the Delay Tolerant Network because of its high mobility, frequent disconnections and nodal congestion features. These challenging features make it prone to congestion which leads to a considerable amount of message drops in the network. To minimize the impact of congestion in the network, we designed and implemented the Congestion Aware Spray and Wait (CASaW) routing protocol. We varied the buffer sizes of the no...
Rate-based congestion control in networks with smart links, revision. B.S. Thesis - May 1988
Heybey, Andrew Tyrrell
1990-01-01
The author uses a network simulator to explore rate-based congestion control in networks with smart links that can feed back information to tell senders to adjust their transmission rates. This method differs in a very important way from congestion control in which a congested network component just drops packets - the most commonly used method. It is clearly advantageous for the links in the network to communicate with the end users about the network capacity, rather than the users unilaterally picking a transmission rate. The components in the middle of the network, not the end users, have information about the capacity and traffic in the network. The author experiments with three different algorithms for calculating the control rate to feed back to the users. All of the algorithms exhibit problems in the form of large queues when simulated with a configuration modeling the dynamics of a packet-voice system. However, the problems are not with the algorithms themselves, but with the fact that feedback takes time. If the network steady-state utilization is low enough that it can absorb transients in the traffic through it, then the large queues disappear. If the users are modified to start sending slowly, to allow the network to adapt to a new flow without causing congestion, a greater portion of the network's bandwidth can be used.
Approaching Incast Congestion with Multi-host Ethernet Controllers
Jereczek, Grzegorz Edmund; The ATLAS collaboration
2018-01-01
The bursty many-to-one communication pattern, typical for data acquisition systems, but also present in datacenter networks, is particularly demanding for commodity TCP/IP and Ethernet technologies. We expand our study of building incast-resistant networks based on software switches running on commercial-off-the-shelf servers. In this paper we provide the estimates for costs and physical area required to build such a network. Our estimates indicate that our proposed design offers significant cost advantage over traditional solutions, but higher space utilisation. Next, we show how the latter can be improved with multi-host Ethernet controllers, as an alternative to typical network interface cards. This can also make software switching easier to adapt in datacenter as a solution for incast congestion. We confirm the capabilities for incast-avoidance by evaluating the performance of a reference platform.
Approaching Incast Congestion with Multi-host Ethernet Controllers
AUTHOR|(SzGeCERN)698154; The ATLAS collaboration; Lehmann Miotto, Giovanna; Malone, David; Walukiewicz, Miroslaw
2017-01-01
The bursty many-to-one communication pattern, typical for data acquisition systems, but also present in datacenter networks, is particularly demanding for commodity TCP/IP and Ethernet technologies. We expand our study of building incast-resistant networks based on software switches running on commercial-off-the-shelf servers. In this paper we provide the estimates for costs and physical area required to build such a network. Our estimates indicate that our proposed design offers significant cost advantage over traditional solutions, but higher space utilisation. Next, we show how the latter can be improved with multi-host Ethernet controllers, as an alternative to typical network interface cards. This can also make software switching easier to adapt in datacenter as a solution for incast congestion. We confirm the capabilities for incast-avoidance by evaluating the performance of a reference platform.
Congestion control in wireless links based on selective delivery of erroneous packets
DEFF Research Database (Denmark)
Korhonen, Jari; Perkis, Andrew; Reiter, Ulrich
2011-01-01
Traditionally, congestion control in packet networks is performed by reducing the transmission rate when congestion is detected, in order to cut down the traffic that overwhelms the capacity of the network. However, if the bottleneck is a wireless link, congestion is often cumulated because...... the performance of the proposed mechanism against traditional congestion control with a simulation study. The results show that the proposed approach can improve the overall performance both by increasing the throughput over the wireless and improving the video quality in terms of peak signal-to-noise ratio (PSNR...
Directory of Open Access Journals (Sweden)
Javid Jouzdani
2016-01-01
Full Text Available With the constantly increasing pressure of the competitive environment, supply chain (SC decision makers are forced to consider several aspects of business climate. More specifically, they should take into account the endogenous features (e.g., available means of transportation, and the variety of products and exogenous criteria (e.g., the environmental uncertainty, and transportation system conditions. In this paper, a mixed integer nonlinear programming (MINLP model for dynamic design of a supply chain network is proposed. In this model, multiple products and multiple transportation modes, the time value of money, traffic congestion, and both supply-side and demand-side uncertainties are considered. Due to the complexity of such models, conventional solution methods are not applicable; therefore, two hybrid Electromagnetism-Like Algorithms (EMA are designed and discussed for tackling the problem. The numerical results show the applicability of the proposed model and the capabilities of the solution approaches to the MINLP problem.
International Nuclear Information System (INIS)
Yu-Liang, Liu; Jie, Zhu; Xiao-Shu, Luo
2009-01-01
Based on the fluid flow time-delayed model proposed by Misra et al in internet congestion control, one modified time-delayed model is presented, where the influence of the communication delay on the router queue length is investigated in detail. The main advantage of the new model is that its stability domain is larger even without an extra controller. By linear stability analysis and numerical simulation, the effectiveness and feasibility of the novel model in internet congestion control are verified
Liu, Yu-Liang; Zhu, Jie; Luo, Xiao-Shu
2009-09-01
Based on the fluid flow time-delayed model proposed by Misra et al in internet congestion control, one modified time-delayed model is presented, where the influence of the communication delay on the router queue length is investigated in detail. The main advantage of the new model is that its stability domain is larger even without an extra controller. By linear stability analysis and numerical simulation, the effectiveness and feasibility of the novel model in internet congestion control are verified.
Naja, Rola; Université de Versailles
2015-01-01
In this paper, we develop a preventive congestion control mechanism applied at highway entrances and devised for Intelligent Transportation Systems (ITS). The proposed mechanism provides a vehicular admission control, regulates input traffic and performs vehicular traffic shaping. Our congestion control mechanism includes two classes of vehicles and is based on a specific priority ticket pool scheme with queue-length threshold scheduling policy, tailored to vehicular networks. In an attempt t...
A Survey of Congestion Control Techniques and Data Link Protocols in Satellite Networks
Fahmy, Sonia; Jain, Raj; Lu, Fang; Kalyanaraman, Shivkumar
1998-01-01
Satellite communication systems are the means of realizing a global broadband integrated services digital network. Due to the statistical nature of the integrated services traffic, the resulting rate fluctuations and burstiness render congestion control a complicated, yet indispensable function. The long propagation delay of the earth-satellite link further imposes severe demands and constraints on the congestion control schemes, as well as the media access control techniques and retransmissi...
Directory of Open Access Journals (Sweden)
Prajakta Desai
Full Text Available Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN, wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction, across variations in: (a environmental parameters such as road network topology and configuration; (b algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies.
Desai, Prajakta; Loke, Seng W; Desai, Aniruddha
2017-01-01
Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN), wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies.
Applications of variable speed control for contending with recurrent highway congestion.
2014-07-01
This research project developed vital operational guidelines for design of a variable speed limit (VSL) system and its integrated operations with ramp metering control in contending with recurrent highway congestion. The developed guidelines can serv...
Hybrid control of bifurcation and chaos in stroboscopic model of Internet congestion control system
International Nuclear Information System (INIS)
Ding Dawei; Zhu Jie; Luo Xiaoshu
2008-01-01
Interaction between transmission control protocol (TCP) and random early detection (RED) gateway in the Internet congestion control system has been modelled as a discrete-time dynamic system which exhibits complex bifurcating and chaotic behaviours. In this paper, a hybrid control strategy using both state feedback and parameter perturbation is employed to control the bifurcation and stabilize the chaotic orbits embedded in this discrete-time dynamic system of TCP/RED. Theoretical analysis and numerical simulations show that the bifurcation is delayed and the chaotic orbits are stabilized to a fixed point, which reliably achieves a stable average queue size in an extended range of parameters and even completely eliminates the chaotic behaviour in a particular range of parameters. Therefore it is possible to decrease the sensitivity of RED to parameters. By using the hybrid strategy, we may improve the stability and performance of TCP/RED congestion control system significantly
Hopf bifurcation in an Internet congestion control model
International Nuclear Information System (INIS)
Li Chunguang; Chen Guanrong; Liao Xiaofeng; Yu Juebang
2004-01-01
We consider an Internet model with a single link accessed by a single source, which responds to congestion signals from the network, and study bifurcation of such a system. By choosing the gain parameter as a bifurcation parameter, we prove that Hopf bifurcation occurs. The stability of bifurcating periodic solutions and the direction of the Hopf bifurcation are determined by applying the normal form theory and the center manifold theorem. Finally, a numerical example is given to verify the theoretical analysis
Short paper: Distributed vehicular traffic congestion detection algorithm for urban environments
Milojevic, M.; Rakocevic, V.
2013-01-01
Vehicular traffic congestion is a well-known economic and social problem generating significant costs and safety challenges, and increasing pollution in the cities. Current intelligent transport systems and vehicular networking technologies rely heavily on the supporting network infrastructure which is still not widely available. This paper contributes towards the development of distributed and cooperative vehicular traffic congestion detection by proposing a new vehicle-to-vehicle (V2V) cong...
Cross-Layer Design of Source Rate Control and Congestion Control for Wireless Video Streaming
Directory of Open Access Journals (Sweden)
Peng Zhu
2007-01-01
Full Text Available Cross-layer design has been used in streaming video over the wireless channels to optimize the overall system performance. In this paper, we extend our previous work on joint design of source rate control and congestion control for video streaming over the wired channel, and propose a cross-layer design approach for wireless video streaming. First, we extend the QoS-aware congestion control mechanism (TFRCC proposed in our previous work to the wireless scenario, and provide a detailed discussion about how to enhance the overall performance in terms of rate smoothness and responsiveness of the transport protocol. Then, we extend our previous joint design work to the wireless scenario, and a thorough performance evaluation is conducted to investigate its performance. Simulation results show that by cross-layer design of source rate control at application layer and congestion control at transport layer, and by taking advantage of the MAC layer information, our approach can avoid the throughput degradation caused by wireless link error, and better support the QoS requirements of the application. Thus, the playback quality is significantly improved, while good performance of the transport protocol is still preserved.
Zepf, Joachim; Rufa, Gerhard
1994-04-01
This paper focuses on the transient performance analysis of the congestion and flow control mechanisms in CCITT Signaling System No. 7 (SS7). Special attention is directed to the impacts of the introduction of intelligent services and new applications, e.g., Freephone, credit card services, user-to-user signaling, etc. In particular, we show that signaling traffic characteristics like signaling scenarios or signaling message length as well as end-to-end signaling capabilities have a significant influence on the congestion and flow control and, therefore, on the real-time signaling performance. One important result of our performance studies is that if, e.g., intelligent services are introduced, the SS7 congestion and flow control does not work correctly. To solve this problem, some reinvestigations into these mechanisms would be necessary. Therefore, some approaches, e.g., modification of the Signaling Connection Control Part (SCCP) congestion control, usage of the SCCP relay function, or a redesign of the MTP flow control procedures are discussed in order to guarantee the efficacy of the congestion and flow control mechanisms also in the future.
An Auto Tuning Substation Peak Shaving Controller for Congestion Management Using Flexible Demand
DEFF Research Database (Denmark)
Sossan, Fabrizio; Marinelli, Mattia
2013-01-01
A closed loop substation peak shaving/congestion management controller for radial distribution networks is presented. The controller it uses an individual control signal in order to shift the consumption of a population of demand side resources, DSRs. The controller auto tunes its parameters on...
A congestion line flow control in deregulated power system
Directory of Open Access Journals (Sweden)
Venkatarajan Shanmuga Sundaram
2011-01-01
Full Text Available Under open access, market-driven transactions have become the new independent decision variables defining the behavior of the power system. The possibility of transmission lines getting over-loaded is relatively more under deregulated operation because different parts of the system are owned by separate companies and in part operated under varying service charges. This paper discusses a two-tier algorithm for correcting the lone overloads in conjunction with the conventional power-flow methods. The method uses line flow sensitivities, which are computed by the East Decoupled Power-flow algorithm and can be adapted for on-line implementation.
MQCC: Maximum Queue Congestion Control for Multipath Networks with Blockage
2015-10-19
IEEE Conf. on Computer Communications (INFOCOM), Rio de Janeiro , Brazil, April 2009. [12] V. Subramanian, S. Kalyanaraman, and K. Ramakrishnan, “An...14) As described in Section III-D, the MQCC algorithm is de - signed as a distributed solution to this problem, so an initial evaluation of MQCC is
Design, Implementation and Evaluation of Congestion Control Mechanism for Video Streaming
Hiroshi Noborio; Hiroyuki Hisamatsu; Hiroki Oda
2011-01-01
In recent years, video streaming services over TCP, such as YouTube, have become more and more popular. TCP NewReno, the current TCP standard, performs greedy congestion control, which increases the congestion window size until packet loss occurs. Therefore, because TCP transmits data at a much higher rate than the video playback rate, the probability of packet loss in the network increases, which in turn takes bandwidth from other network traffic. In this paper, we propose a new transport-la...
Directory of Open Access Journals (Sweden)
Swarup Suresh Kulkarni
2017-07-01
Full Text Available Traffic is significant issue in our nation, particularly in urban ranges. Aftereffect of this, activity clog issue happens. Crisis vehicle like rescue vehicle, fire unit, squad cars confront bunches of issue to achieve their goal on account of congested driving conditions, coming about loss of human lives. To minimize this issue we approach new idea name as ”Traffic control framework for blockage control and stolen Vehicle location”. In this framework activity freedom done by transforming Red flag into Green flag. We demonstrate idea of what is called ”Green wave”. Alongside this, we distinguish stolen vehicle by utilizing extremely advantageous RFID innovation. In the event that stolen vehicle is been distinguished, the framework gives ready sign through ringer. Framework sends Message with the assistance of GSM to Police station. In this framework we Use diverse RFID labels for recognizing rescue vehicle, stolen Vehicles. On the off chance that Red flag is on and IR sensor is initiated, then framework gives ringer alarm to movement police. This is novel framework which encourage great answer for comprehend traffic clog.
Infinite horizon optimal impulsive control with applications to Internet congestion control
Avrachenkov, Konstantin; Habachi, Oussama; Piunovskiy, Alexey; Zhang, Yi
2015-04-01
We investigate infinite-horizon deterministic optimal control problems with both gradual and impulsive controls, where any finitely many impulses are allowed simultaneously. Both discounted and long-run time-average criteria are considered. We establish very general and at the same time natural conditions, under which the dynamic programming approach results in an optimal feedback policy. The established theoretical results are applied to the Internet congestion control, and by solving analytically and nontrivially the underlying optimal control problems, we obtain a simple threshold-based active queue management scheme, which takes into account the main parameters of the transmission control protocols, and improves the fairness among the connections in a given network.
Design issues of a back-pressure-based congestion control mechanism
Malhotra, R.; Mandjes, M.R.H.; Scheinhardt, W.R.W.; Berg, van den J.L.
2008-01-01
Congestion control in packet-based networks is often realized by feedback protocols -- in this paper we assess the performance under a back-pressure mechanism that has been proposed and standardized for Ethernet metropolitan networks. Relying on our earlier results for feedback fluid queues, we
CCS_WHMS: A Congestion Control Scheme for Wearable Health Management System.
Kafi, Mohamed Amine; Ben Othman, Jalel; Bagaa, Miloud; Badache, Nadjib
2015-12-01
Wearable computing is becoming a more and more attracting field in the last years thanks to the miniaturisation of electronic devices. Wearable healthcare monitoring systems (WHMS) as an important client of wearable computing technology has gained a lot. Indeed, the wearable sensors and their surrounding healthcare applications bring a lot of benefits to patients, elderly people and medical staff, so facilitating their daily life quality. But from a research point of view, there is still work to accomplish in order to overcome the gap between hardware and software parts. In this paper, we target the problem of congestion control when all these healthcare sensed data have to reach the destination in a reliable manner that avoids repetitive transmission which wastes precious energy or leads to loss of important information in emergency cases, too. We propose a congestion control scheme CCS_WHMS that ensures efficient and fair data delivery while used in the body wearable system part or in the multi-hop inter bodies wearable ones to get the destination. As the congestion detection paradigm is very important in the control process, we do experimental tests to compare between state of the art congestion detection methods, using MICAz motes, in order to choose the appropriate one for our scheme.
Congestion Control in Data Transmission Networks Sliding Mode and Other Designs
Ignaciuk, Przemysław
2013-01-01
Congestion Control in Data Transmission Networks details the modeling and control of data traffic in communication networks. It shows how various networking phenomena can be represented in a consistent mathematical framework suitable for rigorous formal analysis. The monograph differentiates between fluid-flow continuous-time traffic models, discrete-time processes with constant sampling rates, and sampled-data systems with variable discretization periods. The authors address a number of difficult real-life problems, such as: • optimal control of flows with disparate, time-varying delay; • the existence of source and channel nonlinearities; • the balancing of quality of service and fairness requirements; and • the incorporation of variable rate allocation policies. Appropriate control mechanisms which can handle congestion and guarantee high throughput in various traffic scenarios (with different networking phenomena being considered) are proposed. Systematic design procedures using sound control-theo...
A combined fair decentralized message-rate and data-rate congestion control for V2V communication
Belagal Math, Chetan; Li, Hong; De Groot, Sonia Heemstra; Niemegeers, Ignas
2018-01-01
Channel congestion Is one of the most critical Issues In IEEE 802.11p-based vehicular ad hoc networks as it leads to unreliability of safety applications. As a counter measure, the European Telecommunications Standard Institute (ETSI), proposes a mandatory Decentralized Congestion Control (DCC)
Indirect control of DSRs for regulating power provision and solving local congestions
DEFF Research Database (Denmark)
Sossan, Fabrizio; Marinelli, Mattia; Costanzo, Giuseppe Tommaso
2013-01-01
Inducing a shift in the electricity consumption using a broadcasted dynamic price for the energy is often proposed as a resource for providing regulating power and it is becoming an increasing research focus for enabling higher penetration of renewable energy in the current power system. This paper...... with the CIGRE’ MV reference network with 346 electrically heated buildings as Demand Side Resources, DSRs. The dynamic hourly price of the regulating power provided by Nord Pool Spot market has been used as indirect control signal for the flexible demand....... shows how using indirect control (or control by price) without any precautions, might easily lead to congestions in nearly saturated distribution grids. An auto tuning local controller which acts on the price signal at distribution level is proposed for solving the congestion. Simulations are performed...
Cross-Layer Active Predictive Congestion Control Protocol for Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Yinfeng Wu
2009-10-01
Full Text Available In wireless sensor networks (WSNs, there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node‟s neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks.
Cross-layer active predictive congestion control protocol for wireless sensor networks.
Wan, Jiangwen; Xu, Xiaofeng; Feng, Renjian; Wu, Yinfeng
2009-01-01
In wireless sensor networks (WSNs), there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC) for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node's neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks.
Managing Recurrent Congestion of Subway Network in Peak Hours with Station Inflow Control
Qingru Zou; Xiangming Yao; Peng Zhao; Fei Dou; Taoyuan Yang
2018-01-01
Station inflow control (SIC) is an important and effective method for reducing recurrent congestion during peak hours in the Beijing, Shanghai, and Guangzhou subway systems. This work proposes a practical and efficient method for establishing a static SIC scheme in normal weekdays for large-scale subway networks. First, a traffic assignment model without capacity constraint is utilized to determine passenger flow distributions on the network. An internal relationship between station inflows a...
Dynamics of the congestion control model in underwater wireless sensor networks with time delay
International Nuclear Information System (INIS)
Dong, Tao; Hu, Wenjie; Liao, Xiaofeng
2016-01-01
In this paper, a congestion control model in underwater wireless sensor network with time delay is considered. First, the boundedness of the positive equilibrium, where the samples density is positive for each node and the different event flows coexist, is investigated, which implies that the samples density of sensor node cannot exceed the Environmental carrying capacity. Then, by considering the time delay can be regarded as a bifurcating parameter, the dynamical behaviors, which include local stability and Hopf bifurcation, are investigated. It is found that when the communication time delay passes a critical value, the system loses its stability and a Hopf bifurcation occurs, which means the underwater wireless sensor network will be congested, even collapsed. Furthermore, the direction and stability of the bifurcating periodic solutions are derived by applying the normal form theory and the center manifold theorem. Finally, some numerical examples are finally performed to verify the theoretical results.
Karami, Amin
2015-01-01
Named Data Networking (NDN) is a promising network architecture being considered as a possible replacement for the current IP-based Internet infrastructure. However, NDN is subject to congestion when the number of data packets that reach one or various routers in a certain period of time is so high than its queue gets overflowed. To address this problem many congestion control protocols have been proposed in the literature which, however, they are highly sensitive to their control parameters ...
A Congestion Control System Based on VANET for Small Length Roads
Directory of Open Access Journals (Sweden)
Ruchin Jain
2018-01-01
Full Text Available As vehicle population has been increasing on a daily basis, this leads towards increased number of accidents. To overcome this issue, Vehicular Ad Hoc Network (VANET has come up with lot of novel ideas such as vehicular communication, navigation and traffic controlling. In this study, the main focus is on congestion control at the intersections which result from unclear ahead. For this purpose, a city lane and intersection model has been proposed to manage vehicle mobility. It shows the actual vehicle to vehicle and vehicle to traffic infrastructure communication. The experiment was conducted using Network Simulator 2 (NS 2. The implementation required modelling the road side unit, traffic control unit, and on-board unit along the roadside. In the simulation, including traffic volume, the distance between two signals, end-to-end delay, packet delivery ratio, throughput and packet lost were taken into consideration. These parameters ensure efficient communication between the traffic signals. This results in improved congestion control and road safety, since the vehicles will be signalled not to enter the junction box and information about other vehicles.
SDTCP: Towards Datacenter TCP Congestion Control with SDN for IoT Applications.
Lu, Yifei; Ling, Zhen; Zhu, Shuhong; Tang, Ling
2017-01-08
The Internet of Things (IoT) has gained popularity in recent years. Today's IoT applications are now increasingly deployed in cloud platforms to perform Big Data analytics. In cloud data center networks (DCN), TCP incast usually happens when multiple senders simultaneously communicate with a single receiver. However, when TCP incast happens, DCN may suffer from both throughput collapse for TCP burst flows and temporary starvation for TCP background flows. In this paper, we propose a software defined network (SDN)-based TCP congestion control mechanism, referred to as SDTCP, to leverage the features, e.g., centralized control methods and the global view of the network, in order to solve the TCP incast problems. When we detect network congestion on an OpenFlow switch, our controller can select the background flows and reduce their bandwidth by adjusting the advertised window of TCP ACK packets of the corresponding background flows so as to reserve more bandwidth for burst flows. SDTCP is transparent to the end systems and can accurately decelerate the rate of background flows by leveraging the global view of the network gained via SDN. The experiments demonstrate that our SDTCP can provide high tolerance for burst flows and achieve better flow completion time for short flows. Therefore, SDTCP is an effective and scalable solution for the TCP incast problem.
SDTCP: Towards Datacenter TCP Congestion Control with SDN for IoT Applications
Directory of Open Access Journals (Sweden)
Yifei Lu
2017-01-01
Full Text Available The Internet of Things (IoT has gained popularity in recent years. Today’s IoT applications are now increasingly deployed in cloud platforms to perform Big Data analytics. In cloud data center networks (DCN, TCP incast usually happens when multiple senders simultaneously communicate with a single receiver. However, when TCP incast happens, DCN may suffer from both throughput collapse for TCP burst flows and temporary starvation for TCP background flows. In this paper, we propose a software defined network (SDN-based TCP congestion control mechanism, referred to as SDTCP, to leverage the features, e.g., centralized control methods and the global view of the network, in order to solve the TCP incast problems. When we detect network congestion on an OpenFlow switch, our controller can select the background flows and reduce their bandwidth by adjusting the advertised window of TCP ACK packets of the corresponding background flows so as to reserve more bandwidth for burst flows. SDTCP is transparent to the end systems and can accurately decelerate the rate of background flows by leveraging the global view of the network gained via SDN. The experiments demonstrate that our SDTCP can provide high tolerance for burst flows and achieve better flow completion time for short flows. Therefore, SDTCP is an effective and scalable solution for the TCP incast problem.
Congestion Control for a Fair Packet Delivery in WSN: From a Complex System Perspective
Directory of Open Access Journals (Sweden)
Daniela Aguirre-Guerrero
2014-01-01
Full Text Available In this work, we propose that packets travelling across a wireless sensor network (WSN can be seen as the active agents that make up a complex system, just like a bird flock or a fish school, for instance. From this perspective, the tools and models that have been developed to study this kind of systems have been applied. This is in order to create a distributed congestion control based on a set of simple rules programmed at the nodes of the WSN. Our results show that it is possible to adapt the carried traffic to the network capacity, even under stressing conditions. Also, the network performance shows a smooth degradation when the traffic goes beyond a threshold which is settled by the proposed self-organized control. In contrast, without any control, the network collapses before this threshold. The use of the proposed solution provides an effective strategy to address some of the common problems found in WSN deployment by providing a fair packet delivery. In addition, the network congestion is mitigated using adaptive traffic mechanisms based on a satisfaction parameter assessed by each packet which has impact on the global satisfaction of the traffic carried by the WSN.
Directory of Open Access Journals (Sweden)
Georges Arnaout
2011-12-01
Full Text Available Purpose: In this paper, the impact of Cooperative Adaptive Cruise Control (CACC systems on traffic performance is examined using microscopic agent-based simulation. Using a developed traffic simulation model of a freeway with an on-ramp - created to induce perturbations and to trigger stop-and-go traffic, the CACC system’s effect on the traffic performance is studied. The previously proposed traffic simulation model is extended and validated. By embedding CACC vehicles in different penetration levels, the results show significance and indicate the potential of CACC systems to improve traffic characteristics and therefore can be used to reduce traffic congestion. The study shows that the impact of CACC is positive but is highly dependent on the CACC market penetration. The flow rate of the traffic using CACC is proportional to the market penetration rate of CACC equipped vehicles and the density of the traffic.Design/methodology/approach: This paper uses microscopic simulation experiments followed by a quantitative statistical analysis. Simulation enables researchers manipulating the system variables to straightforwardly predict the outcome on the overall system, giving researchers the unique opportunity to interfere and make improvements to performance. Thus with simulation, changes to variables that might require excessive time, or be unfeasible to carry on real systems, are often completed within seconds.Findings: The findings of this paper are summarized as follow:•\tProvide and validate a platform (agent-based microscopic traffic simulator in which any CACC algorithm (current or future may be evaluated.•\tProvide detailed analysis associated with implementation of CACC vehicles on freeways.•\tInvestigate whether embedding CACC vehicles on freeways has a significant positive impact or not.Research limitations/implications: The main limitation of this research is that it has been conducted solely in a computer laboratory. Laboratory
Performance Analysis of Congestion Control Mechanism in Software Defined Network (SDN
Directory of Open Access Journals (Sweden)
Rahman M. Z. A.
2017-01-01
Full Text Available In the near future, the traditional networks architecture will be difficult to be managed. Hence, Software Defined Network (SDN will be an alternative in the future of programmable networks to replace the conventional network architecture. The main idea of SDN architecture is to separate the forwarding plane and control plane of network system, where network operators can program packet forwarding behaviour to improve the network performance. Congestion control is important mechanism for network traffic to improve network capability and achieve high end Quality of Service (QoS. In this paper, extensive simulation is conducted to analyse the performance of SDN by implementing Link Layer Discovery Protocol (LLDP under congested network. The simulation was conducted on Mininet by creating four different fanout and the result was analysed based on differences of matrix performance. As a result, the packet loss and throughput reduction were observed when number of fanout in the topology was increased. By using LLDP protocol, huge reduction in packet loss rate has been achieved while maximizing percentage packet delivery ratio.
A Beacon Transmission Power Control Algorithm Based on Wireless Channel Load Forecasting in VANETs.
Mo, Yuanfu; Yu, Dexin; Song, Jun; Zheng, Kun; Guo, Yajuan
2015-01-01
In a vehicular ad hoc network (VANET), the periodic exchange of single-hop status information broadcasts (beacon frames) produces channel loading, which causes channel congestion and induces information conflict problems. To guarantee fairness in beacon transmissions from each node and maximum network connectivity, adjustment of the beacon transmission power is an effective method for reducing and preventing channel congestion. In this study, the primary factors that influence wireless channel loading are selected to construct the KF-BCLF, which is a channel load forecasting algorithm based on a recursive Kalman filter and employs multiple regression equation. By pre-adjusting the transmission power based on the forecasted channel load, the channel load was kept within a predefined range; therefore, channel congestion was prevented. Based on this method, the CLF-BTPC, which is a transmission power control algorithm, is proposed. To verify KF-BCLF algorithm, a traffic survey method that involved the collection of floating car data along a major traffic road in Changchun City is employed. By comparing this forecast with the measured channel loads, the proposed KF-BCLF algorithm was proven to be effective. In addition, the CLF-BTPC algorithm is verified by simulating a section of eight-lane highway and a signal-controlled urban intersection. The results of the two verification process indicate that this distributed CLF-BTPC algorithm can effectively control channel load, prevent channel congestion, and enhance the stability and robustness of wireless beacon transmission in a vehicular network.
A Beacon Transmission Power Control Algorithm Based on Wireless Channel Load Forecasting in VANETs.
Directory of Open Access Journals (Sweden)
Yuanfu Mo
Full Text Available In a vehicular ad hoc network (VANET, the periodic exchange of single-hop status information broadcasts (beacon frames produces channel loading, which causes channel congestion and induces information conflict problems. To guarantee fairness in beacon transmissions from each node and maximum network connectivity, adjustment of the beacon transmission power is an effective method for reducing and preventing channel congestion. In this study, the primary factors that influence wireless channel loading are selected to construct the KF-BCLF, which is a channel load forecasting algorithm based on a recursive Kalman filter and employs multiple regression equation. By pre-adjusting the transmission power based on the forecasted channel load, the channel load was kept within a predefined range; therefore, channel congestion was prevented. Based on this method, the CLF-BTPC, which is a transmission power control algorithm, is proposed. To verify KF-BCLF algorithm, a traffic survey method that involved the collection of floating car data along a major traffic road in Changchun City is employed. By comparing this forecast with the measured channel loads, the proposed KF-BCLF algorithm was proven to be effective. In addition, the CLF-BTPC algorithm is verified by simulating a section of eight-lane highway and a signal-controlled urban intersection. The results of the two verification process indicate that this distributed CLF-BTPC algorithm can effectively control channel load, prevent channel congestion, and enhance the stability and robustness of wireless beacon transmission in a vehicular network.
Zhang, Shu; Xu, Jian; Chung, Kwok-wai
2015-05-01
Random early detection (RED) is an effective algorithm to control the Internet congestion. However, researches on RED parameters are difficult since there are state-dependent delay and discontinuous terms on the right-hand side of the model. We smooth the model by hyperbolic tangent function and reformulate it by a switch function to keep state variables positive. Numerical simulations on the original system validates the reformulated model. The multi-stability phenomenon is observed and some suggestions on the selection of RED parameters are given to enhance the global stability of the model by numerical bifurcation continuation on the reformulated model.
Chen, Yanyi; Wu, Hongyu; Wen, Zhe
2017-05-01
Inland waterway transportation is an important part of the comprehensive transportation system of sustainable development, and it is also a way of transportation which is restricted by natural conditions greatly. In recent years, the problems of insufficient traffic capacity of The Three Gorges become prominent due to the increasing in the number of ships. And the ship's detention caused by gale, frog, accident and one-way traffic in dry season has occurred, which not only increased the pressure of the navigable waterway but also seriously affected the safety of shipping. Based on the different types of ships, the Arena software was used to simulate the ship traffic flow. The paper analyzed the traffic congestion propagation and dissipation rule of the ship under different navigation control methods, and provided decision reference for the navigation management department to formulate the relevant navigation control strategy.
Predictive functional control for active queue management in congested TCP/IP networks.
Bigdeli, N; Haeri, M
2009-01-01
Predictive functional control (PFC) as a new active queue management (AQM) method in dynamic TCP networks supporting explicit congestion notification (ECN) is proposed. The ability of the controller in handling system delay along with its simplicity and low computational load makes PFC a privileged AQM method in the high speed networks. Besides, considering the disturbance term (which represents model/process mismatches, external disturbances, and existing noise) in the control formulation adds some level of robustness into the PFC-AQM controller. This is an important and desired property in the control of dynamically-varying computer networks. In this paper, the controller is designed based on a small signal linearized fluid-flow model of the TCP/AQM networks. Then, closed-loop transfer function representation of the system is derived to analyze the robustness with respect to the network and controller parameters. The analytical as well as the packet-level ns-2 simulation results show the out-performance of the developed controller for both queue regulation and resource utilization. Fast response, low queue fluctuations (and consequently low delay jitter), high link utilization, good disturbance rejection, scalability, and low packet marking probability are other features of the developed method with respect to other well-known AQM methods such as RED, PI, and REM which are also simulated for comparison.
Mean Field Type Control with Congestion (II): An Augmented Lagrangian Method
Energy Technology Data Exchange (ETDEWEB)
Achdou, Yves, E-mail: achdou@ljll.univ-paris-diderot.fr; Laurière, Mathieu [Univ. Paris Diderot, Sorbonne Paris Cité, Laboratoire Jacques-Louis Lions, UMR 7598, UPMC, CNRS (France)
2016-12-15
This work deals with a numerical method for solving a mean-field type control problem with congestion. It is the continuation of an article by the same authors, in which suitably defined weak solutions of the system of partial differential equations arising from the model were discussed and existence and uniqueness were proved. Here, the focus is put on numerical methods: a monotone finite difference scheme is proposed and shown to have a variational interpretation. Then an Alternating Direction Method of Multipliers for solving the variational problem is addressed. It is based on an augmented Lagrangian. Two kinds of boundary conditions are considered: periodic conditions and more realistic boundary conditions associated to state constrained problems. Various test cases and numerical results are presented.
Subcubic Control Flow Analysis Algorithms
DEFF Research Database (Denmark)
Midtgaard, Jan; Van Horn, David
We give the first direct subcubic algorithm for performing control flow analysis of higher-order functional programs. Despite the long held belief that inclusion-based flow analysis could not surpass the ``cubic bottleneck, '' we apply known set compression techniques to obtain an algorithm...... that runs in time O(n^3/log n) on a unit cost random-access memory model machine. Moreover, we refine the initial flow analysis into two more precise analyses incorporating notions of reachability. We give subcubic algorithms for these more precise analyses and relate them to an existing analysis from...
Managing Recurrent Congestion of Subway Network in Peak Hours with Station Inflow Control
Directory of Open Access Journals (Sweden)
Qingru Zou
2018-01-01
Full Text Available Station inflow control (SIC is an important and effective method for reducing recurrent congestion during peak hours in the Beijing, Shanghai, and Guangzhou subway systems. This work proposes a practical and efficient method for establishing a static SIC scheme in normal weekdays for large-scale subway networks. First, a traffic assignment model without capacity constraint is utilized to determine passenger flow distributions on the network. An internal relationship between station inflows and section flows is then constructed. Second, capacity bottlenecks are identified by considering the transport capacity of each section. Then, a feedback-based bottleneck elimination strategy is established to search target control stations and determine their control time and control strength. To validate the effectiveness of the proposed approach, a decision support system coded in the C# programming language was developed, and the Beijing subway was used as a case study. The results indicate that the proposed method and tool are capable of practical applications, and the generated SIC plan has better performance over the existing SIC plan. This study provides a practical and useful method for operation agencies to construct SIC schemes in the subway system.
CONGESTION CONTROL IMPROVED QoS ROUTING SCHEME FOR WIRELESS SENSOR NETWORK
A. Elakkiya*, B. Santhana Krishnan, Dr. M. Ramaswamy
2016-01-01
Wireless sensor network is distributed self-governing sensors used to monitor the physical conditions of the environment. They are constructed by nodes where each of them is connected to sensors. These sensor nodes acquire real time information and transmit the information. When large number of sensor nodes are active in transmitting the information there is a possibility of congestion in the data packets. Congestion occurs due to buffer overflow, channel contention, packet collision, reporti...
Congestion levies; Congestieheffingen
Energy Technology Data Exchange (ETDEWEB)
Verhoef, E.T. [Vakgroep Ruimtelijke Economie, Vrije Universiteit en Tinbergen Instituut, Amsterdam (Netherlands)
1998-02-20
Traffic jams or congestion can be controlled by means of Pigouvian levies. Congestion costs comprise both time losses as scheduling costs. Because a part of those costs are external costs, the free market output is not Pareto-efficient, and therefore levies are required to recover the efficiency. With some restrictions, road-pricing for the western part of the Netherlands is considered to be a feasible option
International Nuclear Information System (INIS)
Wang Jun-Song; Yuan Rui-Xi; Gao Zhi-Wei; Wang De-Jin
2011-01-01
We study the Hopf bifurcation and the chaos phenomena in a random early detection-based active queue management (RED-AQM) congestion control system with a communication delay. We prove that there is a critical value of the communication delay for the stability of the RED-AQM control system. Furthermore, we show that the system will lose its stability and Hopf bifurcations will occur when the delay exceeds the critical value. When the delay is close to its critical value, we demonstrate that typical chaos patterns may be induced by the uncontrolled stochastic traffic in the RED-AQM control system even if the system is still stable, which reveals a new route to the chaos besides the bifurcation in the network congestion control system. Numerical simulations are given to illustrate the theoretical results. (general)
A Game Theory Based Congestion Control Protocol for Wireless Personal Area Networks
Directory of Open Access Journals (Sweden)
Chuang Ma
2016-01-01
Full Text Available In wireless sensor networks (WSNs, the presence of congestion increases the ratio of packet loss and energy consumption and reduces the network throughput. Particularly, this situation will be more complex in Internet of Things (IoT environment, which is composed of thousands of heterogeneous nodes. RPL is an IPv6 routing protocol in low power and lossy networks standardized by IETF. However, the RPL can induce problems under network congestion, such as frequently parent changing and throughput degradation. In this paper, we address the congestion problem between parent nodes and child nodes in RPL-enabled networks, which typically consist of low power and resource constraint devices. To mitigate the effect of network congestion, we design a parent-change procedure by game theory strategy, by which the child nodes can change next hop neighbors toward the sink. Comparing to the ContikiRPL implementation, the simulation results show that our protocol can achieve more than two times improvement in throughput and reduce packet loss rate with less increasing of average hop count.
Data rate based congestion control in V2V communication for traffic safety applications
Belagal Math, C.; Özgür, A.; Heemstra de Groot, S.M.; Li, H.
2015-01-01
Vehicle-to-Vehicle (V2V) communication systems intend to increase safety and efficiency of the transportation networks. At high vehicle density, the communication channel may become congested, impairing the reliability of the safety applications. As a counter measure, the European Telecommunications
Congestion Pricing for Aircraft Pushback Slot Allocation.
Liu, Lihua; Zhang, Yaping; Liu, Lan; Xing, Zhiwei
2017-01-01
In order to optimize aircraft pushback management during rush hour, aircraft pushback slot allocation based on congestion pricing is explored while considering monetary compensation based on the quality of the surface operations. First, the concept of the "external cost of surface congestion" is proposed, and a quantitative study on the external cost is performed. Then, an aircraft pushback slot allocation model for minimizing the total surface cost is established. An improved discrete differential evolution algorithm is also designed. Finally, a simulation is performed on Xinzheng International Airport using the proposed model. By comparing the pushback slot control strategy based on congestion pricing with other strategies, the advantages of the proposed model and algorithm are highlighted. In addition to reducing delays and optimizing the delay distribution, the model and algorithm are better suited for use for actual aircraft pushback management during rush hour. Further, it is also observed they do not result in significant increases in the surface cost. These results confirm the effectiveness and suitability of the proposed model and algorithm.
Congestion Pricing for Aircraft Pushback Slot Allocation.
Directory of Open Access Journals (Sweden)
Lihua Liu
Full Text Available In order to optimize aircraft pushback management during rush hour, aircraft pushback slot allocation based on congestion pricing is explored while considering monetary compensation based on the quality of the surface operations. First, the concept of the "external cost of surface congestion" is proposed, and a quantitative study on the external cost is performed. Then, an aircraft pushback slot allocation model for minimizing the total surface cost is established. An improved discrete differential evolution algorithm is also designed. Finally, a simulation is performed on Xinzheng International Airport using the proposed model. By comparing the pushback slot control strategy based on congestion pricing with other strategies, the advantages of the proposed model and algorithm are highlighted. In addition to reducing delays and optimizing the delay distribution, the model and algorithm are better suited for use for actual aircraft pushback management during rush hour. Further, it is also observed they do not result in significant increases in the surface cost. These results confirm the effectiveness and suitability of the proposed model and algorithm.
Control algorithms for dynamic attenuators
Energy Technology Data Exchange (ETDEWEB)
Hsieh, Scott S., E-mail: sshsieh@stanford.edu [Department of Radiology, Stanford University, Stanford, California 94305 and Department of Electrical Engineering, Stanford University, Stanford, California 94305 (United States); Pelc, Norbert J. [Department of Radiology, Stanford University, Stanford California 94305 and Department of Bioengineering, Stanford University, Stanford, California 94305 (United States)
2014-06-15
Purpose: The authors describe algorithms to control dynamic attenuators in CT and compare their performance using simulated scans. Dynamic attenuators are prepatient beam shaping filters that modulate the distribution of x-ray fluence incident on the patient on a view-by-view basis. These attenuators can reduce dose while improving key image quality metrics such as peak or mean variance. In each view, the attenuator presents several degrees of freedom which may be individually adjusted. The total number of degrees of freedom across all views is very large, making many optimization techniques impractical. The authors develop a theory for optimally controlling these attenuators. Special attention is paid to a theoretically perfect attenuator which controls the fluence for each ray individually, but the authors also investigate and compare three other, practical attenuator designs which have been previously proposed: the piecewise-linear attenuator, the translating attenuator, and the double wedge attenuator. Methods: The authors pose and solve the optimization problems of minimizing the mean and peak variance subject to a fixed dose limit. For a perfect attenuator and mean variance minimization, this problem can be solved in simple, closed form. For other attenuator designs, the problem can be decomposed into separate problems for each view to greatly reduce the computational complexity. Peak variance minimization can be approximately solved using iterated, weighted mean variance (WMV) minimization. Also, the authors develop heuristics for the perfect and piecewise-linear attenuators which do not requirea priori knowledge of the patient anatomy. The authors compare these control algorithms on different types of dynamic attenuators using simulated raw data from forward projected DICOM files of a thorax and an abdomen. Results: The translating and double wedge attenuators reduce dose by an average of 30% relative to current techniques (bowtie filter with tube current
Control algorithms for dynamic attenuators
International Nuclear Information System (INIS)
Hsieh, Scott S.; Pelc, Norbert J.
2014-01-01
Purpose: The authors describe algorithms to control dynamic attenuators in CT and compare their performance using simulated scans. Dynamic attenuators are prepatient beam shaping filters that modulate the distribution of x-ray fluence incident on the patient on a view-by-view basis. These attenuators can reduce dose while improving key image quality metrics such as peak or mean variance. In each view, the attenuator presents several degrees of freedom which may be individually adjusted. The total number of degrees of freedom across all views is very large, making many optimization techniques impractical. The authors develop a theory for optimally controlling these attenuators. Special attention is paid to a theoretically perfect attenuator which controls the fluence for each ray individually, but the authors also investigate and compare three other, practical attenuator designs which have been previously proposed: the piecewise-linear attenuator, the translating attenuator, and the double wedge attenuator. Methods: The authors pose and solve the optimization problems of minimizing the mean and peak variance subject to a fixed dose limit. For a perfect attenuator and mean variance minimization, this problem can be solved in simple, closed form. For other attenuator designs, the problem can be decomposed into separate problems for each view to greatly reduce the computational complexity. Peak variance minimization can be approximately solved using iterated, weighted mean variance (WMV) minimization. Also, the authors develop heuristics for the perfect and piecewise-linear attenuators which do not requirea priori knowledge of the patient anatomy. The authors compare these control algorithms on different types of dynamic attenuators using simulated raw data from forward projected DICOM files of a thorax and an abdomen. Results: The translating and double wedge attenuators reduce dose by an average of 30% relative to current techniques (bowtie filter with tube current
Control algorithms for dynamic attenuators.
Hsieh, Scott S; Pelc, Norbert J
2014-06-01
The authors describe algorithms to control dynamic attenuators in CT and compare their performance using simulated scans. Dynamic attenuators are prepatient beam shaping filters that modulate the distribution of x-ray fluence incident on the patient on a view-by-view basis. These attenuators can reduce dose while improving key image quality metrics such as peak or mean variance. In each view, the attenuator presents several degrees of freedom which may be individually adjusted. The total number of degrees of freedom across all views is very large, making many optimization techniques impractical. The authors develop a theory for optimally controlling these attenuators. Special attention is paid to a theoretically perfect attenuator which controls the fluence for each ray individually, but the authors also investigate and compare three other, practical attenuator designs which have been previously proposed: the piecewise-linear attenuator, the translating attenuator, and the double wedge attenuator. The authors pose and solve the optimization problems of minimizing the mean and peak variance subject to a fixed dose limit. For a perfect attenuator and mean variance minimization, this problem can be solved in simple, closed form. For other attenuator designs, the problem can be decomposed into separate problems for each view to greatly reduce the computational complexity. Peak variance minimization can be approximately solved using iterated, weighted mean variance (WMV) minimization. Also, the authors develop heuristics for the perfect and piecewise-linear attenuators which do not require a priori knowledge of the patient anatomy. The authors compare these control algorithms on different types of dynamic attenuators using simulated raw data from forward projected DICOM files of a thorax and an abdomen. The translating and double wedge attenuators reduce dose by an average of 30% relative to current techniques (bowtie filter with tube current modulation) without
Dynamic Control of Airport Departures: Algorithm Development and Field Evaluation
Simaiakis, Ioannis; Balakrishnan, Hamsa
2012-01-01
Surface congestion leads to significant increases in taxi times and fuel burn at major airports. In this paper, we formulate the airport surface congestion management problem as a dynamic control problem. We address two main challenges: the random delay between actuation (at the gate) and the server being controlled (the runway), and the need to develop control strategies that can be implemented in practice by human air traffic controllers. The second requirement necessitates a strategy that ...
Directory of Open Access Journals (Sweden)
Wanke Cao
2017-10-01
Full Text Available All-wheel-independent-drive electric vehicles (AWID-EVs have considerable advantages in terms of energy optimization, drivability and driving safety due to the remarkable actuation flexibility of electric motors. However, in their current implementations, various real-time data in the vehicle control system are exchanged via a controller area network (CAN, which causes network congestion and network-induced delays. These problems could lead to systemic instability and make the system integration difficult. The goal of this paper is to provide a design methodology that can cope with all these challenges for the lateral motion control of AWID-EVs. Firstly, a continuous-time model of an AWID-EV is derived. Then an expression for determining upper and lower bounds on the delays caused by CAN is presented and with which a discrete-time model of the closed-loop CAN system is derived. An expression on the bandwidth utilization is introduced as well. Thirdly, a co-design based scheme combining a period-dependent linear quadratic regulator (LQR and a dynamic period scheduler is designed for the resulting model and the stability criterion is also derived. The results of simulations and hard-in-loop (HIL experiments show that the proposed methodology can effectively guarantee the stability of the vehicle lateral motion control while obviously declining the network congestion.
Automatic control algorithm effects on energy production
Mcnerney, G. M.
1981-01-01
A computer model was developed using actual wind time series and turbine performance data to simulate the power produced by the Sandia 17-m VAWT operating in automatic control. The model was used to investigate the influence of starting algorithms on annual energy production. The results indicate that, depending on turbine and local wind characteristics, a bad choice of a control algorithm can significantly reduce overall energy production. The model can be used to select control algorithms and threshold parameters that maximize long term energy production. The results from local site and turbine characteristics were generalized to obtain general guidelines for control algorithm design.
Energy Technology Data Exchange (ETDEWEB)
Aziz, H. M. Abdul [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Zhu, Feng [Purdue University, West Lafayette, IN (United States). Lyles School of Civil Engineering; Ukkusuri, Satish V. [Purdue University, West Lafayette, IN (United States). Lyles School of Civil Engineering
2017-10-04
Here, this research applies R-Markov Average Reward Technique based reinforcement learning (RL) algorithm, namely RMART, for vehicular signal control problem leveraging information sharing among signal controllers in connected vehicle environment. We implemented the algorithm in a network of 18 signalized intersections and compare the performance of RMART with fixed, adaptive, and variants of the RL schemes. Results show significant improvement in system performance for RMART algorithm with information sharing over both traditional fixed signal timing plans and real time adaptive control schemes. Additionally, the comparison with reinforcement learning algorithms including Q learning and SARSA indicate that RMART performs better at higher congestion levels. Further, a multi-reward structure is proposed that dynamically adjusts the reward function with varying congestion states at the intersection. Finally, the results from test networks show significant reduction in emissions (CO, CO_{2}, NO_{x}, VOC, PM_{10}) when RL algorithms are implemented compared to fixed signal timings and adaptive schemes.
Fuzzy logic congestion control in IEEE 802.11 wireless local area networks: A performance evaluation
CSIR Research Space (South Africa)
Nyirenda, CN
2007-09-01
Full Text Available performance with that of ARED and the Droptail mechanism. Simulation results show that the FLCD algorithm helps to minimize UDP traffic delay, packet loss rates. In terms of throughput, the FLCD algorithm exhibits similar performance to the other schemes. Its...
Joint control algorithm in access network
Institute of Scientific and Technical Information of China (English)
2008-01-01
To deal with long probing delay and inaccurate probing results in the endpoint admission control method,a joint local and end-to-end admission control algorithm is proposed,which introduces local probing of access network besides end-to-end probing.Through local probing,the algorithm accurately estimated the resource status of the access network.Simulation shows that this algorithm can improve admission control performance and reduce users' average waiting time when the access network is heavily loaded.
A Review on Natural Ventilation-enabling Façade Noise Control Devices for Congested High-Rise Cities
Directory of Open Access Journals (Sweden)
Shiu-Keung Tang
2017-02-01
Full Text Available This review summarizes the current status of the research and development of natural ventilation-enabling noise control devices for use on the façades of high-rise residential buildings in congested cities. These devices are important for a sustainable urbanized city, as they are supposed to offer good acoustical protection to citizens, allowing for an acceptable level of natural ventilation inside residential units; energy for mechanical ventilation can then be saved. From the information presented in the existing literature, it is concluded that protrusive devices, such as lintels and balconies, are not effective noise screening devices, even if they are installed with sound absorbers and/or reflectors, under the effect of city reverberation. On the contrary, plenum windows and similar structures, which are plenum structures with a staggered air inlet and outlet, are interesting alternatives that are worth rigorous considerations.
Congestion Pricing for Aircraft Pushback Slot Allocation
Zhang, Yaping
2017-01-01
In order to optimize aircraft pushback management during rush hour, aircraft pushback slot allocation based on congestion pricing is explored while considering monetary compensation based on the quality of the surface operations. First, the concept of the “external cost of surface congestion” is proposed, and a quantitative study on the external cost is performed. Then, an aircraft pushback slot allocation model for minimizing the total surface cost is established. An improved discrete differential evolution algorithm is also designed. Finally, a simulation is performed on Xinzheng International Airport using the proposed model. By comparing the pushback slot control strategy based on congestion pricing with other strategies, the advantages of the proposed model and algorithm are highlighted. In addition to reducing delays and optimizing the delay distribution, the model and algorithm are better suited for use for actual aircraft pushback management during rush hour. Further, it is also observed they do not result in significant increases in the surface cost. These results confirm the effectiveness and suitability of the proposed model and algorithm. PMID:28114429
Algorithms for orbit control on SPEAR
International Nuclear Information System (INIS)
Corbett, J.; Keeley, D.; Hettel, R.; Linscott, I.; Sebek, J.
1994-06-01
A global orbit feedback system has been installed on SPEAR to help stabilize the position of the photon beams. The orbit control algorithms depend on either harmonic reconstruction of the orbit or eigenvector decomposition. The orbit motion is corrected by dipole corrector kicks determined from the inverse corrector-to-bpm response matrix. This paper outlines features of these control algorithms as applied to SPEAR
Pinning impulsive control algorithms for complex network
International Nuclear Information System (INIS)
Sun, Wen; Lü, Jinhu; Chen, Shihua; Yu, Xinghuo
2014-01-01
In this paper, we further investigate the synchronization of complex dynamical network via pinning control in which a selection of nodes are controlled at discrete times. Different from most existing work, the pinning control algorithms utilize only the impulsive signals at discrete time instants, which may greatly improve the communication channel efficiency and reduce control cost. Two classes of algorithms are designed, one for strongly connected complex network and another for non-strongly connected complex network. It is suggested that in the strongly connected network with suitable coupling strength, a single controller at any one of the network's nodes can always pin the network to its homogeneous solution. In the non-strongly connected case, the location and minimum number of nodes needed to pin the network are determined by the Frobenius normal form of the coupling matrix. In addition, the coupling matrix is not necessarily symmetric or irreducible. Illustrative examples are then given to validate the proposed pinning impulsive control algorithms
Model based development of engine control algorithms
Dekker, H.J.; Sturm, W.L.
1996-01-01
Model based development of engine control systems has several advantages. The development time and costs are strongly reduced because much of the development and optimization work is carried out by simulating both engine and control system. After optimizing the control algorithm it can be executed
Control algorithms for autonomous robot navigation
International Nuclear Information System (INIS)
Jorgensen, C.C.
1985-01-01
This paper examines control algorithm requirements for autonomous robot navigation outside laboratory environments. Three aspects of navigation are considered: navigation control in explored terrain, environment interactions with robot sensors, and navigation control in unanticipated situations. Major navigation methods are presented and relevance of traditional human learning theory is discussed. A new navigation technique linking graph theory and incidental learning is introduced
A Novel Congestion Detection Scheme in TCP Over OBS Networks
Shihada, Basem
2009-02-01
This paper introduces a novel congestion detection scheme for high-bandwidth TCP flows over optical burst switching (OBS) networks, called statistical additive increase multiplicative decrease (SAIMD). SAIMD maintains and analyzes a number of previous round-trip time (RTTs) at the TCP senders in order to identify the confidence with which a packet loss event is due to network congestion. The confidence is derived by positioning short-term RTT in the spectrum of long-term historical RTTs. The derived confidence corresponding to the packet loss is then taken in the developed policy for TCP congestion window adjustment. We will show through extensive simulation that the proposed scheme can effectively solve the false congestion detection problem and significantly outperform the conventional TCP counterparts without losing fairness. The advantages gained in our scheme are at the expense of introducing more overhead in the SAIMD TCP senders. Based on the proposed congestion control algorithm, a throughput model is formulated, and is further verified by simulation results.
Silvestre, Julio; Montoya, Maria; Bruera, Eduardo; Elsayem, Ahmed
2015-12-01
We describe an exemplary case of congestive heart failure (CHF) symptoms controlled with milrinone. We also analyze the benefits and risks of milrinone administration in an unmonitored setting. We describe the case of a patient with refractory leukemia and end-stage CHF who developed severe dyspnea after discontinuation of milrinone. At that point, despite starting opioids, she had been severely dyspneic and anxious, requiring admission to the palliative care unit (PCU) for symptom control. After negotiation with hospital administrators, milrinone was administered in an unmonitored setting such as the PCU. A multidisciplinary team approach was also provided. Milrinone produced a dramatic improvement in the patient's symptom scores and performance status. The patient was eventually discharged to home hospice on a milrinone infusion with excellent symptom control. This case suggests that milrinone may be of benefit for short-term inpatient administration for dyspnea management, even in unmonitored settings and consequently during hospice in do-not-resuscitate (DNR) patients. This strategy may reduce costs and readmissions to the hospital related to end-stage CHF.
Directory of Open Access Journals (Sweden)
Beibei Wang
2017-01-01
Full Text Available There are many uncertain factors in the modern distribution network, including the access of renewable energy sources and the heavy load level. The existence of these factors has brought challenges to the stability of the power distribution network, as well as increasing the risk of exceeding transmission capacity of distribution lines. The appearance of flexible load control technology provides a new idea to solve the above problems. Air conditioners (ACs account for a great proportion of all loads. In this paper, the model of dispatching AC loads in the regional power grid is constructed, and the direct load control (DLC method is adopted to reduce the load of ACs. An improved tabu search technique is proposed to solve the problem of network dispatch in distribution systems in order to reduce the resistive line losses and to eliminate the transmission congestion in lines under normal operating conditions. The optimal node solution is obtained to find the best location and reduction capacity of ACs for load control. To demonstrate the validity and effectiveness of the proposed method, a test system is studied. The numerical results are also given in this article, which reveal that the proposed method is promising.
Joint QoS and Congestion Control Based on Traffic Prediction in SDN
Directory of Open Access Journals (Sweden)
Mohammad Mahdi Tajiki
2017-12-01
Full Text Available Due to the various network requirements of applications, quality of service (QoS-aware routing plays an important role in the networks. Recently proposed resource allocation algorithms focus on the current traffic matrix, which is not applicable for dynamic networks. In this paper, we exploit an estimation of flow matrix that gives our scheme the ability to sufficiently reduce the total packet loss and simultaneously raise the network throughput. In this way, we mathematically formulate the QoS-aware resource reallocation in software-defined networking (SDN networks based on the traffic prediction. To solve this optimization problem, two schemes are proposed: (i exact solution; and (ii fast suboptimal one. The proposed schemes are compared with the accuracy perspective. Moreover, the impact of prediction on resource reallocation is discussed. In this regard, it is shown that, compared with the conventional scheme, the proposed scheme decreases the packet loss and increases the throughput significantly.
Directory of Open Access Journals (Sweden)
Edgar Talavera
2018-01-01
Full Text Available In recent years, vehicular communications systems have evolved and allowed for the improvement of adaptive cruise control (ACC systems to make them cooperative (cooperative adaptive cruise control, CACC. Conventional ACC systems use sensors on the ego-vehicle, such as radar or computer vision, to generate their behavioral decisions. However, by having vehicle-to-X (V2X onboard communications, the need to incorporate perception in the vehicle is drastically reduced. Thus, in this paper a CACC solution is proposed that only uses communications to make its decisions with the help of previous road mapping. At the same time, a method to develop these maps is presented, combining the information of a computer vision system to correct the positions obtained from the navigation system. In addition, the cut-in and cut-out maneuvers for a CACC platoon are taken into account, showing the tests of these situations in real environments with instrumented vehicles. To show the potential of the system in a larger-scale implementation, simulations of the behavior are provided under dense traffic conditions where the positive impact on the reduction of traffic congestion and fuel consumption is appreciated.
Evaluation of train-speed control algorithms
Energy Technology Data Exchange (ETDEWEB)
Slavik, M.M. [BKS Advantech (Pty.) Ltd., Pretoria (South Africa)
2000-07-01
A relatively simple and fast simulator has been developed and used for the preliminary testing of train cruise-control algorithms. The simulation is done in software on a PC. The simulator is used to gauge the consequences and feasibility of a cruise-control strategy prior to more elaborate testing and evaluation. The tool was used to design and pre-test a train-cruise control algorithm called NSS, which does not require knowledge of exact train mass, vertical alignment, or actual braking force. Only continuous measurements on the speed of the train and electrical current are required. With this modest input, the NSS algorithm effected speed changes smoothly and efficiently for a wide range of operating conditions. (orig.)
VLSI PARTITIONING ALGORITHM WITH ADAPTIVE CONTROL PARAMETER
Directory of Open Access Journals (Sweden)
P. N. Filippenko
2013-03-01
Full Text Available The article deals with the problem of very large-scale integration circuit partitioning. A graph is selected as a mathematical model describing integrated circuit. Modification of ant colony optimization algorithm is presented, which is used to solve graph partitioning problem. Ant colony optimization algorithm is an optimization method based on the principles of self-organization and other useful features of the ants’ behavior. The proposed search system is based on ant colony optimization algorithm with the improved method of the initial distribution and dynamic adjustment of the control search parameters. The experimental results and performance comparison show that the proposed method of very large-scale integration circuit partitioning provides the better search performance over other well known algorithms.
International Nuclear Information System (INIS)
Cheng Sheng-Yi; Liu Wen-Jin; Chen Shan-Qiu; Dong Li-Zhi; Yang Ping; Xu Bing
2015-01-01
Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n 2 ) ∼ O(n 3 ) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ∼ (O(n) 3/2 ), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. (paper)
DEFF Research Database (Denmark)
Hu, Junjie; Si, Chengyong; Lind, Morten
2016-01-01
In this paper, a hierarchical management system is proposed to integrate electric vehicles (EVs) into a distribution grid. Three types of actors are included in the system: Distribution system operators (DSOs), Fleet operators (FOs) and EV owners. In contrast to a typical hierarchical control sys...
Figuring Control in the Algorithmic Era
DEFF Research Database (Denmark)
Markham, Annette; Bossen, Claus
Drawing on actor network theory, we follow how algorithms, information, selfhood and identity-for-others tangle in interesting and unexpected ways. Starting with simple moments in everyday life that might be described as having implications for ‘control,’ we focus attention on the ways in which t...
Porciello, F; Rishniw, M; Ljungvall, I; Ferasin, L; Haggstrom, J; Ohad, D G
2016-01-01
Sleeping and resting respiratory rates (SRR and RRR, respectively) are commonly used to monitor dogs and cats with left-sided cardiac disease and to identify animals with left-sided congestive heart failure (L-CHF). Dogs and cats with subclinical heart disease have SRRmean values dogs and cats with CHF that is well controlled with medical therapy. In this study, SRR and RRR were measured by the owners of 51 dogs and 22 cats with stable, well-controlled CHF. Median canine SRRmean was 20 breaths/min (7-39 breaths/min); eight dogs were ≥25 breaths/min and one dog only was ≥30 breaths/min. Canine SRRmean was unrelated to pulmonary hypertension or diuretic dose. Median feline SRRmean was 20 breaths/min (13-31 breaths/min); four cats were ≥25 breaths/min and only one cat was ≥30 breaths/min. Feline SRRmean was unrelated to diuretic dose. SRR remained stable during collection in both species with little day-to-day variability. The median canine RRRmean was 24 breaths/min (12-44 breaths/min), 17 were ≥25 breaths/min, seven were ≥30 breaths/min, two were >40 breaths/min. Median feline RRRmean was 24 breaths/min (15-45 breaths/min); five cats had RRRmean ≥25 breaths/min; one had ≥30 breaths/min, and two had ≥40 breaths/min. These data suggest that most dogs and cats with CHF that is medically well-controlled and stable have SRRmean and RRRmean dogs and cats. Copyright © 2015 Elsevier Ltd. All rights reserved.
Congestive index of portal vein
International Nuclear Information System (INIS)
Kim, Won Ho; Kim, H. K.; Lee, S. C.; Han, S. H.; Han, K. H.; Chung, J. B.; Choi, H. J.
1989-01-01
In patients with portal hypertension, the blood flow volume is maintained despite decreased blood flow velocity due to enlargement of the vascular cross sectional area. Thus, the 'congestion index' of the portal vein, which is the ratio between the cross sectional area (cm2) and the blood flow velocity (cm/sec) determined by a Doppler ultrasonography, may be a sensitive index by which to assess portal hypertension. We performed Doppler ultrasonography on 24 normal subjects, 14 patients with biopsy proved chronic active hepatitis and 55 patients with liver cirrhosis in order to assess the diagnostic value of the congestion index. The cross sectional area of the portal vein was significantly enlarged and the mean blood flow velocity was significantly reduced in patients with liver cirrhosis compared with controls. However, the blood flow volume was no difference. The congestion index of the portal vein was significantly increased in patients with liver cirrhosis (0.113+0.035) compared with patients with chronic active hepatitis(0.078+0.029) (p<0.001) and controls (0.053+0.016) (p<0.001). The sensitivity, specificity and predictability of the congestion index for detection of patients with the cirrhosis of the liver were 76.4%, 100% and 100% respectively, when the normal range was set at mean+2SD. The results suggest that the congestion index of the portal vein may pla a significant role in diagnosis of portal hypertensive patients
Pinning impulsive control algorithms for complex network
Energy Technology Data Exchange (ETDEWEB)
Sun, Wen [School of Information and Mathematics, Yangtze University, Jingzhou 434023 (China); Lü, Jinhu [Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190 (China); Chen, Shihua [College of Mathematics and Statistics, Wuhan University, Wuhan 430072 (China); Yu, Xinghuo [School of Electrical and Computer Engineering, RMIT University, Melbourne VIC 3001 (Australia)
2014-03-15
In this paper, we further investigate the synchronization of complex dynamical network via pinning control in which a selection of nodes are controlled at discrete times. Different from most existing work, the pinning control algorithms utilize only the impulsive signals at discrete time instants, which may greatly improve the communication channel efficiency and reduce control cost. Two classes of algorithms are designed, one for strongly connected complex network and another for non-strongly connected complex network. It is suggested that in the strongly connected network with suitable coupling strength, a single controller at any one of the network's nodes can always pin the network to its homogeneous solution. In the non-strongly connected case, the location and minimum number of nodes needed to pin the network are determined by the Frobenius normal form of the coupling matrix. In addition, the coupling matrix is not necessarily symmetric or irreducible. Illustrative examples are then given to validate the proposed pinning impulsive control algorithms.
FPGA Congestion-Driven Placement Refinement
Energy Technology Data Exchange (ETDEWEB)
Vicente de, J.
2005-07-01
The routing congestion usually limits the complete proficiency of the FPGA logic resources. A key question can be formulated regarding the benefits of estimating the congestion at placement stage. In the last years, it is gaining acceptance the idea of a detailed placement taking into account congestion. In this paper, we resort to the Thermodynamic Simulated Annealing (TSA) algorithm to perform a congestion-driven placement refinement on the top of the common Bounding-Box pre optimized solution. The adaptive properties of TSA allow the search to preserve the solution quality of the pre optimized solution while improving other fine-grain objectives. Regarding the cost function two approaches have been considered. In the first one Expected Occupation (EO), a detailed probabilistic model to account for channel congestion is evaluated. We show that in spite of the minute detail of EO, the inherent uncertainty of this probabilistic model impedes to relieve congestion beyond the sole application of the Bounding-Box cost function. In the second approach we resort to the fast Rectilinear Steiner Regions algorithm to perform not an estimation but a measurement of the global routing congestion. This second strategy allows us to successfully reduce the requested channel width for a set of benchmark circuits with respect to the widespread Versatile Place and Route (VPR) tool. (Author) 31 refs.
Chemical optimization algorithm for fuzzy controller design
Astudillo, Leslie; Castillo, Oscar
2014-01-01
In this book, a novel optimization method inspired by a paradigm from nature is introduced. The chemical reactions are used as a paradigm to propose an optimization method that simulates these natural processes. The proposed algorithm is described in detail and then a set of typical complex benchmark functions is used to evaluate the performance of the algorithm. Simulation results show that the proposed optimization algorithm can outperform other methods in a set of benchmark functions. This chemical reaction optimization paradigm is also applied to solve the tracking problem for the dynamic model of a unicycle mobile robot by integrating a kinematic and a torque controller based on fuzzy logic theory. Computer simulations are presented confirming that this optimization paradigm is able to outperform other optimization techniques applied to this particular robot application
Algorithm for Controlling a Centrifugal Compressor
Benedict, Scott M.
2004-01-01
An algorithm has been developed for controlling a centrifugal compressor that serves as the prime mover in a heatpump system. Experimental studies have shown that the operating conditions for maximum compressor efficiency are close to the boundary beyond which surge occurs. Compressor surge is a destructive condition in which there are instantaneous reversals of flow associated with a high outlet-to-inlet pressure differential. For a given cooling load, the algorithm sets the compressor speed at the lowest possible value while adjusting the inlet guide vane angle and diffuser vane angle to maximize efficiency, subject to an overriding requirement to prevent surge. The onset of surge is detected via the onset of oscillations of the electric current supplied to the compressor motor, associated with surge-induced oscillations of the torque exerted by and on the compressor rotor. The algorithm can be implemented in any of several computer languages.
Search algorithms, hidden labour and information control
Directory of Open Access Journals (Sweden)
Paško Bilić
2016-06-01
Full Text Available The paper examines some of the processes of the closely knit relationship between Google’s ideologies of neutrality and objectivity and global market dominance. Neutrality construction comprises an important element sustaining the company’s economic position and is reflected in constant updates, estimates and changes to utility and relevance of search results. Providing a purely technical solution to these issues proves to be increasingly difficult without a human hand in steering algorithmic solutions. Search relevance fluctuates and shifts through continuous tinkering and tweaking of the search algorithm. The company also uses third parties to hire human raters for performing quality assessments of algorithmic updates and adaptations in linguistically and culturally diverse global markets. The adaptation process contradicts the technical foundations of the company and calculations based on the initial Page Rank algorithm. Annual market reports, Google’s Search Quality Rating Guidelines, and reports from media specialising in search engine optimisation business are analysed. The Search Quality Rating Guidelines document provides a rare glimpse into the internal architecture of search algorithms and the notions of utility and relevance which are presented and structured as neutral and objective. Intertwined layers of ideology, hidden labour of human raters, advertising revenues, market dominance and control are discussed throughout the paper.
Gradient algorithm applied to laboratory quantum control
International Nuclear Information System (INIS)
Roslund, Jonathan; Rabitz, Herschel
2009-01-01
The exploration of a quantum control landscape, which is the physical observable as a function of the control variables, is fundamental for understanding the ability to perform observable optimization in the laboratory. For high control variable dimensions, trajectory-based methods provide a means for performing such systematic explorations by exploiting the measured gradient of the observable with respect to the control variables. This paper presents a practical, robust, easily implemented statistical method for obtaining the gradient on a general quantum control landscape in the presence of noise. In order to demonstrate the method's utility, the experimentally measured gradient is utilized as input in steepest-ascent trajectories on the landscapes of three model quantum control problems: spectrally filtered and integrated second harmonic generation as well as excitation of atomic rubidium. The gradient algorithm achieves efficiency gains of up to approximately three times that of the standard genetic algorithm and, as such, is a promising tool for meeting quantum control optimization goals as well as landscape analyses. The landscape trajectories directed by the gradient should aid in the continued investigation and understanding of controlled quantum phenomena.
An efficient control algorithm for nonlinear systems
International Nuclear Information System (INIS)
Sinha, S.
1990-12-01
We suggest a scheme to step up the efficiency of a recently proposed adaptive control algorithm, which is remarkably effective for regulating nonlinear systems. The technique involves monitoring of the ''stiffness of control'' to get maximum gain while maintaining a predetermined accuracy. The success of the procedure is demonstrated for the case of the logistic map, where we show that the improvement in performance is often factors of tens, and for small control stiffness, even factors of hundreds. (author). 4 refs, 1 fig., 1 tab
Cheng, Sheng-Yi; Liu, Wen-Jin; Chen, Shan-Qiu; Dong, Li-Zhi; Yang, Ping; Xu, Bing
2015-08-01
Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n2) ˜ O(n3) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ˜ (O(n)3/2), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. Project supported by the National Key Scientific and Research Equipment Development Project of China (Grant No. ZDYZ2013-2), the National Natural Science Foundation of China (Grant No. 11173008), and the Sichuan Provincial Outstanding Youth Academic Technology Leaders Program, China (Grant No. 2012JQ0012).
Adaptive Control Algorithm of the Synchronous Generator
Directory of Open Access Journals (Sweden)
Shevchenko Victor
2017-01-01
Full Text Available The article discusses the the problem of controlling a synchronous generator, namely, maintaining the stability of the control object in the conditions of occurrence of noise and disturbances in the regulatory process. The model of a synchronous generator is represented by a system of differential equations of Park-Gorev, where state variables are computed relative to synchronously rotating d, q-axis. Management of synchronous generator is proposed to organize on the basis of the position-path control using algorithms to adapt with the reference model. Basic control law directed on the stabilizing indicators the frequency generated by the current and the required power level, which is achieved by controlling the mechanical torque on the shaft of the turbine and the value of the excitation voltage of the synchronous generator. Modification of the classic adaptation algorithm using the reference model, allowing to minimize the error of the reference regulation and the model under investigation within the prescribed limits, produced by means of the introduction of additional variables controller adaptation in the model. Сarried out the mathematical modeling of control provided influence on the studied model of continuous nonlinear and unmeasured the disturbance. Simulation results confirm the high level accuracy of tracking and adaptation investigated model with respect to the reference, and the present value of the loop error depends on parameters performance of regulator.
Avoiding congestion in recommender systems
International Nuclear Information System (INIS)
Ren, Xiaolong; Lü, Linyuan; Liu, Runran; Zhang, Jianlin
2014-01-01
Recommender systems use the historical activities and personal profiles of users to uncover their preferences and recommend objects. Most of the previous methods are based on objects’ (and/or users’) similarity rather than on their difference. Such approaches are subject to a high risk of increasingly exposing users to a narrowing band of popular objects. As a result, a few objects may be recommended to an enormous number of users, resulting in the problem of recommendation congestion, which is to be avoided, especially when the recommended objects are limited resources. In order to quantitatively measure a recommendation algorithm's ability to avoid congestion, we proposed a new metric inspired by the Gini index, which is used to measure the inequality of the individual wealth distribution in an economy. Besides this, a new recommendation method called directed weighted conduction (DWC) was developed by considering the heat conduction process on a user–object bipartite network with different thermal conductivities. Experimental results obtained for three benchmark data sets showed that the DWC algorithm can effectively avoid system congestion, and greatly improve the novelty and diversity, while retaining relatively high accuracy, in comparison with the state-of-the-art methods. (paper)
DEFF Research Database (Denmark)
Fosgerau, Mogens
2010-01-01
This paper considers the impact of random delays during a repeatedly occurring demand peak in a congested facility, such as an airport or an urban road. Congestion is described in the form of a dynamic queue using the Vickrey bottleneck model and assuming Nash equilibrium in departure times. Ever...
Application of genetic algorithm to control design
International Nuclear Information System (INIS)
Lee, Yoon Joon; Cho, Kyung Ho
1995-01-01
A classical PID controller is designed by applying the GA (Genetic Algorithm) which searches the optimal parameters through three major operators of reproduction, crossover and mutation under the given constraints. The GA could minimize the designer's interference and the whole design process could easily be automated. In contrast with other traditional PID design methods which allows for the system output responses only, the design with the GA can take account of the magnitude or the rate of change of control input together with the output responses, which reflects the more realistic situations. Compared with other PIDs designed by the traditional methods such as Ziegler and analytic, the PID by the GA shows the superior response characteristics to those of others with the least control input energy
Nonlinear model predictive control theory and algorithms
Grüne, Lars
2017-01-01
This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...
MPPT algorithm for voltage controlled PV inverters
DEFF Research Database (Denmark)
Kerekes, Tamas; Teodorescu, Remus; Liserre, Marco
2008-01-01
This paper presents a novel concept for an MPPT that can be used in case of a voltage controlled grid connected PV inverters. In case of single-phase systems, the 100 Hz ripple in the AC power is also present on the DC side. Depending on the DC link capacitor, this power fluctuation can be used t...... to track the MPP of the PV array, using the information that at MPP the power oscillations are very small. In this way the algorithm can detect the fact that the current working point is at the MPP, for the current atmospheric conditions....
Seismic active control by a heuristic-based algorithm
International Nuclear Information System (INIS)
Tang, Yu.
1996-01-01
A heuristic-based algorithm for seismic active control is generalized to permit consideration of the effects of control-structure interaction and actuator dynamics. Control force is computed at onetime step ahead before being applied to the structure. Therefore, the proposed control algorithm is free from the problem of time delay. A numerical example is presented to show the effectiveness of the proposed control algorithm. Also, two indices are introduced in the paper to assess the effectiveness and efficiency of control laws
Control algorithms and applications of the wavefront sensorless adaptive optics
Ma, Liang; Wang, Bin; Zhou, Yuanshen; Yang, Huizhen
2017-10-01
Compared with the conventional adaptive optics (AO) system, the wavefront sensorless (WFSless) AO system need not to measure the wavefront and reconstruct it. It is simpler than the conventional AO in system architecture and can be applied to the complex conditions. Based on the analysis of principle and system model of the WFSless AO system, wavefront correction methods of the WFSless AO system were divided into two categories: model-free-based and model-based control algorithms. The WFSless AO system based on model-free-based control algorithms commonly considers the performance metric as a function of the control parameters and then uses certain control algorithm to improve the performance metric. The model-based control algorithms include modal control algorithms, nonlinear control algorithms and control algorithms based on geometrical optics. Based on the brief description of above typical control algorithms, hybrid methods combining the model-free-based control algorithm with the model-based control algorithm were generalized. Additionally, characteristics of various control algorithms were compared and analyzed. We also discussed the extensive applications of WFSless AO system in free space optical communication (FSO), retinal imaging in the human eye, confocal microscope, coherent beam combination (CBC) techniques and extended objects.
Efficiency of equilibria in uniform matroid congestion games
de Jong, Jasper; Klimm, Max; Uetz, Marc Jochen
2016-01-01
Network routing games, and more generally congestion games play a central role in algorithmic game theory, comparable to the role of the traveling salesman problem in combinatorial optimization. It is known that the price of anarchy is independent of the network topology for non-atomic congestion
Packet-Based Control Algorithms for Cooperative Surveillance and Reconnaissance
National Research Council Canada - National Science Library
Murray, Richard M
2007-01-01
..., and repeated transmissions. Results include analysis and design of estimation and control algorithms in the presence of packet loss and across multi-hop data networks, distributed estimation and sensor fusion algorithms...
Multiobjective Genetic Algorithm applied to dengue control.
Florentino, Helenice O; Cantane, Daniela R; Santos, Fernando L P; Bannwart, Bettina F
2014-12-01
Dengue fever is an infectious disease caused by a virus of the Flaviridae family and transmitted to the person by a mosquito of the genus Aedes aegypti. This disease has been a global public health problem because a single mosquito can infect up to 300 people and between 50 and 100 million people are infected annually on all continents. Thus, dengue fever is currently a subject of research, whether in the search for vaccines and treatments for the disease or efficient and economical forms of mosquito control. The current study aims to study techniques of multiobjective optimization to assist in solving problems involving the control of the mosquito that transmits dengue fever. The population dynamics of the mosquito is studied in order to understand the epidemic phenomenon and suggest strategies of multiobjective programming for mosquito control. A Multiobjective Genetic Algorithm (MGA_DENGUE) is proposed to solve the optimization model treated here and we discuss the computational results obtained from the application of this technique. Copyright © 2014 Elsevier Inc. All rights reserved.
Rate-control algorithms testing by using video source model
DEFF Research Database (Denmark)
Belyaev, Evgeny; Turlikov, Andrey; Ukhanova, Anna
2008-01-01
In this paper the method of rate control algorithms testing by the use of video source model is suggested. The proposed method allows to significantly improve algorithms testing over the big test set.......In this paper the method of rate control algorithms testing by the use of video source model is suggested. The proposed method allows to significantly improve algorithms testing over the big test set....
International Nuclear Information System (INIS)
Kassis, E.; Jacobsen, T.N.; Mogensen, F.; Amtorp, O.
1986-01-01
Mechanisms controlling forearm muscle vascular resistance (FMVR) during postural changes were investigated in seven patients with severe congestive heart failure (CHF) and in seven control subjects with unimpaired left ventricular function. Relative brachioradial muscle blood flow was determined by the local 133 Xe-washout technique. Unloading of baroreceptors with use of 45 degree upright tilt was comparably obtained in the patients with CHF and control subjects. Control subjects had substantially increased FMVR and heart rate to maintain arterial pressure whereas patients with CHF had decreased FMVR by 51 +/- 11% and had no increase in heart rate despite a fall in arterial pressure during upright tilt. The autoregulatory and local vasoconstrictor reflex responsiveness during postural changes in forearm vascular pressures were intact in both groups. In the patients with CHF, the left axillary nerve plexus was blocked by local anesthesia. No alterations in forearm vascular pressures were observed. This blockade preserved the local regulation of FMVR but reversed the vasodilator response to upright tilt as FMVR increased by 30 +/- 7% (p less than .02). Blockade of central neural impulses to this limb combined with brachial arterial infusions of phentolamine completely abolished the humoral vasoconstriction in the tilted position. Infusions of propranolol to the contralateral brachial artery that did not affect baseline values of heart rate, arterial pressure, or the local reflex regulation of FMVR reversed the abnormal vasodilator response to upright tilt as FMVR increased by 42 +/- 12% (p less than .02). Despite augmented baseline values, forearm venous but not arterial plasma levels of epinephrine increased in the tilted position, as did arteri rather than venous plasma concentrations of norepinephrine in these patients
Implementation of fuzzy logic control algorithm in embedded ...
African Journals Online (AJOL)
Fuzzy logic control algorithm solves problems that are difficult to address with traditional control techniques. This paper describes an implementation of fuzzy logic control algorithm using inexpensive hardware as well as how to use fuzzy logic to tackle a specific control problem without any special software tools. As a case ...
Desk Congest Desktop Congesting Software for Desktop Clutter Congestion
Directory of Open Access Journals (Sweden)
Solomon A. Adepoju
2015-06-01
Full Text Available Abstract The computer desktop environment is a working environment which can be likened unto a users desk in homes and offices. Often times the computer desktop get cluttered with files either as shortcuts used for quick links files stored temporarily to be accessed later or just being dumped there for no vivid reasons. However previous researches have shown that cluttered desktop affects users productivity and getting these files organized is a laborious task for most users. To be able to conveniently alleviate the effect clutters have on users performances and productivity there is need for third party software that will help get the desktop environment organized in a logical and efficient manner. It is to this end that desktop decongesting software is being designed and implemented to help curb clutter problems which existing tools have only partially addressed. The system is designed using Visual Basic .Net and it proves to be effective in tackling desktop congestion problem.
Photovoltaic Cells Mppt Algorithm and Design of Controller Monitoring System
Meng, X. Z.; Feng, H. B.
2017-10-01
This paper combined the advantages of each maximum power point tracking (MPPT) algorithm, put forward a kind of algorithm with higher speed and higher precision, based on this algorithm designed a maximum power point tracking controller with ARM. The controller, communication technology and PC software formed a control system. Results of the simulation and experiment showed that the process of maximum power tracking was effective, and the system was stable.
Maintenance of Process Control Algorithms based on Dynamic Program Slicing
DEFF Research Database (Denmark)
Hansen, Ole Fink; Andersen, Nils Axel; Ravn, Ole
2010-01-01
Today’s industrial control systems gradually lose performance after installation and must be regularly maintained by means of adjusting parameters and modifying the control algorithm, in order to regain high performance. Industrial control algorithms are complex software systems, and it is partic...
PSO Algorithm for an Optimal Power Controller in a Microgrid
Al-Saedi, W.; Lachowicz, S.; Habibi, D.; Bass, O.
2017-07-01
This paper presents the Particle Swarm Optimization (PSO) algorithm to improve the quality of the power supply in a microgrid. This algorithm is proposed for a real-time selftuning method that used in a power controller for an inverter based Distributed Generation (DG) unit. In such system, the voltage and frequency are the main control objectives, particularly when the microgrid is islanded or during load change. In this work, the PSO algorithm is implemented to find the optimal controller parameters to satisfy the control objectives. The results show high performance of the applied PSO algorithm of regulating the microgrid voltage and frequency.
Directory of Open Access Journals (Sweden)
A. R. Moradi
2017-03-01
Full Text Available Congestion and overloading for lines are the main problems in the exploitation of power grids. The consequences of these problems in deregulated systems can be mentioned as sudden jumps in prices in some parts of the power system, lead to an increase in market power and reduction of competition in it. FACTS devices are efficient, powerful and economical tools in controlling power flows through transmission lines that play a fundamental role in congestion management. However, after removing congestion, power systems due to targeting security restrictions may be managed with a lower voltage or transient stability rather than before removing. Thus, power system stability should be considered within the construction of congestion management. In this paper, a multi-objective structure is presented for congestion management that simultaneously optimizes goals such as total operating cost, voltage and transient security. In order to achieve the desired goals, locating and sizing of series FACTS devices are done with using components of nodal prices and the newly developed grey wolf optimizer (GWO algorithm, respectively. In order to evaluate reliability of mentioned approaches, a simulation is done on the 39-bus New England network.
Demonstration of Market-Based Real-Time Electricity Pricing on a Congested Feeder
DEFF Research Database (Denmark)
Larsen, Emil Mahler; Pinson, Pierre; le Ray, Guillaume
2015-01-01
Congestion management can delay grid reinforcements needed due to the growth of distributed technologies like photovoltaics and electric vehicles. This paper presents a method of congestion management for low voltage feeders using indirect control from the smart grid demonstration EcoGrid EU, where...... prices to 1900 houses, with a virtual feeder of 28 houses receiving congestion pricing. Simulations are used to calculate the cost from using this congestion management method, while demonstration results indicate that congestion can be managed successfully....
Transmission Congestion Management using a Wind Integrated Compressed Air Energy Storage System
Directory of Open Access Journals (Sweden)
S. Gope
2017-08-01
Full Text Available Transmission congestion is a vital problem in the power system security and reliability sector. To ensure the stable operation of the system, a congestion free power network is desirable. In this paper, a new Congestion Management (CM technique, the Wind integrated Compressed Air Energy Storage (WCAES system is used to alleviate transmission congestion and to minimize congestion mitigation cost. The CM problem has been solved by using the Generator Sensitivity Factor (GSF and the Bus Sensitivity Factor (BSF. BSF is used for finding the optimal location of WCAES in the system. GSF with a Moth Flame Optimization (MFO algorithm is used for rescheduling the generators to alleviate congestion and to minimize congestion cost by improving security margin. The impact of the WCAES system is tested with a 39 bus system. To validate this approach, the same problem has been solved with a Particle Swarm Optimization (PSO algorithm and the obtained results are compared with the ones from the MFO algorithm.
Research on Congestion Pricing in Multimode Traffic considering Delay and Emission
Directory of Open Access Journals (Sweden)
Hongna Dai
2015-01-01
Full Text Available Rapid development of urbanization and automation has resulted in serious urban traffic congestion and air pollution problems in many Chinese cities recently. As a traffic demand management strategy, congestion pricing is acknowledged to be effective in alleviating the traffic congestion and improving the efficiency of traffic system. This paper proposes an urban traffic congestion pricing model based on the consideration of transportation network efficiency and environment effects. First, the congestion pricing problem under multimode (i.e., car mode and bus mode urban traffic network condition is investigated. Second, a traffic congestion pricing model based on bilevel programming is formulated for a dual-mode urban transportation network, in which the delay and emission of vehicles are considered. Third, an improved mathematical algorithm combining successive average method with the genetic algorithm is proposed to solve the bilevel programming problem. Finally, a numerical experiment based on a hypothetical network is performed to validate the proposed congestion pricing model and algorithm.
Optimal Pid Controller Design Using Adaptive Vurpso Algorithm
Zirkohi, Majid Moradi
2015-04-01
The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.
Research on intelligent algorithm of electro - hydraulic servo control system
Wang, Yannian; Zhao, Yuhui; Liu, Chengtao
2017-09-01
In order to adapt the nonlinear characteristics of the electro-hydraulic servo control system and the influence of complex interference in the industrial field, using a fuzzy PID switching learning algorithm is proposed and a fuzzy PID switching learning controller is designed and applied in the electro-hydraulic servo controller. The designed controller not only combines the advantages of the fuzzy control and PID control, but also introduces the learning algorithm into the switching function, which makes the learning of the three parameters in the switching function can avoid the instability of the system during the switching between the fuzzy control and PID control algorithms. It also makes the switch between these two control algorithm more smoother than that of the conventional fuzzy PID.
The research on algorithms for optoelectronic tracking servo control systems
Zhu, Qi-Hai; Zhao, Chang-Ming; Zhu, Zheng; Li, Kun
2016-10-01
The photoelectric servo control system based on PC controllers is mainly used to control the speed and position of the load. This paper analyzed the mathematical modeling and the system identification of the servo system. In the aspect of the control algorithm, the IP regulator, the fuzzy PID, the Active Disturbance Rejection Control (ADRC) and the adaptive algorithms were compared and analyzed. The PI-P control algorithm was proposed in this paper, which not only has the advantages of the PI regulator that can be quickly saturated, but also overcomes the shortcomings of the IP regulator. The control system has a good starting performance and the anti-load ability in a wide range. Experimental results show that the system has good performance under the guarantee of the PI-P control algorithm.
Making the Traffic Operations Case for Congestion Pricing: Operational Impacts of Congestion Pricing
Energy Technology Data Exchange (ETDEWEB)
Chin, Shih-Miao [ORNL; Hu, Patricia S [ORNL; Davidson, Diane [ORNL
2011-02-01
Congestion begins when an excess of vehicles on a segment of roadway at a given time, resulting in speeds that are significantly slower than normal or 'free flow' speeds. Congestion often means stop-and-go traffic. The transition occurs when vehicle density (the number of vehicles per mile in a lane) exceeds a critical level. Once traffic enters a state of congestion, recovery or time to return to a free-flow state is lengthy; and during the recovery process, delay continues to accumulate. The breakdown in speed and flow greatly impedes the efficient operation of the freeway system, resulting in economic, mobility, environmental and safety problems. Freeways are designed to function as access-controlled highways characterized by uninterrupted traffic flow so references to freeway performance relate primarily to the quality of traffic flow or traffic conditions as experienced by users of the freeway. The maximum flow or capacity of a freeway segment is reached while traffic is moving freely. As a result, freeways are most productive when they carry capacity flows at 60 mph, whereas lower speeds impose freeway delay, resulting in bottlenecks. Bottlenecks may be caused by physical disruptions, such as a reduced number of lanes, a change in grade, or an on-ramp with a short merge lane. This type of bottleneck occurs on a predictable or 'recurrent' basis at the same time of day and same day of week. Recurrent congestion totals 45% of congestion and is primarily from bottlenecks (40%) as well as inadequate signal timing (5%). Nonrecurring bottlenecks result from crashes, work zone disruptions, adverse weather conditions, and special events that create surges in demand and that account for over 55% of experienced congestion. Figure 1.1 shows that nonrecurring congestion is composed of traffic incidents (25%), severe weather (15%), work zones, (10%), and special events (5%). Between 1995 and 2005, the average percentage change in increased peak traveler
Telephony Over IP: A QoS Measurement-Based End to End Control Algorithm
Directory of Open Access Journals (Sweden)
Luigi Alcuri
2004-12-01
Full Text Available This paper presents a method for admitting voice calls in Telephony over IP (ToIP scenarios. This method, called QoS-Weighted CAC, aims to guarantee Quality of Service to telephony applications. We use a measurement-based call admission control algorithm, which detects network congested links through a feedback on overall link utilization. This feedback is based on the measures of packet delivery latencies related to voice over IP connections at the edges of the transport network. In this way we introduce a close loop control method, which is able to auto-adapt the quality margin on the basis of network load and specific service level requirements. Moreover we evaluate the difference in performance achieved by different Queue management configurations to guarantee Quality of Service to telephony applications, in which our goal was to evaluate the weight of edge router queue configuration in complex and real-like telephony over IP scenario. We want to compare many well-know queue scheduling algorithms, such as SFQ, WRR, RR, WIRR, and Priority. This comparison aims to locate queue schedulers in a more general control scheme context where different elements such as DiffServ marking and Admission control algorithms contribute to the overall Quality of Service required by real-time voice conversations. By means of software simulations we want to compare this solution with other call admission methods already described in scientific literature in order to locate this proposed method in a more general control scheme context. On the basis of the results we try to evidence the possible advantages of this QoS-Weighted solution in comparison with other similar CAC solutions ( in particular Measured Sum, Bandwidth Equivalent with Hoeffding Bounds, and Simple Measure CAC, on the planes of complexity, stability, management, tune-ability to service level requirements, and compatibility with actual network implementation.
Model-Free Adaptive Control Algorithm with Data Dropout Compensation
Directory of Open Access Journals (Sweden)
Xuhui Bu
2012-01-01
Full Text Available The convergence of model-free adaptive control (MFAC algorithm can be guaranteed when the system is subject to measurement data dropout. The system output convergent speed gets slower as dropout rate increases. This paper proposes a MFAC algorithm with data compensation. The missing data is first estimated using the dynamical linearization method, and then the estimated value is introduced to update control input. The convergence analysis of the proposed MFAC algorithm is given, and the effectiveness is also validated by simulations. It is shown that the proposed algorithm can compensate the effect of the data dropout, and the better output performance can be obtained.
A controllable sensor management algorithm capable of learning
Osadciw, Lisa A.; Veeramacheneni, Kalyan K.
2005-03-01
Sensor management technology progress is challenged by the geographic space it spans, the heterogeneity of the sensors, and the real-time timeframes within which plans controlling the assets are executed. This paper presents a new sensor management paradigm and demonstrates its application in a sensor management algorithm designed for a biometric access control system. This approach consists of an artificial intelligence (AI) algorithm focused on uncertainty measures, which makes the high level decisions to reduce uncertainties and interfaces with the user, integrated cohesively with a bottom up evolutionary algorithm, which optimizes the sensor network"s operation as determined by the AI algorithm. The sensor management algorithm presented is composed of a Bayesian network, the AI algorithm component, and a swarm optimization algorithm, the evolutionary algorithm. Thus, the algorithm can change its own performance goals in real-time and will modify its own decisions based on observed measures within the sensor network. The definition of the measures as well as the Bayesian network determine the robustness of the algorithm and its utility in reacting dynamically to changes in the global system.
PID controller tuning using metaheuristic optimization algorithms for benchmark problems
Gholap, Vishal; Naik Dessai, Chaitali; Bagyaveereswaran, V.
2017-11-01
This paper contributes to find the optimal PID controller parameters using particle swarm optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA) algorithm. The algorithms were developed through simulation of chemical process and electrical system and the PID controller is tuned. Here, two different fitness functions such as Integral Time Absolute Error and Time domain Specifications were chosen and applied on PSO, GA and SA while tuning the controller. The proposed Algorithms are implemented on two benchmark problems of coupled tank system and DC motor. Finally, comparative study has been done with different algorithms based on best cost, number of iterations and different objective functions. The closed loop process response for each set of tuned parameters is plotted for each system with each fitness function.
Algorithm improvement for phase control of subharmonic buncher
International Nuclear Information System (INIS)
Zhang Junqiang; Yu Luyang; Yin Chongxian; Zhao Minghua; Zhong Shaopeng
2011-01-01
To realize digital phase control of subharmonic buncher,a low level radio frequency control system using down converter, IQ modulator and demodulator techniques, and commercial PXI system, was developed on the platform of LabVIEW. A single-neuron adaptive PID (proportional-integral-derivative) control algorithm with ability of self learning was adopted, satisfying the requirements of phase stability. By comparison with the traditional PID algorithm in field testing, the new algorithm has good stability, fast response and strong anti-interference ability. (authors)
Framework for Traffic Congestion Management
Directory of Open Access Journals (Sweden)
Mahmud Hassan TALUKDAR
2013-06-01
Full Text Available Traffic Congestion is one of many serious global problems in all great cities resulted from rapid urbanization which always exert negative externalities upon society. The solution of traffic congestion is highly geocentric and due to its heterogeneous nature, curbing congestion is one of the hard tasks for transport planners. It is not possible to suggest unique traffic congestion management framework which could be absolutely applied for every great cities. Conversely, it is quite feasible to develop a framework which could be used with or without minor adjustment to deal with congestion problem. So, the main aim of this paper is to prepare a traffic congestion mitigation framework which will be useful for urban planners, transport planners, civil engineers, transport policy makers, congestion management researchers who are directly or indirectly involved or willing to involve in the task of traffic congestion management. Literature review is the main source of information of this study. In this paper, firstly, traffic congestion is defined on the theoretical point of view and then the causes of traffic congestion are briefly described. After describing the causes, common management measures, using world- wide, are described and framework for supply side and demand side congestion management measures are prepared.
Numerical Algorithms for Deterministic Impulse Control Models with Applications
Grass, D.; Chahim, M.
2012-01-01
Abstract: In this paper we describe three different algorithms, from which two (as far as we know) are new in the literature. We take both the size of the jump as the jump times as decision variables. The first (new) algorithm considers an Impulse Control problem as a (multipoint) Boundary Value
Dynamic Algorithm for LQGPC Predictive Control
DEFF Research Database (Denmark)
Hangstrup, M.; Ordys, A.W.; Grimble, M.J.
1998-01-01
In this paper the optimal control law is derived for a multi-variable state space Linear Quadratic Gaussian Predictive Controller (LQGPC). A dynamic performance index is utilized resulting in an optimal steady state controller. Knowledge of future reference values is incorporated into the control......In this paper the optimal control law is derived for a multi-variable state space Linear Quadratic Gaussian Predictive Controller (LQGPC). A dynamic performance index is utilized resulting in an optimal steady state controller. Knowledge of future reference values is incorporated...... into the controller design and the solution is derived using the method of Lagrange multipliers. It is shown how well-known GPC controller can be obtained as a special case of the LQGPC controller design. The important advantage of using the LQGPC framework for designing predictive, e.g. GPS is that LQGPC enables...
Secondary Coordinated Control of Islanded Microgrids Based on Consensus Algorithms
DEFF Research Database (Denmark)
Wu, Dan; Dragicevic, Tomislav; Vasquez, Juan Carlos
2014-01-01
systems. Nevertheless, the conventional decentralized secondary control, although does not need to be implemented in a microgrid central controller (MGCC), it has the limitation that all decentralized controllers must be mutually synchronized. In a clear cut contrast, the proposed secondary control......This paper proposes a decentralized secondary control for islanded microgrids based on consensus algorithms. In a microgrid, the secondary control is implemented in order to eliminate the frequency changes caused by the primary control when coordinating renewable energy sources and energy storage...... requires only a more simplified communication protocol and a sparse communication network. Moreover, the proposed approach based on dynamic consensus algorithms is able to achieve the coordinated secondary performance even when all units are initially out-of-synchronism. The control algorithm implemented...
Researching on YH100 Numerical Control Servo Press Hydraulic Control System and Control Algorithm
Directory of Open Access Journals (Sweden)
Kai LI
2014-09-01
Full Text Available In order to study the numerical control (NC servo press hydraulic control system and its control algorithm. The numerical control servo press performance and control principle of hydraulic control system are analyzed. According to the flow equation of the hydraulic control valve, hydraulic cylinder flow continuity equation and the force balance equation of the hydraulic cylinder with load press, the mathematical model of hydraulic control system is established. And the servo press hydraulic system transfer function is deduced. Introducing the suitable immune particle swarm control algorithm for servo press hydraulic system, and the control system block diagram is established. Immune algorithm is used to optimize new control parameters of the system and adopt the new optimization results to optimize the system simulation. The simulation result shows that the hydraulic system’s transition time controlled by the immune particle swarm algorithm is shorter than traditional ones, and the control performance is obviously improved. Finally it can be concluded that immune particle swarm PID control have these characteristics such as quickness, stability and accuracy. Applying this principle into application, the obtained YH100 numerical control servo press hydraulic control system meets the requirement.
Basic Research on Adaptive Model Algorithmic Control
1985-12-01
Control Conference. Richalet, J., A. Rault, J.L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial...pp.977-982. Richalet, J., A. Rault, J. L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial processes
Robust reactor power control system design by genetic algorithm
Energy Technology Data Exchange (ETDEWEB)
Lee, Yoon Joon; Cho, Kyung Ho; Kim, Sin [Cheju National University, Cheju (Korea, Republic of)
1997-12-31
The H{sub {infinity}} robust controller for the reactor power control system is designed by use of the mixed weight sensitivity. The system is configured into the typical two-port model with which the weight functions are augmented. Since the solution depends on the weighting functions and the problem is of nonconvex, the genetic algorithm is used to determine the weighting functions. The cost function applied in the genetic algorithm permits the direct control of the power tracking performances. In addition, the actual operating constraints such as rod velocity and acceleration can be treated as design parameters. Compared with the conventional approach, the controller designed by the genetic algorithm results in the better performances with the realistic constraints. Also, it is found that the genetic algorithm could be used as an effective tool in the robust design. 4 refs., 6 figs. (Author)
Robust reactor power control system design by genetic algorithm
Energy Technology Data Exchange (ETDEWEB)
Lee, Yoon Joon; Cho, Kyung Ho; Kim, Sin [Cheju National University, Cheju (Korea, Republic of)
1998-12-31
The H{sub {infinity}} robust controller for the reactor power control system is designed by use of the mixed weight sensitivity. The system is configured into the typical two-port model with which the weight functions are augmented. Since the solution depends on the weighting functions and the problem is of nonconvex, the genetic algorithm is used to determine the weighting functions. The cost function applied in the genetic algorithm permits the direct control of the power tracking performances. In addition, the actual operating constraints such as rod velocity and acceleration can be treated as design parameters. Compared with the conventional approach, the controller designed by the genetic algorithm results in the better performances with the realistic constraints. Also, it is found that the genetic algorithm could be used as an effective tool in the robust design. 4 refs., 6 figs. (Author)
Randomized algorithms in automatic control and data mining
Granichin, Oleg; Toledano-Kitai, Dvora
2015-01-01
In the fields of data mining and control, the huge amount of unstructured data and the presence of uncertainty in system descriptions have always been critical issues. The book Randomized Algorithms in Automatic Control and Data Mining introduces the readers to the fundamentals of randomized algorithm applications in data mining (especially clustering) and in automatic control synthesis. The methods proposed in this book guarantee that the computational complexity of classical algorithms and the conservativeness of standard robust control techniques will be reduced. It is shown that when a problem requires "brute force" in selecting among options, algorithms based on random selection of alternatives offer good results with certain probability for a restricted time and significantly reduce the volume of operations.
Fuzzy power control algorithm for a pressurized water reactor
International Nuclear Information System (INIS)
Hah, Y.J.; Lee, B.W.
1994-01-01
A fuzzy power control algorithm is presented for automatic reactor power control in a pressurized water reactor (PWR). Automatic power shape control is complicated by the use of control rods with a conventional proportional-integral-differential controller because it is highly coupled with reactivity compensation. Thus, manual shape controls are usually employed even for the limited capability needed for load-following operations including frequency control. In an attempt to achieve automatic power shape control without any design modifications to the core, a fuzzy power control algorithm is proposed. For the fuzzy control, the rule base is formulated based on a multiple-input multiple-output system. The minimum operation rule and the center of area method are implemented for the development of the fuzzy algorithm. The fuzzy power control algorithm has been applied to Yonggwang Nuclear Unit 3. The simulation results show that the fuzzy control can be adapted as a practical control strategy for automatic reactor power control of PWRs during the load-following operations
B ampersand W PWR advanced control system algorithm development
International Nuclear Information System (INIS)
Winks, R.W.; Wilson, T.L.; Amick, M.
1992-01-01
This paper discusses algorithm development of an Advanced Control System for the B ampersand W Pressurized Water Reactor (PWR) nuclear power plant. The paper summarizes the history of the project, describes the operation of the algorithm, and presents transient results from a simulation of the plant and control system. The history discusses the steps in the development process and the roles played by the utility owners, B ampersand W Nuclear Service Company (BWNS), Oak Ridge National Laboratory (ORNL), and the Foxboro Company. The algorithm description is a brief overview of the features of the control system. The transient results show that operation of the algorithm in a normal power maneuvering mode and in a moderately large upset following a feedwater pump trip
Visual Perception Based Rate Control Algorithm for HEVC
Feng, Zeqi; Liu, PengYu; Jia, Kebin
2018-01-01
For HEVC, rate control is an indispensably important video coding technology to alleviate the contradiction between video quality and the limited encoding resources during video communication. However, the rate control benchmark algorithm of HEVC ignores subjective visual perception. For key focus regions, bit allocation of LCU is not ideal and subjective quality is unsatisfied. In this paper, a visual perception based rate control algorithm for HEVC is proposed. First bit allocation weight of LCU level is optimized based on the visual perception of luminance and motion to ameliorate video subjective quality. Then λ and QP are adjusted in combination with the bit allocation weight to improve rate distortion performance. Experimental results show that the proposed algorithm reduces average 0.5% BD-BR and maximum 1.09% BD-BR at no cost in bitrate accuracy compared with HEVC (HM15.0). The proposed algorithm devotes to improving video subjective quality under various video applications.
Reactor controller design using genetic algorithms with simulated annealing
International Nuclear Information System (INIS)
Erkan, K.; Buetuen, E.
2000-01-01
This chapter presents a digital control system for ITU TRIGA Mark-II reactor using genetic algorithms with simulated annealing. The basic principles of genetic algorithms for problem solving are inspired by the mechanism of natural selection. Natural selection is a biological process in which stronger individuals are likely to be winners in a competing environment. Genetic algorithms use a direct analogy of natural evolution. Genetic algorithms are global search techniques for optimisation but they are poor at hill-climbing. Simulated annealing has the ability of probabilistic hill-climbing. Thus, the two techniques are combined here to get a fine-tuned algorithm that yields a faster convergence and a more accurate search by introducing a new mutation operator like simulated annealing or an adaptive cooling schedule. In control system design, there are currently no systematic approaches to choose the controller parameters to obtain the desired performance. The controller parameters are usually determined by test and error with simulation and experimental analysis. Genetic algorithm is used automatically and efficiently searching for a set of controller parameters for better performance. (orig.)
Impulse position control algorithms for nonlinear systems
Energy Technology Data Exchange (ETDEWEB)
Sesekin, A. N., E-mail: sesekin@list.ru [Ural Federal University, 19 S. Mira, Ekaterinburg, 620002 (Russian Federation); Institute of Mathematics and Mechanics, Ural Division of Russian Academy of Sciences, 16 S. Kovalevskaya, Ekaterinburg, 620990 (Russian Federation); Nepp, A. N., E-mail: anepp@urfu.ru [Ural Federal University, 19 S. Mira, Ekaterinburg, 620002 (Russian Federation)
2015-11-30
The article is devoted to the formalization and description of impulse-sliding regime in nonlinear dynamical systems that arise in the application of impulse position controls of a special kind. The concept of trajectory impulse-sliding regime formalized as some limiting network element Euler polygons generated by a discrete approximation of the impulse position control This paper differs from the previously published papers in that it uses a definition of solutions of systems with impulse controls, it based on the closure of the set of smooth solutions in the space of functions of bounded variation. The need for the study of such regimes is the fact that they often arise when parry disturbances acting on technical or economic control system.
Impulse position control algorithms for nonlinear systems
Sesekin, A. N.; Nepp, A. N.
2015-11-01
The article is devoted to the formalization and description of impulse-sliding regime in nonlinear dynamical systems that arise in the application of impulse position controls of a special kind. The concept of trajectory impulse-sliding regime formalized as some limiting network element Euler polygons generated by a discrete approximation of the impulse position control This paper differs from the previously published papers in that it uses a definition of solutions of systems with impulse controls, it based on the closure of the set of smooth solutions in the space of functions of bounded variation. The need for the study of such regimes is the fact that they often arise when parry disturbances acting on technical or economic control system.
Auctions for Congestion Management in Distribution Grids
Philipsen, R.M.; de Weerdt, M.M.; de Vries, L.J.
2016-01-01
Large controllable loads, such as electric vehicles, are increasingly penetrating electricity distribution feeders. To avoid local congestion, their consumption behaviour must be steered, for which a real-time price propagated down from the transmission system does not suffice, as it does not
Immune algorithm based active PID control for structure systems
International Nuclear Information System (INIS)
Lee, Young Jin; Cho, Hyun Cheol; Lee, Kwon Soon
2006-01-01
An immune algorithm is a kind of evolutional computation strategies, which is developed in the basis of a real immune mechanism in the human body. Recently, scientific or engineering applications using this scheme are remarkably increased due to its significant ability in terms of adaptation and robustness for external disturbances. Particularly, this algorithm is efficient to search optimal parameters against complicated dynamic systems with uncertainty and perturbation. In this paper, we investigate an immune algorithm embedded Proportional Integral Derivate (called I P ID) control, in which an optimal parameter vector of the controller is determined offline by using a cell-mediated immune response of the immunized mechanism. For evaluation, we apply the proposed control to mitigation of vibrations for nonlinear structural systems, cased by external environment load such as winds and earthquakes. Comparing to traditional controls under same simulation scenarios, we demonstrate the innovation control is superior especially in robustness aspect
Urhahne, Joseph
2016-01-01
The role of the driver is changing now that vehicles with driving automation technologies appear on the road. It evolves from being an active controller of the vehicle to being a supervisor of the automated ride. The driver has to collaborate with the driving automation and remains responsible for
Searching for the majority: algorithms of voluntary control.
Directory of Open Access Journals (Sweden)
Jin Fan
Full Text Available Voluntary control of information processing is crucial to allocate resources and prioritize the processes that are most important under a given situation; the algorithms underlying such control, however, are often not clear. We investigated possible algorithms of control for the performance of the majority function, in which participants searched for and identified one of two alternative categories (left or right pointing arrows as composing the majority in each stimulus set. We manipulated the amount (set size of 1, 3, and 5 and content (ratio of left and right pointing arrows within a set of the inputs to test competing hypotheses regarding mental operations for information processing. Using a novel measure based on computational load, we found that reaction time was best predicted by a grouping search algorithm as compared to alternative algorithms (i.e., exhaustive or self-terminating search. The grouping search algorithm involves sampling and resampling of the inputs before a decision is reached. These findings highlight the importance of investigating the implications of voluntary control via algorithms of mental operations.
Efficient evolutionary algorithms for optimal control
López Cruz, I.L.
2002-01-01
If optimal control problems are solved by means of gradient based local search methods, convergence to local solutions is likely. Recently, there has been an increasing interest in the use
Congestion management in Alberta
International Nuclear Information System (INIS)
Way, R.
2002-01-01
The challenges facing Alberta regarding electricity market design and congestion management were described. The electricity market in the province consists of a central power pool, an open access transmission network, and a single pool price, unlike many other jurisdictions in North America which have adopted a location margin price (LMP) design with significant price differences between various locations within the power network. Alberta's transmission network is regulated and provides carrier functions. Power moves freely throughout Alberta's power pool network with no congestion, therefore the common pool price signals market participants throughout the entire network with no segregation into zones. Alberta is currently at a cross road in choosing between a single pool price model or a nodal price model. In the first instance, the province would have to strengthen the transmission network to maintain the market at a reasonable size. The alternative would permit Alberta to use market-based techniques to deal with the evolution of many smaller markets in the province, but these would be very small by North American standards and their ability to compete would be questionable
Computationally efficient model predictive control algorithms a neural network approach
Ławryńczuk, Maciej
2014-01-01
This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: · A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. · Implementation details of the MPC algorithms for feedforward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. · The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). · The MPC algorithms with neural approximation with no on-line linearization. · The MPC algorithms with guaranteed stability and robustness. · Cooperation between the MPC algorithms and set-point optimization. Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require d...
CSIR Research Space (South Africa)
Mkuzangwe, NNP
2015-08-01
Full Text Available This work implements two anomaly detection algorithms for detecting Transmission Control Protocol Synchronized (TCP SYN) flooding attack. The two algorithms are an adaptive threshold algorithm and a cumulative sum (CUSUM) based algorithm...
Slot allocation on congested motorways : An alternative to congestion pricing
Koolstra, K.
1999-01-01
With respect to the prevailing congestion problems in the more urbanised regions of the European Union, transportation planners and policymakers are facing a dilemma. Supply-side measures, i.e. increasing the capacities, might shorten the congestion duration, especially if bottlenecks can be
Tuning of active vibration controllers for ACTEX by genetic algorithm
Kwak, Moon K.; Denoyer, Keith K.
1999-06-01
This paper is concerned with the optimal tuning of digitally programmable analog controllers on the ACTEX-1 smart structures flight experiment. The programmable controllers for each channel include a third order Strain Rate Feedback (SRF) controller, a fifth order SRF controller, a second order Positive Position Feedback (PPF) controller, and a fourth order PPF controller. Optimal manual tuning of several control parameters can be a difficult task even though the closed-loop control characteristics of each controller are well known. Hence, the automatic tuning of individual control parameters using Genetic Algorithms is proposed in this paper. The optimal control parameters of each control law are obtained by imposing a constraint on the closed-loop frequency response functions using the ACTEX mathematical model. The tuned control parameters are then uploaded to the ACTEX electronic control electronics and experiments on the active vibration control are carried out in space. The experimental results on ACTEX will be presented.
Towards Automatic Controller Design using Multi-Objective Evolutionary Algorithms
DEFF Research Database (Denmark)
Pedersen, Gerulf
of evolutionary computation, a choice was made to use multi-objective algorithms for the purpose of aiding in automatic controller design. More specifically, the choice was made to use the Non-dominated Sorting Genetic Algorithm II (NSGAII), which is one of the most potent algorithms currently in use...... for automatic controller design. However, because the field of evolutionary computation is relatively unknown in the field of control engineering, this thesis also includes a comprehensive introduction to the basic field of evolutionary computation as well as a description of how the field has previously been......In order to design the controllers of tomorrow, a need has risen for tools that can aid in the design of these. A desire to use evolutionary computation as a tool to achieve that goal is what gave inspiration for the work contained in this thesis. After having studied the foundations...
Energy Technology Data Exchange (ETDEWEB)
Aziz, H. M. Abdul [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wang, Hong [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Young, Stan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sperling, Joshua [National Renewable Energy Lab. (NREL), Golden, CO (United States); Beck, John [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2017-06-01
Documenting existing state of practice is an initial step in developing future control infrastructure to be co-deployed for heterogeneous mix of connected and automated vehicles with human drivers while leveraging benefits to safety, congestion, and energy. With advances in information technology and extensive deployment of connected and automated vehicle technology anticipated over the coming decades, cities globally are making efforts to plan and prepare for these transitions. CAVs not only offer opportunities to improve transportation systems through enhanced safety and efficient operations of vehicles. There are also significant needs in terms of exploring how best to leverage vehicle-to-vehicle (V2V) technology, vehicle-to-infrastructure (V2I) technology and vehicle-to-everything (V2X) technology. Both Connected Vehicle (CV) and Connected and Automated Vehicle (CAV) paradigms feature bi-directional connectivity and share similar applications in terms of signal control algorithm and infrastructure implementation. The discussion in our synthesis study assumes the CAV/CV context where connectivity exists with or without automated vehicles. Our synthesis study explores the current state of signal control algorithms and infrastructure, reports the completed and newly proposed CV/CAV deployment studies regarding signal control schemes, reviews the deployment costs for CAV/AV signal infrastructure, and concludes with a discussion on the opportunities such as detector free signal control schemes and dynamic performance management for intersections, and challenges such as dependency on market adaptation and the need to build a fault-tolerant signal system deployment in a CAV/CV environment. The study will serve as an initial critical assessment of existing signal control infrastructure (devices, control instruments, and firmware) and control schemes (actuated, adaptive, and coordinated-green wave). Also, the report will help to identify the future needs for the signal
Indian Academy of Sciences (India)
polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.
Stall Recovery Guidance Algorithms Based on Constrained Control Approaches
Stepanyan, Vahram; Krishnakumar, Kalmanje; Kaneshige, John; Acosta, Diana
2016-01-01
Aircraft loss-of-control, in particular approach to stall or fully developed stall, is a major factor contributing to aircraft safety risks, which emphasizes the need to develop algorithms that are capable of assisting the pilots to identify the problem and providing guidance to recover the aircraft. In this paper we present several stall recovery guidance algorithms, which are implemented in the background without interfering with flight control system and altering the pilot's actions. They are using input and state constrained control methods to generate guidance signals, which are provided to the pilot in the form of visual cues. It is the pilot's decision to follow these signals. The algorithms are validated in the pilot-in-the loop medium fidelity simulation experiment.
A Traffic Prediction Algorithm for Street Lighting Control Efficiency
Directory of Open Access Journals (Sweden)
POPA Valentin
2013-01-01
Full Text Available This paper presents the development of a traffic prediction algorithm that can be integrated in a street lighting monitoring and control system. The prediction algorithm must enable the reduction of energy costs and improve energy efficiency by decreasing the light intensity depending on the traffic level. The algorithm analyses and processes the information received at the command center based on the traffic level at different moments. The data is collected by means of the Doppler vehicle detection sensors integrated within the system. Thus, two methods are used for the implementation of the algorithm: a neural network and a k-NN (k-Nearest Neighbor prediction algorithm. For 500 training cycles, the mean square error of the neural network is 9.766 and for 500.000 training cycles the error amounts to 0.877. In case of the k-NN algorithm the error increases from 8.24 for k=5 to 12.27 for a number of 50 neighbors. In terms of a root means square error parameter, the use of a neural network ensures the highest performance level and can be integrated in a street lighting control system.
Algorithms and procedures in the model based control of accelerators
International Nuclear Information System (INIS)
Bozoki, E.
1987-10-01
The overall design of a Model Based Control system was presented. The system consists of PLUG-IN MODULES, governed by a SUPERVISORY PROGRAM and communicating via SHARED DATA FILES. Models can be ladded or replaced without affecting the oveall system. There can be more then one module (algorithm) to perform the same task. The user can choose the most appropriate algorithm or can compare the results using different algorithms. Calculations, algorithms, file read and write, etc. which are used in more than one module, will be in a subroutine library. This feature will simplify the maintenance of the system. A partial list of modules is presented, specifying the task they perform. 19 refs., 1 fig
ROBUST CONTROL ALGORITHM FOR MULTIVARIABLE PLANTS WITH QUANTIZED OUTPUT
Directory of Open Access Journals (Sweden)
A. A. Margun
2017-01-01
Full Text Available The paper deals with robust output control algorithm for multivariable plants under disturbances. A plant is described by the system of linear differential equations with known relative degrees. Plant parameters are unknown but belong to the known closed bounded set. Plant state vector is unmeasured. Plant output is measured only via static quantizer. Control system algorithm is based on the high gain feedback method. Developed controller provides exponential convergence of tracking error to the bounded area. The area bounds depend on quantizer parameters and the value of external disturbances. Experimental approbation of the proposed control algorithm is performed with the use of Twin Rotor MIMO System laboratory bench. This bench is a helicopter like model with two degrees of freedom (pitch and yaw. DC motors are used as actuators. The output signals are measured via optical encoders. Mathematical model of laboratory bench is obtained. Proposed algorithm was compared with proportional - integral – differential controller in conditions of output quantization. Obtained results have confirmed the efficiency of proposed controller.
On flexible CAD of adaptive control and identification algorithms
DEFF Research Database (Denmark)
Christensen, Anders; Ravn, Ole
1988-01-01
a total redesign of the system within each sample. The necessary design parameters are evaluated and a decision vector is defined, from which the identification algorithm can be generated by the program. Using the decision vector, a decision-node tree structure is built up, where the nodes define......SLLAB is a MATLAB-family software package for solving control and identification problems. This paper concerns the planning of a general-purpose subroutine structure for solving identification and adaptive control problems. A general-purpose identification algorithm is suggested, which allows...
Position Control of Switched Reluctance Motor Using Super Twisting Algorithm
Directory of Open Access Journals (Sweden)
Muhammad Rafiq Mufti
2016-01-01
Full Text Available The inherent problem of chattering in traditional sliding mode control is harmful for practical application of control system. This paper pays a considerable attention to a chattering-free control method, that is, higher-order sliding mode (super twisting algorithm. The design of a position controller for switched reluctance motor is presented and its stability is assured using Lyapunov stability theorem. In order to highlight the advantages of higher-order sliding mode controller (HOSMC, a classical first-order sliding mode controller (FOSMC is also applied to the same system and compared. The simulation results reflect the effectiveness of the proposed technique.
Review of control algorithms for offshore wind turbines
Energy Technology Data Exchange (ETDEWEB)
Spruce, C.J.; Markou, H.; Leithead, W.E.; Dominguez Ruiz, S.
2005-07-01
Innovative turbine control strategies could allow the improvements to cost and performance considered essential to reduce the cost of energy from offshore wind farms around the UK. This project reviewed and investigated the possibility for further development of a power control algorithm originally developed by NEG Micon Rotors Ltd for use with offshore wind turbines in the hope that more advanced algorithms would reduce the loads on, and hence the costs of, components such as the foundation/support structure, tower, blades and bedplate. Three models (simulation model, linearisation of the simulation model and control model) were produced in order to conduct the review. Application of these models produced the conclusion that the size of the latest generation of offshore wind turbines has now reached a level where performance is starting to be constrained by fundamental factors in the dynamics caused by the machine's physical size. It was also concluded that an ideal control strategy could achieve potential cost savings for the tower and support structure of 5-10% of the total cost of the turbine plus support structure. Further work to develop controllers to reduce loads in the tower and support structure is urged. The report considers non-linear simulation, the linear model, the control model, general operation of the controller, the drive train damping filter, torque control, pitch control and advanced algorithms, and makes detailed recommendations for future work.
Review of control algorithms for offshore wind turbines
Energy Technology Data Exchange (ETDEWEB)
Spruce, C J; Markou, H; Leithead, W E; Dominguez Ruiz, S
2005-07-01
Innovative turbine control strategies could allow the improvements to cost and performance considered essential to reduce the cost of energy from offshore wind farms around the UK. This project reviewed and investigated the possibility for further development of a power control algorithm originally developed by NEG Micon Rotors Ltd for use with offshore wind turbines in the hope that more advanced algorithms would reduce the loads on, and hence the costs of, components such as the foundation/support structure, tower, blades and bedplate. Three models (simulation model, linearisation of the simulation model and control model) were produced in order to conduct the review. Application of these models produced the conclusion that the size of the latest generation of offshore wind turbines has now reached a level where performance is starting to be constrained by fundamental factors in the dynamics caused by the machine's physical size. It was also concluded that an ideal control strategy could achieve potential cost savings for the tower and support structure of 5-10% of the total cost of the turbine plus support structure. Further work to develop controllers to reduce loads in the tower and support structure is urged. The report considers non-linear simulation, the linear model, the control model, general operation of the controller, the drive train damping filter, torque control, pitch control and advanced algorithms, and makes detailed recommendations for future work.
de Milliano, Paul A. R.; de Groot, Andre C.; Tijssen, Jan G. P.; van Eck-Smit, Berthe L. F.; van Zwieten, Pieter A.; Lie, Kong I.
2002-01-01
BACKGROUND: We sought to investigate whether beta-blockers exert a presynaptic effect in the myocardium as measured by 123I-metaiodobenzylguanidine. METHODS: The study comprised 59 patients with congestive heart failure, New York Heart Association class II or III, and left ventricular ejection
Congestion Management Strategies of Real-Time Market
DEFF Research Database (Denmark)
Wang, Qi; Zhang, Chunyu; Ding, Yi
2014-01-01
The high penetration of distributed energy resources (DERs) will significantly challenge the power system operation and control due to their stochastic, intermittent, and fluctuation characteristics. This enhances the difficulty of congestion management of power systems in cross-border electricity...... are introduced with the congestion constraints complied. Pre-Contingency strategy is proposed as the advance preparation for the future congestion, and In-Day re-dispatch is used for regulation. Accordingly, the requirements on facilities considering telemetry and remote control in a fast manner are discussed...
Configuration-defined control algorithms with the ASDEX Upgrade DCS
Energy Technology Data Exchange (ETDEWEB)
Treutterer, Wolfgang, E-mail: Wolfgang.Treutterer@ipp.mpg.de [Max-Planck-Institut für Plasmaphysik, Boltzmannstr. 2, 85748 Garching (Germany); Cole, Richard [Unlimited Computer Systems, Seeshaupter Str. 15, 82393 Iffeldorf Germany (Germany); Gräter, Alexander [Max-Planck-Institut für Plasmaphysik, Boltzmannstr. 2, 85748 Garching (Germany); Lüddecke, Klaus [Unlimited Computer Systems, Seeshaupter Str. 15, 82393 Iffeldorf Germany (Germany); Neu, Gregor; Rapson, Christopher; Raupp, Gerhard; Zehetbauer, Thomas [Max-Planck-Institut für Plasmaphysik, Boltzmannstr. 2, 85748 Garching (Germany)
2016-11-15
Highlights: • Control algorithm built from combination of pre-fabricated standard function blocks. • Seamless integration in multi-threaded computation context. • Block composition defined by configuration data, only. - Abstract: The ASDEX Upgrade Discharge Control System (DCS) is a distributed real-time control system executing complex control and monitoring tasks. Up to now, DCS control algorithms have been implemented by coding dedicated application processes with the C++ programming language. Algorithm changes required code modification, compilation and commissioning which only experienced programmers could perform. This was a significant constraint of flexibility for both control system operation and design. The new approach extends DCS with the capability of configuration-defined control algorithms. These are composed of chains of small, configurable standard function blocks providing general purpose functions like algebraic operations, filters, feedback controllers, output limiters and decision logic. In a later phase a graphical editor could help to compose and modify such configuration in a Simulink-like fashion. Building algorithms from standard functions can result in a high number of elements. In order to achieve a similar performance as with C++ coding, it is essential to avoid administrative bottlenecks by design. As a consequence, DCS executes a function block chain in the context of a single real-time thread of an application process. No concurrency issues as in a multi-threaded context need to be considered resulting in strongly simplified signal handling and zero performance overhead for inter-block communication. Instead of signal-driven synchronization, a block scheduler derives the execution sequence automatically from the block dependencies as defined in the configuration. All blocks and connecting signals are instantiated dynamically, based on definitions in a configuration file. Algorithms thus are not defined in the code but only in
Application of genetic algorithms to tuning fuzzy control systems
Espy, Todd; Vombrack, Endre; Aldridge, Jack
1993-01-01
Real number genetic algorithms (GA) were applied for tuning fuzzy membership functions of three controller applications. The first application is our 'Fuzzy Pong' demonstration, a controller that controls a very responsive system. The performance of the automatically tuned membership functions exceeded that of manually tuned membership functions both when the algorithm started with randomly generated functions and with the best manually-tuned functions. The second GA tunes input membership functions to achieve a specified control surface. The third application is a practical one, a motor controller for a printed circuit manufacturing system. The GA alters the positions and overlaps of the membership functions to accomplish the tuning. The applications, the real number GA approach, the fitness function and population parameters, and the performance improvements achieved are discussed. Directions for further research in tuning input and output membership functions and in tuning fuzzy rules are described.
Fuzzy model predictive control algorithm applied in nuclear power plant
International Nuclear Information System (INIS)
Zuheir, Ahmad
2006-01-01
The aim of this paper is to design a predictive controller based on a fuzzy model. The Takagi-Sugeno fuzzy model with an Adaptive B-splines neuro-fuzzy implementation is used and incorporated as a predictor in a predictive controller. An optimization approach with a simplified gradient technique is used to calculate predictions of the future control actions. In this approach, adaptation of the fuzzy model using dynamic process information is carried out to build the predictive controller. The easy description of the fuzzy model and the easy computation of the gradient sector during the optimization procedure are the main advantages of the computation algorithm. The algorithm is applied to the control of a U-tube steam generation unit (UTSG) used for electricity generation. (author)
Implantation of algorithms of diffuse control in DSPS
International Nuclear Information System (INIS)
Perez C, B.
2003-01-01
In this thesis work there are presented: a) The characteristics and main components used in an electronic system based on a Dsp guided to control applications of processes, b) The description of an algorithm of diffuse control whose objective is the regulation of neutron power in a model of the punctual kinetics of a nuclear research reactor type TRIGA, and c) The installation in language assembler and execution in real time of the control algorithm in the system based on a Dsp. With regard to the installation and execution of the algorithm, the reaches of the project have been delimited to the following: a) Readiness of the entrance values to the controller in specific registrations of the system Dsp, b) Conversion of the entrances to the numerical formats with those that one obtains the best acting in the control algorithm, c) Execution of the algorithm until the obtaining of the value of the controller's exit, and d) Placement of the result in specific registrations of the Dsp for their later reading for an external parallel interface. It is necessary to mention that the simulation of the punctual kinetics of a reactor type TRIGA in the Pc and its integration with the control system based on the one Dsp is had contemplated as continuation of this work and that one of those will constitute main activities in my project of master thesis. A brief description of the topics presented in this thesis is given next. In the chapter one it is presented a general description of the diffuse logic and some of their applications in the industry. The main characteristics of a Dsp are also presented that they make it different from a micro controller or a microprocessor of general purpose. In the chapter 2 details of the internal architecture of the Dsp TMS320CS0 of Texas Instruments that are not explained with detail in the manual of user of the same one. This chapter has as objective to understand the internal hardware of the Dsp that is used for to carry out the program in
Application of epidemic algorithms for smart grids control
International Nuclear Information System (INIS)
Krkoleva, Aleksandra
2012-01-01
Smart Grids are a new concept for electricity networks development, aiming to provide economically efficient and sustainable power system by integrating effectively the actions and needs of the network users. The thesis addresses the Smart Grids concept, with emphasis on the control strategies developed on the basis of epidemic algorithms, more specifically, gossip algorithms. The thesis is developed around three Smart grid aspects: the changed role of consumers in terms of taking part in providing services within Smart Grids; the possibilities to implement decentralized control strategies based on distributed algorithms; and information exchange and benefits emerging from implementation of information and communication technologies. More specifically, the thesis presents a novel approach for providing ancillary services by implementing gossip algorithms. In a decentralized manner, by exchange of information between the consumers and by making decisions on local level, based on the received information and local parameters, the group achieves its global objective, i. e. providing ancillary services. The thesis presents an overview of the Smart Grids control strategies with emphasises on new strategies developed for the most promising Smart Grids concepts, as Micro grids and Virtual power plants. The thesis also presents the characteristics of epidemic algorithms and possibilities for their implementation in Smart Grids. Based on the research on epidemic algorithms, two applications have been developed. These applications are the main outcome of the research. The first application enables consumers, represented by their commercial aggregators, to participate in load reduction and consequently, to participate in balancing market or reduce the balancing costs of the group. In this context, the gossip algorithms are used for aggregator's message dissemination for load reduction and households and small commercial and industrial consumers to participate in maintaining
control of a dc motor using fuzzy logic control algorithm
African Journals Online (AJOL)
user
controller in the control performance of an industrial type DC motor using MATLAB. The fuzzy logic .... controlled separately excited permanent magnet DC motor (PMDC). ... When the field current is constant, the flux induced by the field ...
International Nuclear Information System (INIS)
Dong Yun Kim; Poong Hyun Seong; .
1997-01-01
In this research, we propose a fuzzy gain scheduler (FGS) with an intelligent learning algorithm for a reactor control. In the proposed algorithm, the gradient descent method is used in order to generate the rule bases of a fuzzy algorithm by learning. These rule bases are obtained by minimizing an objective function, which is called a performance cost function. The objective of the FGS with an intelligent learning algorithm is to generate gains, which minimize the error of system. The proposed algorithm can reduce the time and effort required for obtaining the fuzzy rules through the intelligent learning function. It is applied to reactor control of nuclear power plant (NPP), and the results are compared with those of a conventional PI controller with fixed gains. As a result, it is shown that the proposed algorithm is superior to the conventional PI controller. (author)
System control fuzzy neural sewage pumping stations using genetic algorithms
Directory of Open Access Journals (Sweden)
Владлен Николаевич Кузнецов
2015-06-01
Full Text Available It is considered the system of management of sewage pumping station with regulators based on a neuron network with fuzzy logic. Linguistic rules for the controller based on fuzzy logic, maintaining the level of effluent in the receiving tank within the prescribed limits are developed. The use of genetic algorithms for neuron network training is shown.
Design of PID Controller Simulator based on Genetic Algorithm
Directory of Open Access Journals (Sweden)
Fahri VATANSEVER
2013-08-01
Full Text Available PID (Proportional Integral and Derivative controllers take an important place in the field of system controlling. Various methods such as Ziegler-Nichols, Cohen-Coon, Chien Hrones Reswick (CHR and Wang-Juang-Chan are available for the design of such controllers benefiting from the system time and frequency domain data. These controllers are in compliance with system properties under certain criteria suitable to the system. Genetic algorithms have become widely used in control system applications in parallel to the advances in the field of computer and artificial intelligence. In this study, PID controller designs have been carried out by means of classical methods and genetic algorithms and comparative results have been analyzed. For this purpose, a graphical user interface program which can be used for educational purpose has been developed. For the definite (entered transfer functions, the suitable P, PI and PID controller coefficients have calculated by both classical methods and genetic algorithms and many parameters and responses of the systems have been compared and presented numerically and graphically
Control of the lighting system using a genetic algorithm
Directory of Open Access Journals (Sweden)
Čongradac Velimir D.
2012-01-01
Full Text Available The manufacturing, distribution and use of electricity are of fundamental importance for the social life and they have the biggest influence on the environment associated with any human activity. The energy needed for building lighting makes up 20-40% of the total consumption. This paper displays the development of the mathematical model and genetic algorithm for the control of dimmable lighting on problems of regulating the level of internal lighting and increase of energetic efficiency using daylight. A series of experiments using the optimization algorithm on the realized model confirmed very high savings in electricity consumption.
Automatic brightness control algorithms and their effect on fluoroscopic imaging
International Nuclear Information System (INIS)
Quinn, P.W.; Gagne, R.M.
1989-01-01
This paper reports a computer model used to investigate the effect on dose and image quality of three automatic brightness control (ABC) algorithms used in the imaging of barium during general-purpose fluoroscopy. A model incorporating all aspects of image formation - i.e., x- ray production, phantom attenuation, and energy absorption in the CSI phosphor - was driven according to each ABC algorithm as a function of patient thickness. The energy absorbed in the phosphor was kept constant, while the changes in exposure, integral dose, organ dose, and contrast were monitored
International Nuclear Information System (INIS)
Park, Gee Yong; Seong, Poong Hyun
1994-01-01
In order to reduce the load of tuning works by trial-and-error for obtaining the best control performance of conventional fuzzy control algorithm, a fuzzy control algorithm with learning function is investigated in this work. This fuzzy control algorithm can make its rule base and tune the membership functions automatically by use of learning function which needs the data from the control actions of the plant operator or other controllers. Learning process in fuzzy control algorithm is to find the optimal values of parameters, which consist of the membership functions and the rule base, by gradient descent method. Learning speed of gradient descent is significantly improved in this work with the addition of modified momentum. This control algorithm is applied to the steam generator level control by computer simulations. The simulation results confirm the good performance of this control algorithm for level control and show that the fuzzy learning algorithm has the generalization capability for the relation of inputs and outputs and it also has the excellent capability of disturbance rejection
Gao, Juntao; Shen, Yulong; Liu, Jia; Ito, Minoru; Shiratori, Norio
2017-01-01
Adaptive traffic signal control, which adjusts traffic signal timing according to real-time traffic, has been shown to be an effective method to reduce traffic congestion. Available works on adaptive traffic signal control make responsive traffic signal control decisions based on human-crafted features (e.g. vehicle queue length). However, human-crafted features are abstractions of raw traffic data (e.g., position and speed of vehicles), which ignore some useful traffic information and lead t...
Wind turbine pitch control using ICPSO-PID algorithm
DEFF Research Database (Denmark)
Xu, Chang; Tian, Qiangqiang; Shen, Wen Zhong
2013-01-01
For the traditional simplified first-order pitch-control system model, it is difficult to describe a real dynamic characteristic of a variable pitch action system, thus a complete high order mathematical model has to be developed for the pitch control of wind turbine generation (WTG). In the paper...... controller parameters quickly; and the feed-forward controller for wind speed can improve dynamics of a pitch-control system; additionally the power controller can allow a wind turbine to have a constant power output as a wind speed is over the rated one. Compared with a conventional PID, the controller...... with ICPSO-PID algorithm has a smaller overshoot, a shorter tuning time and better robustness. The design method proposed in the paper can be applied in a practical electro-hydraulic pitch control system for WTG....
Robotics, vision and control fundamental algorithms in Matlab
Corke, Peter
2017-01-01
Robotic vision, the combination of robotics and computer vision, involves the application of computer algorithms to data acquired from sensors. The research community has developed a large body of such algorithms but for a newcomer to the field this can be quite daunting. For over 20 years the author has maintained two open-source MATLAB® Toolboxes, one for robotics and one for vision. They provide implementations of many important algorithms and allow users to work with real problems, not just trivial examples. This book makes the fundamental algorithms of robotics, vision and control accessible to all. It weaves together theory, algorithms and examples in a narrative that covers robotics and computer vision separately and together. Using the latest versions of the Toolboxes the author shows how complex problems can be decomposed and solved using just a few simple lines of code. The topics covered are guided by real problems observed by the author over many years as a practitioner of both robotics and compu...
Optimal control of hybrid qubits: Implementing the quantum permutation algorithm
Rivera-Ruiz, C. M.; de Lima, E. F.; Fanchini, F. F.; Lopez-Richard, V.; Castelano, L. K.
2018-03-01
The optimal quantum control theory is employed to determine electric pulses capable of producing quantum gates with a fidelity higher than 0.9997, when noise is not taken into account. Particularly, these quantum gates were chosen to perform the permutation algorithm in hybrid qubits in double quantum dots (DQDs). The permutation algorithm is an oracle based quantum algorithm that solves the problem of the permutation parity faster than a classical algorithm without the necessity of entanglement between particles. The only requirement for achieving the speedup is the use of a one-particle quantum system with at least three levels. The high fidelity found in our results is closely related to the quantum speed limit, which is a measure of how fast a quantum state can be manipulated. Furthermore, we model charge noise by considering an average over the optimal field centered at different values of the reference detuning, which follows a Gaussian distribution. When the Gaussian spread is of the order of 5 μ eV (10% of the correct value), the fidelity is still higher than 0.95. Our scheme also can be used for the practical realization of different quantum algorithms in DQDs.
Quantum control using genetic algorithms in quantum communication: superdense coding
International Nuclear Information System (INIS)
Domínguez-Serna, Francisco; Rojas, Fernando
2015-01-01
We present a physical example model of how Quantum Control with genetic algorithms is applied to implement the quantum superdense code protocol. We studied a model consisting of two quantum dots with an electron with spin, including spin-orbit interaction. The electron and the spin get hybridized with the site acquiring two degrees of freedom, spin and charge. The system has tunneling and site energies as time dependent control parameters that are optimized by means of genetic algorithms to prepare a hybrid Bell-like state used as a transmission channel. This state is transformed to obtain any state of the four Bell basis as required by superdense protocol to transmit two bits of classical information. The control process protocol is equivalent to implement one of the quantum gates in the charge subsystem. Fidelities larger than 99.5% are achieved for the hybrid entangled state preparation and the superdense operations. (paper)
Indian Academy of Sciences (India)
to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...
Congestion Management System Process Report
1996-03-01
In January 1995, the Indianapolis Metropolitan Planning Organization with the help of an interagency Study Review Committee began the process of developing a Congestion Management System (CMS) Plan resulting in this report. This report documents the ...
Integrated control algorithms for plant environment in greenhouse
Zhang, Kanyu; Deng, Lujuan; Gong, Youmin; Wang, Shengxue
2003-09-01
In this paper a survey of plant environment control in artificial greenhouse was put forward for discussing the future development. Firstly, plant environment control started with the closed loop control of air temperature in greenhouse. With the emergence of higher property computer, the adaptive control algorithm and system identification were integrated into the control system. As adaptation control is more depending on observation of variables by sensors and yet many variables are unobservable or difficult to observe, especially for observation of crop growth status, so model-based control algorithm were developed. In order to evade modeling difficulty, one method is predigesting the models and the other method is utilizing fuzzy logic and neural network technology that realize the models by the black box and gray box theory. Studies on control method of plant environment in greenhouse by means of expert system (ES) and artificial intelligence (AI) have been initiated and developed. Nowadays, the research of greenhouse environment control focus on energy saving, optimal economic profit, enviornment protection and continualy develop.
Synthesis of Control Algorithm for a Leaderheaded UAVs Group
Directory of Open Access Journals (Sweden)
I. O. Samodov
2015-01-01
Full Text Available Currently, a defense sphere uses unmanned aerial vehicles (UAVs. UAVs have several advantages over manned aircrafts such as small size, reduced combat losses of personnel, etc. In addition, in threat environment, it is necessary to arrange both bringing together distant from each other UAVs in a group and their undetected in radar fields compact flying in terms of the joint flight security.However, the task to control a UAVs group is much more difficult than to control a single UAV, since it is necessary not only to control the aircraft, but also take into account the relative position of objects in the group.To solve this problem two ways are possible: using a network exchange between members of the group on the "everyone with everyone" principle and organizing the leader-headed flight.The aim of the article is to develop and study a possible option of the UAVs group control with arranging a leader-headed flight to provide the undetected in radar fields compact flying in terms of the joint flight security.The article develops a universal algorithm to control leader-headed group, based on a new modification of the statistical theory of optimal control. It studies effectiveness of the algorithm. While solving this task, a flight of seven UAVs was simulated in the horizontal plane in a rectangular coordinate system. Control time, linear errors of desired alignment of UAV, and control errors with respect to angular coordinates are used as measures of merit.The study results of the algorithm to control a leader-headed group of UAVs confirmed that it is possible to fulfill tasks of flying free-of-collision group of UAVs with essentially reduced computational costs.
The algorithms for control of heating massive material
Directory of Open Access Journals (Sweden)
Karol Kostúr
2008-03-01
Full Text Available In numerous technological processes a change on the output follows change on the input pending specific time. This time is called dead time and if this time is too large, it causes problems in the control. This contribution is aimed at analyzing the algorithms of discreet regulation of the systems with dead time. Verified were classical PID regulator and a regulator using Dead Beat method. The control was also tried with Dead interval method. The regulators were tested by simulation and in the electrical laboratory furnace. The task was to control the temperature inside the material heated by furnace power.
Genetic Algorithm Optimizes Q-LAW Control Parameters
Lee, Seungwon; von Allmen, Paul; Petropoulos, Anastassios; Terrile, Richard
2008-01-01
A document discusses a multi-objective, genetic algorithm designed to optimize Lyapunov feedback control law (Q-law) parameters in order to efficiently find Pareto-optimal solutions for low-thrust trajectories for electronic propulsion systems. These would be propellant-optimal solutions for a given flight time, or flight time optimal solutions for a given propellant requirement. The approximate solutions are used as good initial solutions for high-fidelity optimization tools. When the good initial solutions are used, the high-fidelity optimization tools quickly converge to a locally optimal solution near the initial solution. Q-law control parameters are represented as real-valued genes in the genetic algorithm. The performances of the Q-law control parameters are evaluated in the multi-objective space (flight time vs. propellant mass) and sorted by the non-dominated sorting method that assigns a better fitness value to the solutions that are dominated by a fewer number of other solutions. With the ranking result, the genetic algorithm encourages the solutions with higher fitness values to participate in the reproduction process, improving the solutions in the evolution process. The population of solutions converges to the Pareto front that is permitted within the Q-law control parameter space.
Design and implementation of adaptive inverse control algorithm for a micro-hand control system
Directory of Open Access Journals (Sweden)
Wan-Cheng Wang
2014-01-01
Full Text Available The Letter proposes an online tuned adaptive inverse position control algorithm for a micro-hand. First, the configuration of the micro-hand is discussed. Next, a kinematic analysis of the micro-hand is investigated and then the relationship between the rotor position of micro-permanent magnet synchronous motor and the tip of the micro-finger is derived. After that, an online tuned adaptive inverse control algorithm, which includes an adaptive inverse model and an adaptive inverse control, is designed. The online tuned adaptive inverse control algorithm has better performance than the proportional–integral control algorithm does. In addition, to avoid damaging the object during the grasping process, an online force control algorithm is proposed here as well. An embedded micro-computer, cRIO-9024, is used to realise the whole position control algorithm and the force control algorithm by using software. As a result, the hardware circuit is very simple. Experimental results show that the proposed system can provide fast transient responses, good load disturbance responses, good tracking responses and satisfactory grasping responses.
A Design of a Hybrid Non-Linear Control Algorithm
Directory of Open Access Journals (Sweden)
Farinaz Behrooz
2017-11-01
Full Text Available One of the high energy consuming devices in the buildings is the air-conditioning system. Designing a proper controller to consider the thermal comfort and simultaneously control the energy usage of the device will impact on the system energy efficiency and its performance. The aim of this study was to design a Multiple-Input and Multiple-Output (MIMO, non-linear, and intelligent controller on direct expansion air-conditioning system The control algorithm uses the Fuzzy Cognitive Map method as a main controller and the Generalized Predictive Control method is used for assigning the initial weights of the main controller. The results of the proposed controller shows that the controller was successfully designed and works in set point tracking and under disturbance rejection tests. The obtained results of the Generalized Predictive Control-Fuzzy Cognitive Map controller are compared with the previous MIMO Linear Quadratic Gaussian control design on the same direct expansion air-conditioning system under the same conditions. The comparative results indicate energy savings would be achieved with the proposed controller with long-term usage. Energy efficiency and thermal comfort conditions are achieved by the proposed controller.
Optimum Actuator Selection with a Genetic Algorithm for Aircraft Control
Rogers, James L.
2004-01-01
The placement of actuators on a wing determines the control effectiveness of the airplane. One approach to placement maximizes the moments about the pitch, roll, and yaw axes, while minimizing the coupling. For example, the desired actuators produce a pure roll moment without at the same time causing much pitch or yaw. For a typical wing, there is a large set of candidate locations for placing actuators, resulting in a substantially larger number of combinations to examine in order to find an optimum placement satisfying the mission requirements and mission constraints. A genetic algorithm has been developed for finding the best placement for four actuators to produce an uncoupled pitch moment. The genetic algorithm has been extended to find the minimum number of actuators required to provide uncoupled pitch, roll, and yaw control. A simplified, untapered, unswept wing is the model for each application.
Active control of flexible structures using a fuzzy logic algorithm
Cohen, Kelly; Weller, Tanchum; Ben-Asher, Joseph Z.
2002-08-01
This study deals with the development and application of an active control law for the vibration suppression of beam-like flexible structures experiencing transient disturbances. Collocated pairs of sensors/actuators provide active control of the structure. A design methodology for the closed-loop control algorithm based on fuzzy logic is proposed. First, the behavior of the open-loop system is observed. Then, the number and locations of collocated actuator/sensor pairs are selected. The proposed control law, which is based on the principles of passivity, commands the actuator to emulate the behavior of a dynamic vibration absorber. The absorber is tuned to a targeted frequency, whereas the damping coefficient of the dashpot is varied in a closed loop using a fuzzy logic based algorithm. This approach not only ensures inherent stability associated with passive absorbers, but also circumvents the phenomenon of modal spillover. The developed controller is applied to the AFWAL/FIB 10 bar truss. Simulated results using MATLAB© show that the closed-loop system exhibits fairly quick settling times and desirable performance, as well as robustness characteristics. To demonstrate the robustness of the control system to changes in the temporal dynamics of the flexible structure, the transient response to a considerably perturbed plant is simulated. The modal frequencies of the 10 bar truss were raised as well as lowered substantially, thereby significantly perturbing the natural frequencies of vibration. For these cases, too, the developed control law provides adequate settling times and rates of vibrational energy dissipation.
A neuro-fuzzy controlling algorithm for wind turbine
Energy Technology Data Exchange (ETDEWEB)
Lin, Li [Tampere Univ. of Technology (Finland); Eriksson, J T [Tampere Univ. of Technology (Finland)
1996-12-31
The wind turbine control system is stochastic and nonlinear, offering a demanding field for different control methods. An improved and efficient controller will have great impact on the cost-effectiveness of the technology. In this article, a design method for a self-organizing fuzzy controller is discussed, which combines two popular computational intelligence techniques, neural networks and fuzzy logic. Based on acquisited dynamic parameters of the wind, it can effectively predict wind changes in speed and direction. Maximum power can always be extracted from the kinetic energy of the wind. Based on the stimulating experiments applying nonlinear dynamics to a `Variable Speed Fixed Angle` wind turbine, it is demonstrated that the proposed control model 3rd learning algorithm provide a predictable, stable and accurate performance. The robustness of the controller to system parameter variations and measurement disturbances is also discussed. (author)
A neuro-fuzzy controlling algorithm for wind turbine
Energy Technology Data Exchange (ETDEWEB)
Li Lin [Tampere Univ. of Technology (Finland); Eriksson, J.T. [Tampere Univ. of Technology (Finland)
1995-12-31
The wind turbine control system is stochastic and nonlinear, offering a demanding field for different control methods. An improved and efficient controller will have great impact on the cost-effectiveness of the technology. In this article, a design method for a self-organizing fuzzy controller is discussed, which combines two popular computational intelligence techniques, neural networks and fuzzy logic. Based on acquisited dynamic parameters of the wind, it can effectively predict wind changes in speed and direction. Maximum power can always be extracted from the kinetic energy of the wind. Based on the stimulating experiments applying nonlinear dynamics to a `Variable Speed Fixed Angle` wind turbine, it is demonstrated that the proposed control model 3rd learning algorithm provide a predictable, stable and accurate performance. The robustness of the controller to system parameter variations and measurement disturbances is also discussed. (author)
Auctionable fixed transmission rights for congestion management
Alomoush, Muwaffaq Irsheid
Electric power deregulation has proposed a major change to the regulated utility monopoly. The change manifests the main part of engineers' efforts to reshape three components of today's regulated monopoly: generation, distribution and transmission. In this open access deregulated power market, transmission network plays a major role, and transmission congestion is a major problem that requires further consideration especially when inter-zonal/intra-zonal scheme is implemented. Declaring that engineering studies and experience are the criteria to define zonal boundaries or defining a zone based on the fact that a zone is a densely interconnected area (lake) and paths connecting these densely interconnected areas are inter-zonal lines will render insufficient and fuzzy definitions. Moreover, a congestion problem formulation should take into consideration interactions between intra-zonal and inter-zonal flows and their effects on power systems. In this thesis, we introduce a procedure for minimizing the number of adjustments of preferred schedules to alleviate congestion and apply control schemes to minimize interactions between zones. In addition, we give the zone definition a certain criterion based on the Locational Marginal Price (LMP). This concept will be used to define congestion zonal boundaries and to decide whether any zone should be merged with another zone or split into new zones. The thesis presents a unified scheme that combines zonal and FTR schemes to manage congestion. This combined scheme is utilized with LMPs to define zonal boundaries more appropriately. The presented scheme gains the best features of the FTR scheme, which are providing financial certainty, maximizing the efficient use of the system and making users pay for the actual use of congested paths. LMPs may give an indication of the impact of wheeling transactions, and calculations of and comparisons of LMPs with and without wheeling transactions should be adequate criteria to approve
How Smog Awareness Influences Public Acceptance of Congestion Charge Policies
Lingyi Zhou; Yixin Dai
2017-01-01
Although various studies have investigated public acceptance of congestion charge policies, most of them have focused on behavioral and policy-related factors, and did not consider the moderating influence that individual concern about smog and perceived smog risk may have on public acceptance. This paper takes the congestion charge policy in China, targeted at smog and traffic control, and checks how smog awareness—including smog concerns and perceived smog risks, besides behavioral and poli...
A Feedback Optimal Control Algorithm with Optimal Measurement Time Points
Directory of Open Access Journals (Sweden)
Felix Jost
2017-02-01
Full Text Available Nonlinear model predictive control has been established as a powerful methodology to provide feedback for dynamic processes over the last decades. In practice it is usually combined with parameter and state estimation techniques, which allows to cope with uncertainty on many levels. To reduce the uncertainty it has also been suggested to include optimal experimental design into the sequential process of estimation and control calculation. Most of the focus so far was on dual control approaches, i.e., on using the controls to simultaneously excite the system dynamics (learning as well as minimizing a given objective (performing. We propose a new algorithm, which sequentially solves robust optimal control, optimal experimental design, state and parameter estimation problems. Thus, we decouple the control and the experimental design problems. This has the advantages that we can analyze the impact of measurement timing (sampling independently, and is practically relevant for applications with either an ethical limitation on system excitation (e.g., chemotherapy treatment or the need for fast feedback. The algorithm shows promising results with a 36% reduction of parameter uncertainties for the Lotka-Volterra fishing benchmark example.
A NEW CONGESTION MANAGEMENT MECHANISM FOR NEXT GENERATION ROUTERS
Directory of Open Access Journals (Sweden)
MOHAMMED M. KADHUM
2008-12-01
Full Text Available While computer networks go towards dealing with varied traffic types with different service requirements, there is a necessity for modern network control mechanisms that can control the network traffic to meet the users' service requirements. Optimizing the network utilization by improving the network performance can help to accommodate more users and thus increase operators’ profits. Controlling the congestion at the gateway leads to better performance of the network. Sending congestion signal sooner can be of great benefit to the TCP connection. In this paper, we propose Fast Congestion Notification (FCN mechanism which is a new method for managing the gateway queues and fast sending of congestion signal to the sender. We tested our mechanism on Explicit Congestion Notification (ECN packets which have higher priority; we achieved good results in terms of faster congestion signal propagation and better network utilization. Our analysis and simulations results show that the use of FCN over TCP connections sharing one bottleneck can improve the throughput, having less loss, less delay time, and better network utilization.
Research on Urban Road Congestion Pricing Strategy Considering Carbon Dioxide Emissions
Directory of Open Access Journals (Sweden)
Yitian Wang
2015-08-01
Full Text Available Congestion pricing strategy has been recognized as an effective countermeasure in the practical field of urban traffic congestion mitigation. In this paper, a bi-level programming model considering carbon dioxide emission is proposed to mitigate traffic congestion and reduce carbon dioxide emissions. The objective function of the upper level model is to minimize the sum of travel costs and the carbon dioxide emissions costs. The lower level is a multi-modal transportation network equilibrium model. To solve the model, the method of successive averages (MSA and the shuffled frog leaping algorithm (SFLA are introduced. The proposed method and algorithm are tested through the numerical example. The results show that the proposed congestion pricing strategy can mitigate traffic congestion and reduce carbon emissions effectively.
Research on digital PID control algorithm for HPCT
International Nuclear Information System (INIS)
Zeng Yi; Li Rui; Shen Tianjian; Ke Xinhua
2009-01-01
Digital PID applied in high-precision HPCT (High-precision current transducer) based on Digital Signal Processor (DSP) TMS320F2812 and special D/A converter was researched. By using increment style PID Control algorithm, the stability and precision of high-precision HPCT output voltage is improved. On basis of deeply analysing incremental digital PID, the scheme model of HPCT is proposed, the feasibility simulation using Matlab is given. Practical hardware circuit verified the incremental PID has closed-loop control process in tracking HPCT output voltage. (authors)
Nuclear power control system design using genetic algorithm
International Nuclear Information System (INIS)
Lee, Yoon Joon; Cho, Kyung Ho
1996-01-01
The genetic algorithm(GA) is applied to the design of the nuclear power control system. The reactor control system model is described in the LQR configuration. The LQR system order is increased to make the tracking system. The key parameters of the design are weighting matrices, and these are usually determined through numerous simulations in the conventional design. To determine the more objective and optimal weightings, the improved GA is applied. The results show that the weightings determined by the GA yield the better system responses than those obtained by the conventional design method
A comparison of three self-tuning control algorithms developed for the Bristol-Babcock controller
International Nuclear Information System (INIS)
Tapp, P.A.
1992-04-01
A brief overview of adaptive control methods relating to the design of self-tuning proportional-integral-derivative (PID) controllers is given. The methods discussed include gain scheduling, self-tuning, auto-tuning, and model-reference adaptive control systems. Several process identification and parameter adjustment methods are discussed. Characteristics of the two most common types of self-tuning controllers implemented by industry (i.e., pattern recognition and process identification) are summarized. The substance of the work is a comparison of three self-tuning proportional-plus-integral (STPI) control algorithms developed to work in conjunction with the Bristol-Babcock PID control module. The STPI control algorithms are based on closed-loop cycling theory, pattern recognition theory, and model-based theory. A brief theory of operation of these three STPI control algorithms is given. Details of the process simulations developed to test the STPI algorithms are given, including an integrating process, a first-order system, a second-order system, a system with initial inverse response, and a system with variable time constant and delay. The STPI algorithms' performance with regard to both setpoint changes and load disturbances is evaluated, and their robustness is compared. The dynamic effects of process deadtime and noise are also considered. Finally, the limitations of each of the STPI algorithms is discussed, some conclusions are drawn from the performance comparisons, and a few recommendations are made. 6 refs
Study and Analysis of Congestion Management in Hybrid Electric Market
Directory of Open Access Journals (Sweden)
Moayed Mohseni
2013-01-01
Full Text Available The congestion management system is a systematic approach, collaboratively developed and implemented throughout a metropolitan region that provides for the safe and effective management and operation of new and existing transportation facilities through the use of demand reduction and operational management strategies. In this paper we try to present some points which should be investigated in congestion management problems. We calculate different kinds of congestion problems which may be occurred in our network. Here, the hybrid model is used to solve problems in the electricity market to solve the congestion problem in the network and Benders techniques is used together with an optimal power flow (OPF. In fact, by using of Benders algorithm the problem is divided into two major and minor problems. Therefore, the major problem related to the economy sector and no network is included and the minor problem is to solve the network and examine the accuracy of the network. Benders algorithm has been tested on a standard network IEEE 24 bus and Matlab software is used to implement the algorithm.
Diversity Controlling Genetic Algorithm for Order Acceptance and Scheduling Problem
Directory of Open Access Journals (Sweden)
Cheng Chen
2014-01-01
Full Text Available Selection and scheduling are an important topic in production systems. To tackle the order acceptance and scheduling problem on a single machine with release dates, tardiness penalty, and sequence-dependent setup times, in this paper a diversity controlling genetic algorithm (DCGA is proposed, in which a diversified population is maintained during the whole search process through survival selection considering both the fitness and the diversity of individuals. To measure the similarity between individuals, a modified Hamming distance without considering the unaccepted orders in the chromosome is adopted. The proposed DCGA was validated on 1500 benchmark instances with up to 100 orders. Compared with the state-of-the-art algorithms, the experimental results show that DCGA improves the solution quality obtained significantly, in terms of the deviation from upper bound.
Traffic Congestion Detection System through Connected Vehicles and Big Data.
Cárdenas-Benítez, Néstor; Aquino-Santos, Raúl; Magaña-Espinoza, Pedro; Aguilar-Velazco, José; Edwards-Block, Arthur; Medina Cass, Aldo
2016-04-28
This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO₂ and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility) traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur.
A cooperative control algorithm for camera based observational systems.
Energy Technology Data Exchange (ETDEWEB)
Young, Joseph G.
2012-01-01
Over the last several years, there has been considerable growth in camera based observation systems for a variety of safety, scientific, and recreational applications. In order to improve the effectiveness of these systems, we frequently desire the ability to increase the number of observed objects, but solving this problem is not as simple as adding more cameras. Quite often, there are economic or physical restrictions that prevent us from adding additional cameras to the system. As a result, we require methods that coordinate the tracking of objects between multiple cameras in an optimal way. In order to accomplish this goal, we present a new cooperative control algorithm for a camera based observational system. Specifically, we present a receding horizon control where we model the underlying optimal control problem as a mixed integer linear program. The benefit of this design is that we can coordinate the actions between each camera while simultaneously respecting its kinematics. In addition, we further improve the quality of our solution by coupling our algorithm with a Kalman filter. Through this integration, we not only add a predictive component to our control, but we use the uncertainty estimates provided by the filter to encourage the system to periodically observe any outliers in the observed area. This combined approach allows us to intelligently observe the entire region of interest in an effective and thorough manner.
Combined Intelligent Control (CIC an Intelligent Decision Making Algorithm
Directory of Open Access Journals (Sweden)
Moteaal Asadi Shirzi
2007-03-01
Full Text Available The focus of this research is to introduce the concept of combined intelligent control (CIC as an effective architecture for decision-making and control of intelligent agents and multi-robot sets. Basically, the CIC is a combination of various architectures and methods from fields such as artificial intelligence, Distributed Artificial Intelligence (DAI, control and biological computing. Although any intelligent architecture may be very effective for some specific applications, it could be less for others. Therefore, CIC combines and arranges them in a way that the strengths of any approach cover the weaknesses of others. In this paper first, we introduce some intelligent architectures from a new aspect. Afterward, we offer the CIC by combining them. CIC has been executed in a multi-agent set. In this set, robots must cooperate to perform some various tasks in a complex and nondeterministic environment with a low sensory feedback and relationship. In order to investigate, improve, and correct the combined intelligent control method, simulation software has been designed which will be presented and considered. To show the ability of the CIC algorithm as a distributed architecture, a central algorithm is designed and compared with the CIC.
Air congestion delay: a review
Directory of Open Access Journals (Sweden)
Daniel Alberto Pamplona
2016-04-01
Full Text Available This article is a literature review of the air congestion delay and its costs. Air congestion is a worldwide problem. Its existence brings costs for airlines and discomfort for passengers. With the increasing demand for air transport, the study of air congestion has attracted the attention of many researchers around the world. The cause for the delays is erroneously attributed only to the lack of infrastructure investments. The literature review shows that other factors such as population growth, increasing standards of living, lack of operational planning and environmental issues exercise decisive influence. Several studies have been conducted in order to analyze and propose solutions to this problem that affects society as a whole.
Endogenous scheduling preferences and congestion
DEFF Research Database (Denmark)
Fosgerau, Mogens; Small, Kenneth
2017-01-01
We consider the timing of activities through a dynamic model of commuting with congestion, in which workers care solely about leisure and consumption. Implicit preferences for the timing of the commute form endogenously due to temporal agglomeration economies. Equilibrium exists uniquely and is i......We consider the timing of activities through a dynamic model of commuting with congestion, in which workers care solely about leisure and consumption. Implicit preferences for the timing of the commute form endogenously due to temporal agglomeration economies. Equilibrium exists uniquely...... and is indistinguishable from that of a generalized version of the classical Vickrey bottleneck model, based on exogenous trip-timing preferences, but optimal policies differ: the Vickrey model will misstate the benefits of a capacity increase, it will underpredict the benefits of congestion pricing, and pricing may make...
International Nuclear Information System (INIS)
Kim, Dong Yun
1997-02-01
In this research, we propose a fuzzy gain scheduler (FGS) with an intelligent learning algorithm for a reactor control. In the proposed algorithm, the gradient descent method is used in order to generate the rule bases of a fuzzy algorithm by learning. These rule bases are obtained by minimizing an objective function, which is called a performance cost function. The objective of the FGS with an intelligent learning algorithm is to generate adequate gains, which minimize the error of system. The proposed algorithm can reduce the time and efforts required for obtaining the fuzzy rules through the intelligent learning function. The evolutionary programming algorithm is modified and adopted as the method in order to find the optimal gains which are used as the initial gains of FGS with learning function. It is applied to reactor control of nuclear power plant (NPP), and the results are compared with those of a conventional PI controller with fixed gains. As a result, it is shown that the proposed algorithm is superior to the conventional PI controller
Dynamic Power Tariff for Congestion Management in Distribution Networks
DEFF Research Database (Denmark)
Huang, Shaojun; Wu, Qiuwei; Shahidehpour, Mohammad
2018-01-01
This paper proposes dynamic power tariff (DPT), a new concept for congestion management in distribution networks with high penetration of electric vehicles (EVs), and heat pumps (HPs). The DPT concept is proposed to overcome a drawback of the dynamic tariff (DT) method, i.e., DPT can replace...... the price sensitivity parameter in the DT method, which is relatively unrealistic in practice. Based on the control theory, a control model with two control loops, i.e., the power flow control and voltage control, is established to analyze the congestion management process by the DPT method. Furthermore...
Congestion Service Facilities Location Problem with Promise of Response Time
Directory of Open Access Journals (Sweden)
Dandan Hu
2013-01-01
Full Text Available In many services, promise of specific response time is advertised as a commitment by the service providers for the customer satisfaction. Congestion on service facilities could delay the delivery of the services and hurts the overall satisfaction. In this paper, congestion service facilities location problem with promise of response time is studied, and a mixed integer nonlinear programming model is presented with budget constrained. The facilities are modeled as M/M/c queues. The decision variables of the model are the locations of the service facilities and the number of servers at each facility. The objective function is to maximize the demands served within specific response time promised by the service provider. To solve this problem, we propose an algorithm that combines greedy and genetic algorithms. In order to verify the proposed algorithm, a lot of computational experiments are tested. And the results demonstrate that response time has a significant impact on location decision.
Optimization Design by Genetic Algorithm Controller for Trajectory Control of a 3-RRR Parallel Robot
Directory of Open Access Journals (Sweden)
Lianchao Sheng
2018-01-01
Full Text Available In order to improve the control precision and robustness of the existing proportion integration differentiation (PID controller of a 3-Revolute–Revolute–Revolute (3-RRR parallel robot, a variable PID parameter controller optimized by a genetic algorithm controller is proposed in this paper. Firstly, the inverse kinematics model of the 3-RRR parallel robot was established according to the vector method, and the motor conversion matrix was deduced. Then, the error square integral was chosen as the fitness function, and the genetic algorithm controller was designed. Finally, the control precision of the new controller was verified through the simulation model of the 3-RRR planar parallel robot—built in SimMechanics—and the robustness of the new controller was verified by adding interference. The results show that compared with the traditional PID controller, the new controller designed in this paper has better control precision and robustness, which provides the basis for practical application.
Endogenous scheduling preferences and congestion
DEFF Research Database (Denmark)
Fosgerau, Mogens; Small, Kenneth
2010-01-01
and leisure, but agglomeration economies at home and at work lead to scheduling preferences forming endogenously. Using bottleneck congestion technology, we obtain an equilibrium queuing pattern consistent with a general version of the Vickrey bottleneck model. However, the policy implications are different....... Compared to the predictions of an analyst observing untolled equilibrium and taking scheduling preferences as exogenous, we find that both the optimal capacity and the marginal external cost of congestion have changed. The benefits of tolling are greater, and the optimal time varying toll is different....
Indian Academy of Sciences (India)
ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...
Navigation Algorithm Using Fuzzy Control Method in Mobile Robotics
Directory of Open Access Journals (Sweden)
Cviklovič Vladimír
2016-03-01
Full Text Available The issue of navigation methods is being continuously developed globally. The aim of this article is to test the fuzzy control algorithm for track finding in mobile robotics. The concept of an autonomous mobile robot EN20 has been designed to test its behaviour. The odometry navigation method was used. The benefits of fuzzy control are in the evidence of mobile robot’s behaviour. These benefits are obtained when more physical variables on the base of more input variables are controlled at the same time. In our case, there are two input variables - heading angle and distance, and two output variables - the angular velocity of the left and right wheel. The autonomous mobile robot is moving with human logic.
DOOCS environment for FPGA-based cavity control system and control algorithms development
International Nuclear Information System (INIS)
Pucyk, P.; Koprek, W.; Kaleta, P.; Szewinski, J.; Pozniak, K.T.; Czarski, T.; Romaniuk, R.S.
2005-01-01
The paper describes the concept and realization of the DOOCS control software for FPGAbased TESLA cavity controller and simulator (SIMCON). It bases on universal software components, created for laboratory purposes and used in MATLAB based control environment. These modules have been recently adapted to the DOOCS environment to ensure a unified software to hardware communication model. The presented solution can be also used as a general platform for control algorithms development. The proposed interfaces between MATLAB and DOOCS modules allow to check the developed algorithm in the operation environment before implementation in the FPGA. As the examples two systems have been presented. (orig.)
Framework for Traffic Congestion Prediction
Zaki, J.F.W.; Ali-Eldin, A.M.T.; Hussein, S.E.; Saraya, S.F.; Areed, F.F.
2016-01-01
Traffic Congestion is a complex dilemma facing most major cities. It has undergone a lot of research since the early 80s in an attempt to predict traffic in the short-term. Recently, Intelligent Transportation Systems (ITS) became an integral part of traffic research which helped in modeling and
Congestion and residential moving behaviour
DEFF Research Database (Denmark)
Larsen, Morten Marott; Pilegaard, Ninette; Van Ommeren, Jos
2008-01-01
to congestion. We focus on the equilibrium in which some workers currently living in one region accept jobs in the other, with a fraction of them choosing to commute from their current residence to the new job in the other region and the remainder choosing to move to the region in which the new job is located...
Advanced illumination control algorithm for medical endoscopy applications
Sousa, Ricardo M.; Wäny, Martin; Santos, Pedro; Morgado-Dias, F.
2015-05-01
CMOS image sensor manufacturer, AWAIBA, is providing the world's smallest digital camera modules to the world market for minimally invasive surgery and one time use endoscopic equipment. Based on the world's smallest digital camera head and the evaluation board provided to it, the aim of this paper is to demonstrate an advanced fast response dynamic control algorithm of the illumination LED source coupled to the camera head, over the LED drivers embedded on the evaluation board. Cost efficient and small size endoscopic camera modules nowadays embed minimal size image sensors capable of not only adjusting gain and exposure time but also LED illumination with adjustable illumination power. The LED illumination power has to be dynamically adjusted while navigating the endoscope over changing illumination conditions of several orders of magnitude within fractions of the second to guarantee a smooth viewing experience. The algorithm is centered on the pixel analysis of selected ROIs enabling it to dynamically adjust the illumination intensity based on the measured pixel saturation level. The control core was developed in VHDL and tested in a laboratory environment over changing light conditions. The obtained results show that it is capable of achieving correction speeds under 1 s while maintaining a static error below 3% relative to the total number of pixels on the image. The result of this work will allow the integration of millimeter sized high brightness LED sources on minimal form factor cameras enabling its use in endoscopic surgical robotic or micro invasive surgery.
Combustion distribution control using the extremum seeking algorithm
Marjanovic, A.; Krstic, M.; Djurovic, Z.; Kvascev, G.; Papic, V.
2014-12-01
Quality regulation of the combustion process inside the furnace is the basis of high demands for increasing robustness, safety and efficiency of thermal power plants. The paper considers the possibility of spatial temperature distribution control inside the boiler, based on the correction of distribution of coal over the mills. Such control system ensures the maintenance of the flame focus away from the walls of the boiler, and thus preserves the equipment and reduces the possibility of ash slugging. At the same time, uniform heat dissipation over mills enhances the energy efficiency of the boiler, while reducing the pollution of the system. A constrained multivariable extremum seeking algorithm is proposed as a tool for combustion process optimization with the main objective of centralizing the flame in the furnace. Simulations are conducted on a model corresponding to the 350MW boiler of the Nikola Tesla Power Plant, in Obrenovac, Serbia.
Combustion distribution control using the extremum seeking algorithm
International Nuclear Information System (INIS)
Marjanovic, A; Djurovic, Z; Kvascev, G; Papic, V; Krstic, M
2014-01-01
Quality regulation of the combustion process inside the furnace is the basis of high demands for increasing robustness, safety and efficiency of thermal power plants. The paper considers the possibility of spatial temperature distribution control inside the boiler, based on the correction of distribution of coal over the mills. Such control system ensures the maintenance of the flame focus away from the walls of the boiler, and thus preserves the equipment and reduces the possibility of ash slugging. At the same time, uniform heat dissipation over mills enhances the energy efficiency of the boiler, while reducing the pollution of the system. A constrained multivariable extremum seeking algorithm is proposed as a tool for combustion process optimization with the main objective of centralizing the flame in the furnace. Simulations are conducted on a model corresponding to the 350MW boiler of the Nikola Tesla Power Plant, in Obrenovac, Serbia
OPTIMAL CONGESTION CHARGES IN GENERAL EQUILIBRIUM
Directory of Open Access Journals (Sweden)
Dong-Joo MOON, Ph.D.
2002-01-01
Another maximization problem involves characterizing the second-best optimal solution. In this problem, it is assumed to impose the congestion toll only on a single highway link. This problem yields the second-best congestion toll different from the first-best one. This second-best optimal congestion toll has the structure to reflect its impact on other highway links exempt from the congestion charge program.
Application of Fuzzy Algorithm in Optimizing Hierarchical Sliding Mode Control for Pendubot System
Directory of Open Access Journals (Sweden)
Xuan Dung Huynh
2017-12-01
Full Text Available Pendubot is a classical under-actuated SIMO model for control algorithm testing in laboratory of universities. In this paper, authors design a fuzzy-sliding control for this system. The controller is designed from a new idea of application of fuzzy algorithm for optioning control parameters. The response of system on TOP position under fuzzysliding control algorithm is proved to be better than under sliding controller through Matlab/Simulink simulation.
Indian Academy of Sciences (India)
algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).
Indian Academy of Sciences (India)
algorithm that it is implicitly understood that we know how to generate the next natural ..... Explicit comparisons are made in line (1) where maximum and minimum is ... It can be shown that the function T(n) = 3/2n -2 is the solution to the above ...
Directory of Open Access Journals (Sweden)
W. H. Kwong
2000-06-01
Full Text Available The development of a new simplified model predictive control algorithm has been proposed in this work. The algorithm is developed within the framework of internal model control, and it is easy to understanding and implement. Simulation results for a continuous fermenter, which show that the proposed control algorithm is robust for moderate variations in plant parameters, are presented. The algorithm shows a good performance for setpoint tracking.
Algorithm for Public Electric Transport Schedule Control for Intelligent Embedded Devices
Alps, Ivars; Potapov, Andrey; Gorobetz, Mikhail; Levchenkov, Anatoly
2010-01-01
In this paper authors present heuristics algorithm for precise schedule fulfilment in city traffic conditions taking in account traffic lights. The algorithm is proposed for programmable controller. PLC is proposed to be installed in electric vehicle to control its motion speed and signals of traffic lights. Algorithm is tested using real controller connected to virtual devices and real functional models of real tram devices. Results of experiments show high precision of public transport schedule fulfilment using proposed algorithm.
The product composition control system at Savannah River: Statistical process control algorithm
International Nuclear Information System (INIS)
Brown, K.G.
1994-01-01
The Defense Waste Processing Facility (DWPF) at the Savannah River Site (SRS) will be used to immobilize the approximately 130 million liters of high-level nuclear waste currently stored at the site in 51 carbon steel tanks. Waste handling operations separate this waste into highly radioactive insoluble sludge and precipitate and less radioactive water soluble salts. In DWPF, precipitate (PHA) is blended with insoluble sludge and ground glass frit to produce melter feed slurry which is continuously fed to the DWPF melter. The melter produces a molten borosilicate glass which is poured into stainless steel canisters for cooling and, ultimately, shipment to and storage in an geologic repository. Described here is the Product Composition Control System (PCCS) process control algorithm. The PCCS is the amalgam of computer hardware and software intended to ensure that the melt will be processable and that the glass wasteform produced will be acceptable. Within PCCS, the Statistical Process Control (SPC) Algorithm is the means which guides control of the DWPF process. The SPC Algorithm is necessary to control the multivariate DWPF process in the face of uncertainties arising from the process, its feeds, sampling, modeling, and measurement systems. This article describes the functions performed by the SPC Algorithm, characterization of DWPF prior to making product, accounting for prediction uncertainty, accounting for measurement uncertainty, monitoring a SME batch, incorporating process information, and advantages of the algorithm. 9 refs., 6 figs
COALA: A Protocol for the Avoidance and Alleviation of Congestion in Wireless Sensor Networks.
Kandris, Dionisis; Tselikis, George; Anastasiadis, Eleftherios; Panaousis, Emmanouil; Dagiuklas, Tasos
2017-10-31
The occurrence of congestion has an extremely deleterious impact on the performance of Wireless Sensor Networks (WSNs). This article presents a novel protocol, named COALA ( COngestion ALleviation and Avoidance ), which aims to act both proactively, in order to avoid the creation of congestion in WSNs, and reactively, so as to mitigate the diffusion of upcoming congestion through alternative path routing. Its operation is based on the utilization of an accumulative cost function, which considers both static and dynamic metrics in order to send data through the paths that are less probable to be congested. COALA is validated through simulation tests, which exhibit its ability to achieve remarkable reduction of loss ratios, transmission delays and energy dissipation. Moreover, the appropriate adjustment of the weighting of the accumulative cost function enables the algorithm to adapt to the performance criteria of individual case scenarios.
COALA: A Protocol for the Avoidance and Alleviation of Congestion in Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Dionisis Kandris
2017-10-01
Full Text Available The occurrence of congestion has an extremely deleterious impact on the performance of Wireless Sensor Networks (WSNs. This article presents a novel protocol, named COALA (COngestion ALleviation and Avoidance, which aims to act both proactively, in order to avoid the creation of congestion in WSNs, and reactively, so as to mitigate the diffusion of upcoming congestion through alternative path routing. Its operation is based on the utilization of an accumulative cost function, which considers both static and dynamic metrics in order to send data through the paths that are less probable to be congested. COALA is validated through simulation tests, which exhibit its ability to achieve remarkable reduction of loss ratios, transmission delays and energy dissipation. Moreover, the appropriate adjustment of the weighting of the accumulative cost function enables the algorithm to adapt to the performance criteria of individual case scenarios.
Reactor controller design using genetic algorithm with simulated annealing
International Nuclear Information System (INIS)
Willjuice Iruthyarajan, M.
2012-01-01
Many reactor control design work, specifically the problem of synthesis and optimization of reactor networks involving the classical reaction schemes was studied, considering a superstructure formed by a CSTR and a PFR and their possible arrangements. A genetic algorithm was proposed, together with a systematic procedure. Two case studies were solved with the proposed systematic. Both of them present similar results than the published in the literature. The first case studied was the Trambouze reaction scheme. Although selectivity values are smaller then the values published in the referred papers, the reactors system combined volume is always minor them the other ones. The second case studied was the Van de Vusse reaction scheme. In this case, the obtained value for the total volume is always minor then the considered papers. One can conclude that when compared with the other works presented in the literature results are compatible and very interesting. The developed algorithms can be used as a good alternative for reactor networks design and optimization problem
Energy Optimal Control Strategy of PHEV Based on PMP Algorithm
Directory of Open Access Journals (Sweden)
Tiezhou Wu
2017-01-01
Full Text Available Under the global voice of “energy saving” and the current boom in the development of energy storage technology at home and abroad, energy optimal control of the whole hybrid electric vehicle power system, as one of the core technologies of electric vehicles, is bound to become a hot target of “clean energy” vehicle development and research. This paper considers the constraints to the performance of energy storage system in Parallel Hybrid Electric Vehicle (PHEV, from which lithium-ion battery frequently charges/discharges, PHEV largely consumes energy of fuel, and their are difficulty in energy recovery and other issues in a single cycle; the research uses lithium-ion battery combined with super-capacitor (SC, which is hybrid energy storage system (Li-SC HESS, working together with internal combustion engine (ICE to drive PHEV. Combined with PSO-PI controller and Li-SC HESS internal power limited management approach, the research proposes the PHEV energy optimal control strategy. It is based on revised Pontryagin’s minimum principle (PMP algorithm, which establishes the PHEV vehicle simulation model through ADVISOR software and verifies the effectiveness and feasibility. Finally, the results show that the energy optimization control strategy can improve the instantaneity of tracking PHEV minimum fuel consumption track, implement energy saving, and prolong the life of lithium-ion batteries and thereby can improve hybrid energy storage system performance.
International Nuclear Information System (INIS)
Kim, Dong Yun; Seong, Poong Hyun
1996-01-01
In this study, we proposed a fuzzy gain scheduler with intelligent learning algorithm for a reactor control. In the proposed algorithm, we used the gradient descent method to learn the rule bases of a fuzzy algorithm. These rule bases are learned toward minimizing an objective function, which is called a performance cost function. The objective of fuzzy gain scheduler with intelligent learning algorithm is the generation of adequate gains, which minimize the error of system. The condition of every plant is generally changed as time gose. That is, the initial gains obtained through the analysis of system are no longer suitable for the changed plant. And we need to set new gains, which minimize the error stemmed from changing the condition of a plant. In this paper, we applied this strategy for reactor control of nuclear power plant (NPP), and the results were compared with those of a simple PI controller, which has fixed gains. As a result, it was shown that the proposed algorithm was superior to the simple PI controller
Indian Academy of Sciences (India)
will become clear in the next article when we discuss a simple logo like programming language. ... Rod B may be used as an auxiliary store. The problem is to find an algorithm which performs this task. ... No disks are moved from A to Busing C as auxiliary rod. • move _disk (A, C);. (No + l)th disk is moved from A to C directly ...
Wavelet Adaptive Algorithm and Its Application to MRE Noise Control System
Directory of Open Access Journals (Sweden)
Zhang Yulin
2015-01-01
Full Text Available To address the limitation of conventional adaptive algorithm used for active noise control (ANC system, this paper proposed and studied two adaptive algorithms based on Wavelet. The twos are applied to a noise control system including magnetorheological elastomers (MRE, which is a smart viscoelastic material characterized by a complex modulus dependent on vibration frequency and controllable by external magnetic fields. Simulation results reveal that the Decomposition LMS algorithm (D-LMS and Decomposition and Reconstruction LMS algorithm (DR-LMS based on Wavelet can significantly improve the noise reduction performance of MRE control system compared with traditional LMS algorithm.
Towards Scalable Distributed Framework for Urban Congestion Traffic Patterns Warehousing
Directory of Open Access Journals (Sweden)
A. Boulmakoul
2015-01-01
Full Text Available We put forward architecture of a framework for integration of data from moving objects related to urban transportation network. Most of this research refers to the GPS outdoor geolocation technology and uses distributed cloud infrastructure with big data NoSQL database. A network of intelligent mobile sensors, distributed on urban network, produces congestion traffic patterns. Congestion predictions are based on extended simulation model. This model provides traffic indicators calculations, which fuse with the GPS data for allowing estimation of traffic states across the whole network. The discovery process of congestion patterns uses semantic trajectories metamodel given in our previous works. The challenge of the proposed solution is to store patterns of traffic, which aims to ensure the surveillance and intelligent real-time control network to reduce congestion and avoid its consequences. The fusion of real-time data from GPS-enabled smartphones integrated with those provided by existing traffic systems improves traffic congestion knowledge, as well as generating new information for a soft operational control and providing intelligent added value for transportation systems deployment.
Modelling and experimental study for automated congestion driving
Urhahne, Joseph; Piastowski, P.; van der Voort, Mascha C.; Bebis, G; Boyle, R.; Parvin, B.; Koracin, D.; Pavlidis, I.; Feris, R.; McGraw, T.; Elendt, M.; Kopper, R.; Ragan, E.; Ye, Z.; Weber, G.
2015-01-01
Taking a collaborative approach in automated congestion driving with a Traffic Jam Assist system requires the driver to take over control in certain traffic situations. In order to warn the driver appropriately, warnings are issued (“pay attention” vs. “take action”) due to a control transition
Radiotherapy for hypersplenism from congestive splenomegaly
International Nuclear Information System (INIS)
Liu, Mu-Tai; Hsieh, Chang-Yo; Chang, Tung-Hao; Lin, Jao-Perng; Huang, Chia-Chun
2004-01-01
We evaluated the effects of splenic irradiation on the common hematological disorders of hypersplenism. From August 2002 to March 2003, five patients with hypersplenism due to congestive splenomegaly underwent splenic irradiation at the Department od Radiation Oncology, Changhua Chirstian Hospital, Taiwan. 3 were males and 2 were females aging from 38 to 66 years. All patients had history of liver cirrhosis. 4 patients underwent thee-dimensional conformal radiotherapy and received conventional radiotherapy with anterior-posterior parallel opposing fields. The followup-period ranged from 1 to 7 months. Thrombocytopenia and splenomegaly were found in all 5 patients by physical examination, hematological test, abdominal sonography and/or abdominal computed tomography. After radiotherapy, thrombocytopenia improved, but leukopenia and anemia did not. No complication due to radiotherapy was found during the follow-up period after splenic irradiation. 2 patients died of hepatocellular carcinoma with active bleeding. One patient died of renal failure due to end-stage renal disease. Based on our results, it seems that splenic irradiation might be effective in treating thrombocytopenia and splenomegaly. Splenic irradiatin seems to be effective for thrombocytopenia, splenomegaly and splenic pain associated with hypersplenism from congenstive splenomegaly. This approach is non-invasive and may be an alternative treatment for splenectomy and splenic embolization for patients with hypersplenism due to congestive splenomegaly. The shortcoming of this study are small sample size, short period of follow-up and lack of randomization. A randomized control trial with more cases and further follow-up of hematological tests and splenic size estimation are warranted to evaluate long term improvement of congestive splenomegaly with thrombocytopeniaafter splenic irradiation
Green supply chain: Simulating road traffic congestion
Jalal, Muhammad Zulqarnain Hakim Abd; Nawawi, Mohd Kamal Mohd; Laailatul Hanim Mat Desa, Wan; Khalid, Ruzelan; Khalid Abduljabbar, Waleed; Ramli, Razamin
2017-09-01
With the increasing awareness of the consumers about environmental issues, businesses, households and governments increasingly want use green products and services which lead to green supply chain. This paper discusses a simulation study of a selected road traffic system that will contribute to the air pollution if in the congestion state. Road traffic congestion (RTC) can be caused by a temporary obstruction, a permanent capacity bottleneck in the network itself, and stochastic fluctuation in demand within a particular sector of the network, leading to spillback and queue propagation. A discrete-event simulation model is developed to represent the real traffic light control (TLC) system condition during peak hours. Certain performance measures such as average waiting time and queue length were measured using the simulation model. Existing system uses pre-set cycle time to control the light changes which is fixed time cycle. In this research, we test several other combination of pre-set cycle time with the objective to find the best system. In addition, we plan to use a combination of the pre-set cycle time and a proximity sensor which have the authority to manipulate the cycle time of the lights. The sensors work in such situation when the street seems to have less occupied vehicles, obviously it may not need a normal cycle for green light, and automatically change the cycle to street where vehicle is present.
Directory of Open Access Journals (Sweden)
Gang Qin
2015-01-01
Full Text Available The acceleration performance of EV, which affects a lot of performances of EV such as start-up, overtaking, driving safety, and ride comfort, has become increasingly popular in recent researches. An improved variable gain PID control algorithm to improve the acceleration performance is proposed in this paper. The results of simulation with Matlab/Simulink demonstrate the effectiveness of the proposed algorithm through the control performance of motor velocity, motor torque, and three-phase current of motor. Moreover, it is investigated that the proposed controller is valid by comparison with the other PID controllers. Furthermore, the AC induction motor experiment set is constructed to verify the effect of proposed controller.
Energy Technology Data Exchange (ETDEWEB)
Perez C, B
2003-07-01
In this thesis work there are presented: a) The characteristics and main components used in an electronic system based on a Dsp guided to control applications of processes, b) The description of an algorithm of diffuse control whose objective is the regulation of neutron power in a model of the punctual kinetics of a nuclear research reactor type TRIGA, and c) The installation in language assembler and execution in real time of the control algorithm in the system based on a Dsp. With regard to the installation and execution of the algorithm, the reaches of the project have been delimited to the following: a) Readiness of the entrance values to the controller in specific registrations of the system Dsp, b) Conversion of the entrances to the numerical formats with those that one obtains the best acting in the control algorithm, c) Execution of the algorithm until the obtaining of the value of the controller's exit, and d) Placement of the result in specific registrations of the Dsp for their later reading for an external parallel interface. It is necessary to mention that the simulation of the punctual kinetics of a reactor type TRIGA in the Pc and its integration with the control system based on the one Dsp is had contemplated as continuation of this work and that one of those will constitute main activities in my project of master thesis. A brief description of the topics presented in this thesis is given next. In the chapter one it is presented a general description of the diffuse logic and some of their applications in the industry. The main characteristics of a Dsp are also presented that they make it different from a micro controller or a microprocessor of general purpose. In the chapter 2 details of the internal architecture of the Dsp TMS320CS0 of Texas Instruments that are not explained with detail in the manual of user of the same one. This chapter has as objective to understand the internal hardware of the Dsp that is used for to carry out the program in
Energy Technology Data Exchange (ETDEWEB)
Perez C, B
2003-07-01
In this thesis work there are presented: a) The characteristics and main components used in an electronic system based on a Dsp guided to control applications of processes, b) The description of an algorithm of diffuse control whose objective is the regulation of neutron power in a model of the punctual kinetics of a nuclear research reactor type TRIGA, and c) The installation in language assembler and execution in real time of the control algorithm in the system based on a Dsp. With regard to the installation and execution of the algorithm, the reaches of the project have been delimited to the following: a) Readiness of the entrance values to the controller in specific registrations of the system Dsp, b) Conversion of the entrances to the numerical formats with those that one obtains the best acting in the control algorithm, c) Execution of the algorithm until the obtaining of the value of the controller's exit, and d) Placement of the result in specific registrations of the Dsp for their later reading for an external parallel interface. It is necessary to mention that the simulation of the punctual kinetics of a reactor type TRIGA in the Pc and its integration with the control system based on the one Dsp is had contemplated as continuation of this work and that one of those will constitute main activities in my project of master thesis. A brief description of the topics presented in this thesis is given next. In the chapter one it is presented a general description of the diffuse logic and some of their applications in the industry. The main characteristics of a Dsp are also presented that they make it different from a micro controller or a microprocessor of general purpose. In the chapter 2 details of the internal architecture of the Dsp TMS320CS0 of Texas Instruments that are not explained with detail in the manual of user of the same one. This chapter has as objective to understand the internal hardware of the Dsp that is used for to carry out the program
Debbarma, Sanjoy; Saikia, Lalit Chandra; Sinha, Nidul
2014-03-01
Present work focused on automatic generation control (AGC) of a three unequal area thermal systems considering reheat turbines and appropriate generation rate constraints (GRC). A fractional order (FO) controller named as I(λ)D(µ) controller based on crone approximation is proposed for the first time as an appropriate technique to solve the multi-area AGC problem in power systems. A recently developed metaheuristic algorithm known as firefly algorithm (FA) is used for the simultaneous optimization of the gains and other parameters such as order of integrator (λ) and differentiator (μ) of I(λ)D(µ) controller and governor speed regulation parameters (R). The dynamic responses corresponding to optimized I(λ)D(µ) controller gains, λ, μ, and R are compared with that of classical integer order (IO) controllers such as I, PI and PID controllers. Simulation results show that the proposed I(λ)D(µ) controller provides more improved dynamic responses and outperforms the IO based classical controllers. Further, sensitivity analysis confirms the robustness of the so optimized I(λ)D(µ) controller to wide changes in system loading conditions and size and position of SLP. Proposed controller is also found to have performed well as compared to IO based controllers when SLP takes place simultaneously in any two areas or all the areas. Robustness of the proposed I(λ)D(µ) controller is also tested against system parameter variations. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
DEFF Research Database (Denmark)
Conrad, Finn; Zhou, Jianjun; Gabacik, Andrzej
1998-01-01
Invited paper presents a new control algorithm based on feed-forward geometrical compensation strategy combined with adaptive feedback control.......Invited paper presents a new control algorithm based on feed-forward geometrical compensation strategy combined with adaptive feedback control....
Qiang, Jiang; Meng-wei, Liao; Ming-jie, Luo
2018-03-01
Abstract.The control performance of Permanent Magnet Synchronous Motor will be affected by the fluctuation or changes of mechanical parameters when PMSM is applied as driving motor in actual electric vehicle,and external disturbance would influence control robustness.To improve control dynamic quality and robustness of PMSM speed control system, a new second order integral sliding mode control algorithm is introduced into PMSM vector control.The simulation results show that, compared with the traditional PID control,the modified control scheme optimized has better control precision and dynamic response ability and perform better with a stronger robustness facing external disturbance,it can effectively solve the traditional sliding mode variable structure control chattering problems as well.
PSO-RBF Neural Network PID Control Algorithm of Electric Gas Pressure Regulator
Directory of Open Access Journals (Sweden)
Yuanchang Zhong
2014-01-01
Full Text Available The current electric gas pressure regulator often adopts the conventional PID control algorithm to take drive control of the core part (micromotor of electric gas pressure regulator. In order to further improve tracking performance and to shorten response time, this paper presents an improved PID intelligent control algorithm which applies to the electric gas pressure regulator. The algorithm uses the improved RBF neural network based on PSO algorithm to make online adjustment on PID parameters. Theoretical analysis and simulation result show that the algorithm shortens the step response time and improves tracking performance.
Pole placement algorithm for control of civil structures subjected to earthquake excitation
Directory of Open Access Journals (Sweden)
Nikos Pnevmatikos
2017-04-01
Full Text Available In this paper the control algorithm for controlled civil structures subjected to earthquake excitation is thoroughly investigated. The objective of this work is the control of structures by means of the pole placement algorithm, in order to improve their response against earthquake actions. Successful application of the algorithm requires judicious placement of the closed-loop eigenvalues from the part of the designer. The pole placement algorithm was widely applied to control mechanical systems. In this paper, a modification in the mathematical background of the algorithm in order to be suitable for civil fixed structures is primarily presented. The proposed approach is demonstrated by numerical simulations for the control of both single and multi-degree of freedom systems subjected to seismic actions. Numerical results have shown that the control algorithm is efficient in reducing the response of building structures, with small amount of required control forces.
A Compatible Control Algorithm for Greenhouse Environment Control Based on MOCC Strategy
Directory of Open Access Journals (Sweden)
Bingkun Zhu
2011-03-01
Full Text Available Conventional methods used for solving greenhouse environment multi-objective conflict control problems lay excessive emphasis on control performance and have inadequate consideration for both energy consumption and special requirements for plant growth. The resulting solution will cause higher energy cost. However, during the long period of work and practice, we find that it may be more reasonable to adopt interval or region control objectives instead of point control objectives. In this paper, we propose a modified compatible control algorithm, and employ Multi-Objective Compatible Control (MOCC strategy and an extant greenhouse model to achieve greenhouse climate control based on feedback control architecture. A series of simulation experiments through various comparative studies are presented to validate the feasibility of the proposed algorithm. The results are encouraging and suggest the energy-saving application to real-world engineering problems in greenhouse production. It may be valuable and helpful to formulate environmental control strategies, and to achieve high control precision and low energy cost for real-world engineering application in greenhouse production. Moreover, the proposed approach has also potential to be useful for other practical control optimization problems with the features like the greenhouse environment control system.
A compatible control algorithm for greenhouse environment control based on MOCC strategy.
Hu, Haigen; Xu, Lihong; Zhu, Bingkun; Wei, Ruihua
2011-01-01
Conventional methods used for solving greenhouse environment multi-objective conflict control problems lay excessive emphasis on control performance and have inadequate consideration for both energy consumption and special requirements for plant growth. The resulting solution will cause higher energy cost. However, during the long period of work and practice, we find that it may be more reasonable to adopt interval or region control objectives instead of point control objectives. In this paper, we propose a modified compatible control algorithm, and employ Multi-Objective Compatible Control (MOCC) strategy and an extant greenhouse model to achieve greenhouse climate control based on feedback control architecture. A series of simulation experiments through various comparative studies are presented to validate the feasibility of the proposed algorithm. The results are encouraging and suggest the energy-saving application to real-world engineering problems in greenhouse production. It may be valuable and helpful to formulate environmental control strategies, and to achieve high control precision and low energy cost for real-world engineering application in greenhouse production. Moreover, the proposed approach has also potential to be useful for other practical control optimization problems with the features like the greenhouse environment control system.
International Nuclear Information System (INIS)
Ardian, Faddy; Concettini, Silvia; Creti, Anna
2015-01-01
The literature demonstrates the likely reduction of wholesale electricity prices due to a larger penetration of renewable energy sources (RES). When markets are organized as two or more inter-connected sub-markets within a larger power market the final impact of increasing RES production may be less straightforward given the presence of network constraints. We tests this phenomenon by analyzing the impact of RES production on the probability of congestion and on the size of congestion cost in Italy. Using a database with hourly observations for a five year period we estimate two econometric models on five zonal pairings: a multinomial logit model for the occurrence and direction of congestion and a three stage least square model for the size of congestion costs. The analysis suggests that the effect of a larger local wind and solar supply is to decrease the probability of suffering congestion in entry and to increase the probability of causing a congestion in exit compared to no congestion case. Increasing hydroelectric production has a similar effect. These results hold for both importing and exporting regions, but importing regions are less likely to cause congestion in exit, therefore the installation of new RES capacity in these zones may have a positive effects in terms of flow balance between regions. Concerning the cost level, a larger local RES supply seems to push the congestion cost towards negative values as it decreases the marginal cost for balancing the system. This is true for all zones in the case of explicit congestion cost, but it is only verified in importing regions in the case of implicit congestion cost. This result suggests that the increase of RES production should be promoted in importing zones, but the overall growth should be controlled in order to avoid congestion in the opposite direction. (authors)
Energy Technology Data Exchange (ETDEWEB)
Goddard, H.C. [Instituto Tecnologico Autonomo de Mexico, Mexico City (Mexico)
1997-07-01
Many large cities in the world have serious ground level ozone problems, largely the product of vehicular emissions and thus the argued unsustainability of current urban growth patterns is frequently blamed on unrestricted private vehicle use. This article reviews Mexico City`s experience with vehicle use restrictions as an emissions control program and develops the conditions for optimal quantitative restrictions on vehicle use and for complementary abatement technologies. The stochastic nature of air pollution outcomes is modelled explicitly in both the static and dynamic formulations of the control problem, in which for the first time in the literature the use of tradeable vehicle use permits is proposed as a cost-effective complement to technological abatement for mobile emissions control. This control regime gives the authorities a broader and more flexible set of instruments with which to deal more effectively with vehicle emissions, and with seasonal and stochastic variation of air quality outcomes. The market in tradeable vehicle use permits would be very competitive with low transactions costs. This control policy would have very favorable impacts on air quality, vehicle congestion and on urban form and development. Given the general political resistance to environmental taxes, this program could constitute a workable and politically palatable set of policies for controlling greenhouse gas emissions from the transport sector. 7 figs., 1 appendix, 23 refs.
International Nuclear Information System (INIS)
Goddard, H.C.
1997-01-01
Many large cities in the world have serious ground level ozone problems, largely the product of vehicular emissions and thus the argued unsustainability of current urban growth patterns is frequently blamed on unrestricted private vehicle use. This article reviews Mexico City's experience with vehicle use restrictions as an emissions control program and develops the conditions for optimal quantitative restrictions on vehicle use and for complementary abatement technologies. The stochastic nature of air pollution outcomes is modelled explicitly in both the static and dynamic formulations of the control problem, in which for the first time in the literature the use of tradeable vehicle use permits is proposed as a cost-effective complement to technological abatement for mobile emissions control. This control regime gives the authorities a broader and more flexible set of instruments with which to deal more effectively with vehicle emissions, and with seasonal and stochastic variation of air quality outcomes. The market in tradeable vehicle use permits would be very competitive with low transactions costs. This control policy would have very favorable impacts on air quality, vehicle congestion and on urban form and development. Given the general political resistance to environmental taxes, this program could constitute a workable and politically palatable set of policies for controlling greenhouse gas emissions from the transport sector. 7 figs., 1 appendix, 23 refs
Directory of Open Access Journals (Sweden)
Woonki Na
2017-03-01
Full Text Available This paper presents an improved maximum power point tracking (MPPT algorithm using a fuzzy logic controller (FLC in order to extract potential maximum power from photovoltaic cells. The objectives of the proposed algorithm are to improve the tracking speed, and to simultaneously solve the inherent drawbacks such as slow tracking in the conventional perturb and observe (P and O algorithm. The performances of the conventional P and O algorithm and the proposed algorithm are compared by using MATLAB/Simulink in terms of the tracking speed and steady-state oscillations. Additionally, both algorithms were experimentally validated through a digital signal processor (DSP-based controlled-boost DC-DC converter. The experimental results show that the proposed algorithm performs with a shorter tracking time, smaller output power oscillation, and higher efficiency, compared with the conventional P and O algorithm.
Implementation of Real-Time Feedback Flow Control Algorithms on a Canonical Testbed
Tian, Ye; Song, Qi; Cattafesta, Louis
2005-01-01
This report summarizes the activities on "Implementation of Real-Time Feedback Flow Control Algorithms on a Canonical Testbed." The work summarized consists primarily of two parts. The first part summarizes our previous work and the extensions to adaptive ID and control algorithms. The second part concentrates on the validation of adaptive algorithms by applying them to a vibration beam test bed. Extensions to flow control problems are discussed.
Fuzzy algorithm for an automatic reactor power control in a PWR
International Nuclear Information System (INIS)
Hah, Yung Joon; Song, In Ho; Yu, Sung Sik; Choi, Jung In; Lee, Byong Whi
1994-01-01
A fuzzy algorithm is presented for automatic reactor power control in a pressurized water reactor. Automatic power shape control is complicated by the use of control rods because it is highly coupled with reactivity compensation. Thus, manual shape controls are usually employed even for the limited capability for the load - follow operation including frequency control. In an attempt to achieve automatic power shape control without any design modification of the core, a fuzzy power control algorithm is proposed. For the fuzzy control, the rule base is formulated based on a multi - input multi - output system. The minimum operation rule and the center of area method are implemented for the development of the fuzzy algorithm. The fuzzy power control algorithm has been applied to the Yonggwang Nuclear Unit 3. The simulation results show that the fuzzy control can be adapted as a practical control strategy for automatic reactor power control of the pressurized water reactor during the load - follow operation
Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao
2016-01-01
In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…
Classon, Johan; Andersson, Viktor
2016-01-01
This thesis describes the implementation and evaluation of a genetic algorithm (GA) for procedurally generating levels with controllable difficulty for a motion-based 2D platform game. Manually creating content can be time-consuming, and it may be desirable to automate this process with an algorithm, using Procedural Content Generation (PCG). An algorithm was implemented and then refined with an iterative method by conducting user tests. The resulting algorithm is considered a success and sho...
Directory of Open Access Journals (Sweden)
Ashutosh K. AGARWAL
2011-10-01
Full Text Available Genetic algorithms are robust search techniques based on the principles of evolution. A genetic algorithm maintains a population of encoded solutions and guides the population towards the optimum solution. This important property of genetic algorithm is used in this paper to stabilize the Inverted pendulum system. This paper highlights the application and stability of inverted pendulum using PID controller with fuzzy logic genetic algorithm supervisor . There are a large number of well established search techniques in use within the information technology industry. We propose a method to control inverted pendulum steady state error and overshoot using genetic algorithm technique.
A Multilevel Congestion-Based Global Router
Directory of Open Access Journals (Sweden)
Logan Rakai
2009-01-01
Full Text Available Routing in nanometer nodes creates an elevated level of importance for low-congestion routing. At the same time, advances in mathematical programming have increased the power to solve complex problems, such as the routing problem. Hence, new routing methods need to be developed that can combine advanced mathematical programming and modeling techniques to provide low-congestion solutions. In this paper, a hierarchical mathematical programming-based global routing technique that considers congestion is proposed. The main contributions presented in this paper include (i implementation of congestion estimation based on actual routing solutions versus purely probabilistic techniques, (ii development of a congestion-based hierarchy for solving the global routing problem, and (iii generation of a robust framework for solving the routing problem using mathematical programming techniques. Experimental results illustrate that the proposed global router is capable of reducing congestion and overflow by as much as 36% compared to the state-of-the-art mathematical programming models.
Road traffic congestion a concise guide
Falcocchio, John C
2015-01-01
This book on road traffic congestion in cities and suburbs describes congestion problems and shows how they can be relieved. The first part (Chapters 1 - 3) shows how congestion reflects transportation technologies and settlement patterns. The second part (Chapters 4 - 13) describes the causes, characteristics, and consequences of congestion. The third part (Chapters 14 - 23) presents various relief strategies - including supply adaptation and demand mitigation - for nonrecurring and recurring congestion. The last part (Chapter 24) gives general guidelines for congestion relief and provides a general outlook for the future. The book will be useful for a wide audience - including students, practitioners and researchers in a variety of professional endeavors: traffic engineers, transportation planners, public transport specialists, city planners, public administrators, and private enterprises that depend on transportation for their activities.
Advanced carrier sensing to resolve local channel congestion
Schmidt, Robert K.; Brakemeier, Achim; Leinmüller, Tim; Kargl, Frank; Schäfer, Günther
Communication performance in VANETs under high channel load is significantly degraded due to packet collisions and messages drops, also referred to as local channel congestion. So far, research was focused on the control of transmit power and the limitation of the messages rate to mitigate the
Transvaginal ultrasound examination of women with and without pelvic venous congestion
International Nuclear Information System (INIS)
Halligan, Steve; Campbell, Deidre; Bartram, Clive I.; Rogers, Vera; El-Haddad, Cadria; Patel, Sujata; Beard, Richard W.
2000-01-01
AIM: To determine if transvaginal ultrasound, including power Doppler examination, can distinguish between women with and without pelvic congestion. MATERIALS AND METHODS: Thirty-six women with pelvic congestion were prospectively examined using transvaginal ultrasonography and standard uterine and ovarian measurements made. Additionally, planimetric measurements of each ovary were taken using an image analysis program to determine the cross-sectional area of ovarian stroma and follicles, if any. Power Doppler images of adnexal vessels were obtained and planimetric estimates of surface area calculated. A congestion score was assigned to each patient, based on vein number, diameter and morphology on grey-scale scanning. Identical measurements were obtained from 19 asymptomatic women and results compared. RESULTS: There was no significant difference between women with pelvic congestion and controls with respect to power Doppler or grey-scale images of adnexal vessels, or congestion score. However, women with pelvic congestion had significantly larger and multicystic ovaries when compared to controls. CONCLUSIONS: Transvaginal ultrasound measurements of adnexal vasculature, including power Doppler measurements, cannot reliably distinguish women with pelvic congestion from controls. However, ultrasound may remain useful for diagnosis of pelvic congestion, predominantly because it is able to visualize multi-cystic ovaries in these patients. Halligan, S. (2000).Clinical Radiology 55 , 954-958
Directory of Open Access Journals (Sweden)
Junqing Tang
Full Text Available Traffic congestion brings not only delay and inconvenience, but other associated national concerns, such as greenhouse gases, air pollutants, road safety issues and risks. Identification, measurement, tracking, and control of urban recurrent congestion are vital for building a livable and smart community. A considerable amount of works has made contributions to tackle the problem. Several methods, such as time-based approaches and level of service, can be effective for characterizing congestion on urban streets. However, studies with systemic perspectives have been minor in congestion quantification. Resilience, on the other hand, is an emerging concept that focuses on comprehensive systemic performance and characterizes the ability of a system to cope with disturbance and to recover its functionality. In this paper, we symbolized recurrent congestion as internal disturbance and proposed a modified metric inspired by the well-applied "R4" resilience-triangle framework. We constructed the metric with generic dimensions from both resilience engineering and transport science to quantify recurrent congestion based on spatial-temporal traffic patterns and made the comparison with other two approaches in freeway and signal-controlled arterial cases. Results showed that the metric can effectively capture congestion patterns in the study area and provides a quantitative benchmark for comparison. Also, it suggested not only a good comparative performance in measuring strength of proposed metric, but also its capability of considering the discharging process in congestion. The sensitivity tests showed that proposed metric possesses robustness against parameter perturbation in Robustness Range (RR, but the number of identified congestion patterns can be influenced by the existence of ϵ. In addition, the Elasticity Threshold (ET and the spatial dimension of cell-based platform differ the congestion results significantly on both the detected number and
Congestion management in liberalized market environment
International Nuclear Information System (INIS)
2006-01-01
This paper is based on the survey conducted by WG C5.4 on congestion management. It describes market conditions and institutional arrangements in the 18 countries participating in the survey, and internal and cross-border congestion management. The interaction with the electricity market is discussed, considering allocation of transmission capacity, market schedule, congestion management tools and payment for the costs incurred. The survey shows that there is a tendency towards the use of market-based methods. (author)
Newton algorithm for Hamiltonian characterization in quantum control
International Nuclear Information System (INIS)
Ndong, M; Sugny, D; Salomon, J
2014-01-01
We propose a Newton algorithm to characterize the Hamiltonian of a quantum system interacting with a given laser field. The algorithm is based on the assumption that the evolution operator of the system is perfectly known at a fixed time. The computational scheme uses the Crank–Nicholson approximation to explicitly determine the derivatives of the propagator with respect to the Hamiltonians of the system. In order to globalize this algorithm, we use a continuation method that improves its convergence properties. This technique is applied to a two-level quantum system and to a molecular one with a double-well potential. The numerical tests show that accurate estimates of the unknown parameters are obtained in some cases. We discuss the numerical limits of the algorithm in terms of the basin of convergence and the non-uniqueness of the solution. (paper)
Power control algorithms for mobile ad hoc networks
Directory of Open Access Journals (Sweden)
Nuraj L. Pradhan
2011-07-01
We will also focus on an adaptive distributed power management (DISPOW algorithm as an example of the multi-parameter optimization approach which manages the transmit power of nodes in a wireless ad hoc network to preserve network connectivity and cooperatively reduce interference. We will show that the algorithm in a distributed manner builds a unique stable network topology tailored to its surrounding node density and propagation environment over random topologies in a dynamic mobile wireless channel.
DEFF Research Database (Denmark)
Liu, Weijia; Wu, Qiuwei; Wen, Fushuan
2014-01-01
into balancing power might challenge the operation of electric distribution systems and cause congestions. This paper presents a distribution congestion price (DCP) based market mechanism to alleviate possible distribution system congestions. By employing the loca- tional marginal pricing (LMP) model...... is proposed. Finally, a practical Danish 60kV/10.5kV distribution system is employed as the test case to verify the proposed method for mitigating congestion....
Optimal Control of Complex Systems Based on Improved Dual Heuristic Dynamic Programming Algorithm
Directory of Open Access Journals (Sweden)
Hui Li
2017-01-01
Full Text Available When applied to solving the data modeling and optimal control problems of complex systems, the dual heuristic dynamic programming (DHP technique, which is based on the BP neural network algorithm (BP-DHP, has difficulty in prediction accuracy, slow convergence speed, poor stability, and so forth. In this paper, a dual DHP technique based on Extreme Learning Machine (ELM algorithm (ELM-DHP was proposed. Through constructing three kinds of network structures, the paper gives the detailed realization process of the DHP technique in the ELM. The controller designed upon the ELM-DHP algorithm controlled a molecular distillation system with complex features, such as multivariability, strong coupling, and nonlinearity. Finally, the effectiveness of the algorithm is verified by the simulation that compares DHP and HDP algorithms based on ELM and BP neural network. The algorithm can also be applied to solve the data modeling and optimal control problems of similar complex systems.
International Nuclear Information System (INIS)
Joung, JinWook; Chung, Lan; Smyth, Andrew W
2010-01-01
The active interaction control (AIC) system consisting of a primary structure, an auxiliary structure and an interaction element was proposed to protect the primary structure against earthquakes and winds. The objective of the AIC system in reducing the responses of the primary structure is fulfilled by activating or deactivating the switching between the engagement and the disengagement of the primary and auxiliary structures through the interaction element. The status of the interaction element is controlled by switching control algorithms. The previously developed switching control algorithms require an excessive amount of switching, which is inefficient. In this paper, the excessive amount of switching is restricted by imposing an appropriately designed switching boundary region, where switching is prohibited, on pre-designed engagement–disengagement conditions. Two different approaches are used in designing the newly proposed AID-off and AID-off 2 algorithms. The AID-off 2 algorithm is designed to affect deactivated switching regions explicitly, unlike the AID-off algorithm, which follows the same procedure of designing the engagement–disengagement conditions of the previously developed algorithms, by using the current status of the AIC system. Both algorithms are shown to be effective in reducing the amount of switching times triggered from the previously developed AID algorithm under an appropriately selected control sampling period for different earthquakes, but the AID-off 2 algorithm outperforms the AID-off algorithm in reducing the number of switching times
Distributed control software of high-performance control-loop algorithm
Blanc, D
1999-01-01
The majority of industrial cooling and ventilation plants require the control of complex processes. All these processes are highly important for the operation of the machines. The stability and reliability of these processes are leading factors identifying the quality of the service provided. The control system architecture and software structure, as well, are required to have high dynamical performance and robust behaviour. The intelligent systems based on PID or RST controllers are used for their high level of stability and accuracy. The design and tuning of these complex controllers require the dynamic model of the plant to be known (generally obtained by identification) and the desired performance of the various control loops to be specified for achieving good performances. The concept of having a distributed control algorithm software provides full automation facilities with well-adapted functionality and good performances, giving methodology, means and tools to master the dynamic process optimization an...
Directory of Open Access Journals (Sweden)
Saifullah Khalid
2016-09-01
Full Text Available Three conventional control constant instantaneous power control, sinusoidal current control, and synchronous reference frame techniques for extracting reference currents for shunt active power filters have been optimized using Fuzzy Logic control and Adaptive Tabu search Algorithm and their performances have been compared. Critical analysis of Comparison of the compensation ability of different control strategies based on THD and speed will be done, and suggestions will be given for the selection of technique to be used. The simulated results using MATLAB model are presented, and they will clearly prove the value of the proposed control method of aircraft shunt APF. The waveforms observed after the application of filter will be having the harmonics within the limits and the power quality will be improved.
DEFF Research Database (Denmark)
Huang, Shaojun; Wu, Qiuwei; Liu, Zhaoxi
2014-01-01
This paper reviews the existing congestion management methods for distribution networks with high penetration of DERs documented in the recent research literatures. The congestion management methods for distribution networks reviewed can be grouped into two categories – market methods and direct...... control methods. The market methods consist of dynamic tariff, distribution capacity market, shadow price and flexible service market. The direct control methods are comprised of network reconfiguration, reactive power control and active power control. Based on the review of the existing methods...
Stochastic Stability in Internet Router Congestion Games
Chung, Christine; Pyrga, Evangelia
Congestion control at bottleneck routers on the internet is a long standing problem. Many policies have been proposed for effective ways to drop packets from the queues of these routers so that network endpoints will be inclined to share router capacity fairly and minimize the overflow of packets trying to enter the queues. We study just how effective some of these queuing policies are when each network endpoint is a self-interested player with no information about the other players’ actions or preferences. By employing the adaptive learning model of evolutionary game theory, we study policies such as Droptail, RED, and the greedy-flow-punishing policy proposed by Gao et al. [10] to find the stochastically stable states: the states of the system that will be reached in the long run.
Modified Firefly Algorithm based controller design for integrating and unstable delay processes
Directory of Open Access Journals (Sweden)
A. Gupta
2016-03-01
Full Text Available In this paper, Modified Firefly Algorithm has been used for optimizing the controller parameters of Smith predictor structure. The proposed algorithm modifies the position formula of the standard Firefly Algorithm in order to achieve faster convergence rate. Performance criteria Integral Square Error (ISE is optimized using this optimization technique. Simulation results show high performance for Modified Firefly Algorithm as compared to conventional Firefly Algorithm in terms of convergence rate. Integrating and unstable delay processes are taken as examples to indicate the performance of the proposed method.
Genetic algorithms for adaptive real-time control in space systems
Vanderzijp, J.; Choudry, A.
1988-01-01
Genetic Algorithms that are used for learning as one way to control the combinational explosion associated with the generation of new rules are discussed. The Genetic Algorithm approach tends to work best when it can be applied to a domain independent knowledge representation. Applications to real time control in space systems are discussed.
A parallel row-based algorithm for standard cell placement with integrated error control
Sargent, Jeff S.; Banerjee, Prith
1989-01-01
A new row-based parallel algorithm for standard-cell placement targeted for execution on a hypercube multiprocessor is presented. Key features of this implementation include a dynamic simulated-annealing schedule, row-partitioning of the VLSI chip image, and two novel approaches to control error in parallel cell-placement algorithms: (1) Heuristic Cell-Coloring; (2) Adaptive Sequence Length Control.
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Dammann, Bernd; Madsen, Henrik
2014-01-01
This paper presents a decomposition algorithm for solving the optimal control problem (OCP) that arises in Mean-Variance Economic Model Predictive Control of stochastic linear systems. The algorithm applies the alternating direction method of multipliers to a reformulation of the OCP...
Real-Time Congestion Management in Distribution Networks by Flexible Demand Swap
DEFF Research Database (Denmark)
Huang, Shaojun; Wu, Qiuwei
2017-01-01
In addition to the day-ahead congestion management in distribution networks, the real-time congestion management is very important because many unforeseen events can occur at the real operation time, e.g. loss of generation of distributed energy resources (DERs) or inaccurate forecast of energy...... pumps (HPs) for real time congestion management. The swap method can maintain the power balance of the system and avoid the imbalance cost of activating the flexibility service. An algorithm for forming swaps through optimal power flow (OPF) and mixed integer linear programming (MILP) is proposed...... consumption or production. Flexibility service from demand will be a good option to solve the real-time congestions if the cost of activating the flexibility service is fully addressed. This paper proposes a new method, namely “swap”, to employ the flexibility service from electric vehicles (EVs) and heat...
Buteau, Stephane; Goldberg, Mark S; Burnett, Richard T; Gasparrini, Antonio; Valois, Marie-France; Brophy, James M; Crouse, Dan L; Hatzopoulou, Marianne
2018-04-01
Persons with congestive heart failure may be at higher risk of the acute effects related to daily fluctuations in ambient air pollution. To meet some of the limitations of previous studies using grouped-analysis, we developed a cohort study of persons with congestive heart failure to estimate whether daily non-accidental mortality were associated with spatially-resolved, daily exposures to ambient nitrogen dioxide (NO 2 ) and ozone (O 3 ), and whether these associations were modified according to a series of indicators potentially reflecting complications or worsening of health. We constructed the cohort from the linkage of administrative health databases. Daily exposure was assigned from different methods we developed previously to predict spatially-resolved, time-dependent concentrations of ambient NO 2 (all year) and O 3 (warm season) at participants' residences. We performed two distinct types of analyses: a case-crossover that contrasts the same person at different times, and a nested case-control that contrasts different persons at similar times. We modelled the effects of air pollution and weather (case-crossover only) on mortality using distributed lag nonlinear models over lags 0 to 3 days. We developed from administrative health data a series of indicators that may reflect the underlying construct of "declining health", and used interactions between these indicators and the cross-basis function for air pollutant to assess potential effect modification. The magnitude of the cumulative as well as the lag-specific estimates of association differed in many instances according to the metric of exposure. Using the back-extrapolation method, which is our preferred exposure model, we found for the case-crossover design a cumulative mean percentage changes (MPC) in daily mortality per interquartile increment in NO 2 (8.8 ppb) of 3.0% (95% CI: -0.9, 6.9%) and for O 3 (16.5 ppb) 3.5% (95% CI: -4.5, 12.1). For O 3 there was strong confounding by weather
Implementation of Genetic Algorithm in Control Structure of Induction Motor A.C. Drive
Directory of Open Access Journals (Sweden)
BRANDSTETTER, P.
2014-11-01
Full Text Available Modern concepts of control systems with digital signal processors allow the implementation of time-consuming control algorithms in real-time, for example soft computing methods. The paper deals with the design and technical implementation of a genetic algorithm for setting proportional and integral gain of the speed controller of the A.C. drive with the vector-controlled induction motor. Important simulations and experimental measurements have been realized that confirm the correctness of the proposed speed controller tuned by the genetic algorithm and the quality speed response of the A.C. drive with changing parameters and disturbance variables, such as changes in load torque.
PSO-Based Algorithm Applied to Quadcopter Micro Air Vehicle Controller Design
Directory of Open Access Journals (Sweden)
Huu-Khoa Tran
2016-09-01
Full Text Available Due to the rapid development of science and technology in recent times, many effective controllers are designed and applied successfully to complicated systems. The significant task of controller design is to determine optimized control gains in a short period of time. With this purpose in mind, a combination of the particle swarm optimization (PSO-based algorithm and the evolutionary programming (EP algorithm is introduced in this article. The benefit of this integration algorithm is the creation of new best-parameters for control design schemes. The proposed controller designs are then demonstrated to have the best performance for nonlinear micro air vehicle models.
A guidance and control algorithm for scent tracking micro-robotic vehicle swarms
International Nuclear Information System (INIS)
Dohner, J.L.
1998-03-01
Cooperative micro-robotic scent tracking vehicles are designed to collectively sniff out locations of high scent concentrations in unknown, geometrically complex environments. These vehicles are programmed with guidance and control algorithms that allow inter cooperation among vehicles. In this paper a cooperative guidance and control algorithm for scent tracking micro-robotic vehicles is presented. This algorithm is comprised of a sensory compensation sub-algorithm using point source cancellation, a guidance sub-algorithm using gradient descent tracking, and a control sub-algorithm using proportional feedback. The concepts of social rank and point source cancellation are new concepts introduced within. Simulation results for cooperative vehicles swarms are given. Limitations are discussed
A guidance and control algorithm for scent tracking micro-robotic vehicle swarms
Energy Technology Data Exchange (ETDEWEB)
Dohner, J.L. [Sandia National Labs., Albuquerque, NM (United States). Structural Dynamics Dept.
1998-03-01
Cooperative micro-robotic scent tracking vehicles are designed to collectively sniff out locations of high scent concentrations in unknown, geometrically complex environments. These vehicles are programmed with guidance and control algorithms that allow inter cooperation among vehicles. In this paper a cooperative guidance and control algorithm for scent tracking micro-robotic vehicles is presented. This algorithm is comprised of a sensory compensation sub-algorithm using point source cancellation, a guidance sub-algorithm using gradient descent tracking, and a control sub-algorithm using proportional feedback. The concepts of social rank and point source cancellation are new concepts introduced within. Simulation results for cooperative vehicles swarms are given. Limitations are discussed.
Synthesis of sequential control algorithms for pneumatic drives controlled by monostable valves
Directory of Open Access Journals (Sweden)
Ł. Dworzak
2009-07-01
Full Text Available Application of the Grafpol method [1] for synthesising sequential control algorithms for pneumatic drives controlled by monostable valves is presented. The developed principles simplify the MTS method of programming production processes in the scope of the memory realisation [2]. Thanks to this, time for synthesising the schematic equation can be significantly reduced in comparison to the network transformation method [3]. The designed schematic equation makes a ground for writing an application program of a PLC using any language defined in IEC 61131-3.
International Nuclear Information System (INIS)
Pyragas, V.; Pyragas, K.
2011-01-01
We propose a simple adaptive delayed feedback control algorithm for stabilization of unstable periodic orbits with unknown periods. The state dependent time delay is varied continuously towards the period of controlled orbit according to a gradient-descent method realized through three simple ordinary differential equations. We demonstrate the efficiency of the algorithm with the Roessler and Mackey-Glass chaotic systems. The stability of the controlled orbits is proven by computation of the Lyapunov exponents of linearized equations. -- Highlights: → A simple adaptive modification of the delayed feedback control algorithm is proposed. → It enables the control of unstable periodic orbits with unknown periods. → The delay time is varied continuously according to a gradient descend method. → The algorithm is embodied by three simple ordinary differential equations. → The validity of the algorithm is proven by computation of the Lyapunov exponents.
Bisoprolol for congestive heart failure
DEFF Research Database (Denmark)
Rosenberg, J.; Gustafsson, F.
2008-01-01
Background: beta-Blockers are a cornerstone in the treatment of systolic heart failure treatment, but not all beta-blockers are effective or in this setting. Objective: To define the role of bisoprolol, a highly selective beta(1)-antagonist in congestive heart failure due to systolic dysfunction....... Methods: Using the keywords 'bisoprolol' and 'heart failure' PubMed and BIOSIS databases were searched for information regarding pharmacology and relevant randomised clinical trials. Supplementary publications were acquired by scrutinising reference lists of relevant papers. Additional information...... was obtained from the FDA website. Conclusion: Bisoprolol is an effective and well-tolerated first-line beta-blocker for patients with systolic heart failure. The knowledge is primarily based on study patients with moderate-to-severe heart failure from the three CIBIS trials Udgivelsesdato: 2008/2...
Algorithms and Methods for High-Performance Model Predictive Control
DEFF Research Database (Denmark)
Frison, Gianluca
routines employed in the numerical tests. The main focus of this thesis is on linear MPC problems. In this thesis, both the algorithms and their implementation are equally important. About the implementation, a novel implementation strategy for the dense linear algebra routines in embedded optimization...... is proposed, aiming at improving the computational performance in case of small matrices. About the algorithms, they are built on top of the proposed linear algebra, and they are tailored to exploit the high-level structure of the MPC problems, with special care on reducing the computational complexity....
A parallel adaptive quantum genetic algorithm for the controllability of arbitrary networks.
Li, Yuhong; Gong, Guanghong; Li, Ni
2018-01-01
In this paper, we propose a novel algorithm-parallel adaptive quantum genetic algorithm-which can rapidly determine the minimum control nodes of arbitrary networks with both control nodes and state nodes. The corresponding network can be fully controlled with the obtained control scheme. We transformed the network controllability issue into a combinational optimization problem based on the Popov-Belevitch-Hautus rank condition. A set of canonical networks and a list of real-world networks were experimented. Comparison results demonstrated that the algorithm was more ideal to optimize the controllability of networks, especially those larger-size networks. We demonstrated subsequently that there were links between the optimal control nodes and some network statistical characteristics. The proposed algorithm provides an effective approach to improve the controllability optimization of large networks or even extra-large networks with hundreds of thousands nodes.
Tracing based congestion management and impact of TCPS in competitive power market using MINLP
International Nuclear Information System (INIS)
Kumar, A.; Chanana, S.
2006-01-01
Efficient, fair and secure operation of the competitive power markets are key factors in managing the challenges associated with congestion management. For the system operator, the selection of generators to reschedule their output for effective management of congestion is an important task. This study used a real power flow tracing based approach for selecting the most appropriate generators to reschedule the real power output based on real power flow contribution on a congested line. These generators can be effectively used to reschedule their generation for managing congestion. Using a mixed integer non-linear programming approach for reducing the transmission congestion cost in the system, the impact of Thyristor Controlled Phase Shifter (TCPS) was also investigated and their optimal placement was obtained. The study was carried out on a 39-bus New England system for pool and mix of pool with bilateral and multilateral transactions and their impact on congestion cost. The paper presented the detailed mathematical formulation and modeling process used. It was concluded that for some transactions, the reduction in congestion cost is not very significant. Therefore, system operators should avoid such transactions during congestion to increase market efficiency. 26 refs., 1 tab., 8 figs
Semi-flocking algorithm for motion control of mobile sensors in large-scale surveillance systems.
Semnani, Samaneh Hosseini; Basir, Otman A
2015-01-01
The ability of sensors to self-organize is an important asset in surveillance sensor networks. Self-organize implies self-control at the sensor level and coordination at the network level. Biologically inspired approaches have recently gained significant attention as a tool to address the issue of sensor control and coordination in sensor networks. These approaches are exemplified by the two well-known algorithms, namely, the Flocking algorithm and the Anti-Flocking algorithm. Generally speaking, although these two biologically inspired algorithms have demonstrated promising performance, they expose deficiencies when it comes to their ability to maintain simultaneous robust dynamic area coverage and target coverage. These two coverage performance objectives are inherently conflicting. This paper presents Semi-Flocking, a biologically inspired algorithm that benefits from key characteristics of both the Flocking and Anti-Flocking algorithms. The Semi-Flocking algorithm approaches the problem by assigning a small flock of sensors to each target, while at the same time leaving some sensors free to explore the environment. This allows the algorithm to strike balance between robust area coverage and target coverage. Such balance is facilitated via flock-sensor coordination. The performance of the proposed Semi-Flocking algorithm is examined and compared with other two flocking-based algorithms once using randomly moving targets and once using a standard walking pedestrian dataset. The results of both experiments show that the Semi-Flocking algorithm outperforms both the Flocking algorithm and the Anti-Flocking algorithm with respect to the area of coverage and the target coverage objectives. Furthermore, the results show that the proposed algorithm demonstrates shorter target detection time and fewer undetected targets than the other two flocking-based algorithms.
Route Optimization for Offloading Congested Meter Fixes
Xue, Min; Zelinski, Shannon
2016-01-01
The Optimized Route Capability (ORC) concept proposed by the FAA facilitates traffic managers to identify and resolve arrival flight delays caused by bottlenecks formed at arrival meter fixes when there exists imbalance between arrival fixes and runways. ORC makes use of the prediction capability of existing automation tools, monitors the traffic delays based on these predictions, and searches the best reroutes upstream of the meter fixes based on the predictions and estimated arrival schedules when delays are over a predefined threshold. Initial implementation and evaluation of the ORC concept considered only reroutes available at the time arrival congestion was first predicted. This work extends previous work by introducing an additional dimension in reroute options such that ORC can find the best time to reroute and overcome the 'firstcome- first-reroute' phenomenon. To deal with the enlarged reroute solution space, a genetic algorithm was developed to solve this problem. Experiments were conducted using the same traffic scenario used in previous work, when an arrival rush was created for one of the four arrival meter fixes at George Bush Intercontinental Houston Airport. Results showed the new approach further improved delay savings. The suggested route changes from the new approach were on average 30 minutes later than those using other approaches, and fewer numbers of reroutes were required. Fewer numbers of reroutes reduce operational complexity and later reroutes help decision makers deal with uncertain situations.
International Nuclear Information System (INIS)
Xu Xiangguo; Pan Yan; Deng Shiming; Xia Liang; Chan Mingyin
2013-01-01
The use of a multi-evaporator air conditioning (MEAC) system is advantageous in terms of installation convenience, high design flexibility, being easy to maintain and commission, better indoor thermal comfort control and higher energy efficiency. While MEAC units worth billions of dollars are sold worldwide, the detailed accounts on compressor capacity control and refrigeration flow distribution amongst evaporators remain unavailable in public domain, mainly due to commercial confidentiality. Limited control algorithms for MEAC systems have been developed based on system simulation, and no experimental-based capacity controller developments and their controllability tests may be identified in open literature. In the study reported in this paper, a novel capacity control algorithm, which imitated On–Off control of a single evaporator air conditioning (A/C) system in each indoor unit of a MEAC system by using variable speed compressor and electronic expansion valves (EEVs), was developed. Controllability tests under various settings for experimentally validating the novel capacity control algorithm were carried out and the control algorithm was further improved based on the experimental results. - Highlights: ► A capacity control algorithm for a multi-evaporator air conditioning system was developed. ► Experimental controllability tests under various settings were carried out. ► The control algorithm was further improved based on the experimental results.
Kuzishchin, V. F.; Merzlikina, E. I.; Van Va, Hoang
2017-11-01
The problem of PID and PI-algorithms tuning by means of the approximation by the least square method of the frequency response of a linear algorithm to the sub-optimal algorithm is considered. The advantage of the method is that the parameter values are obtained through one cycle of calculation. Recommendations how to choose the parameters of the least square method taking into consideration the plant dynamics are given. The parameters mentioned are the time constant of the filter, the approximation frequency range and the correction coefficient for the time delay parameter. The problem is considered for integrating plants for some practical cases (the level control system in a boiler drum). The transfer function of the suboptimal algorithm is determined relating to the disturbance that acts in the point of the control impact input, it is typical for thermal plants. In the recommendations it is taken into consideration that the overregulation for the transient process when the setpoint is changed is also limited. In order to compare the results the systems under consideration are also calculated by the classical method with the limited frequency oscillation index. The results given in the paper can be used by specialists dealing with tuning systems with the integrating plants.
Congestion management through topological corrections: A case study of Central Western Europe
International Nuclear Information System (INIS)
Han, Jinil; Papavasiliou, Anthony
2015-01-01
The integration of an increasing amount of renewable generation within Europe is posing operational challenges that require various balancing actions. System operators therefore need to rely increasingly on the active control of the transmission network. Transmission topology control is a fast and economical option to add flexibility to the transmission system. We model the current methodology for controlling congestion in the Central Western European (CWE) market and quantify the benefits of topology control. We also compare the results with a nodal pricing model. Our computational results suggest that topology control can significantly reduce congestion management costs under the current market coupling regime whereas the benefits of topology control are limited under nodal pricing. Topology control emerges as an attractive and implementable means of managing congestion as it provides a significant percentage of the cost savings that would be achieved by overhauling the existing European market design and shifting to a nodal pricing regime. - Highlights: • We present the congestion management model in the CWE region. • The benefits of topology control in the CWE region are quantified. • Topology control significantly reduce congestion under the current market coupling. • The benefits of topology control are limited under the nodal pricing regime. • Network topology control is a promising option for mitigating congestion in Europe.
A novel adaptive joint power control algorithm with channel estimation in a CDMA cellular system
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Joint power control has advantages of multi-user detection and power control; and it can combat the multi-access interference and the near-far problem. A novel adaptive joint power control algorithm with channel estimation in a CDMA cellular system was designed. Simulation results show that the algorithm can control the power not only quickly but also precisely with a time change. The method is useful for increasing system capacity.
Control of baker’s yeast fermentation : PID and fuzzy algorithms
Machado, Carlos; Gomes, Pedro; Soares, Rui; Pereira, Silvia; Soares, Filomena
2001-01-01
A MATLAB/SIMULINK-based simulator was employed for studies concerning the control of baker’s yeast fed-batch fermentation. Four control algorithms were implemented and compared: the classical PID control, two discrete versions- modified velocity and position algorithms, and a fuzzy law. The simulation package was seen to be an efficient tool for the simulation and tests of control strategies of the non-linear process.
Fouladi, Ehsan; Mojallali, Hamed
2018-01-01
In this paper, an adaptive backstepping controller has been tuned to synchronise two chaotic Colpitts oscillators in a master-slave configuration. The parameters of the controller are determined using shark smell optimisation (SSO) algorithm. Numerical results are presented and compared with those of particle swarm optimisation (PSO) algorithm. Simulation results show better performance in terms of accuracy and convergence for the proposed optimised method compared to PSO optimised controller or any non-optimised backstepping controller.
Reinforcement Learning for Online Control of Evolutionary Algorithms
Eiben, A.; Horvath, Mark; Kowalczyk, Wojtek; Schut, Martijn
2007-01-01
The research reported in this paper is concerned with assessing the usefulness of reinforcment learning (RL) for on-line calibration of parameters in evolutionary algorithms (EA). We are running an RL procedure and the EA simultaneously and the RL is changing the EA parameters on-the-fly. We
Control algorithm for multiscale flow simulations of water
DEFF Research Database (Denmark)
Kotsalis, E. M.; Walther, Jens Honore; Kaxiras, E.
2009-01-01
We present a multiscale algorithm to couple atomistic water models with continuum incompressible flow simulations via a Schwarz domain decomposition approach. The coupling introduces an inhomogeneity in the description of the atomistic domain and prevents the use of periodic boundary conditions...
Son, Sanghyun; Baek, Yunju
2015-08-18
As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.
Directory of Open Access Journals (Sweden)
Sanghyun Son
2015-08-01
Full Text Available As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.
Hasbullah Mohd Isa, Wan; Taha, Zahari; Mohd Khairuddin, Ismail; Majeed, Anwar P. P. Abdul; Fikri Muhammad, Khairul; Abdo Hashem, Mohammed; Mahmud, Jamaluddin; Mohamed, Zulkifli
2016-02-01
This paper presents the modelling and control of a two degree of freedom upper extremity exoskeleton by means of an intelligent active force control (AFC) mechanism. The Newton-Euler formulation was used in deriving the dynamic modelling of both the anthropometry based human upper extremity as well as the exoskeleton that consists of the upper arm and the forearm. A proportional-derivative (PD) architecture is employed in this study to investigate its efficacy performing joint-space control objectives. An intelligent AFC algorithm is also incorporated into the PD to investigate the effectiveness of this hybrid system in compensating disturbances. The Mamdani Fuzzy based rule is employed to approximate the estimated inertial properties of the system to ensure the AFC loop responds efficiently. It is found that the IAFC-PD performed well against the disturbances introduced into the system as compared to the conventional PD control architecture in performing the desired trajectory tracking.
CAS algorithm-based optimum design of PID controller in AVR system
International Nuclear Information System (INIS)
Zhu Hui; Li Lixiang; Zhao Ying; Guo Yu; Yang Yixian
2009-01-01
This paper presents a novel design method for determining the optimal PID controller parameters of an automatic voltage regulator (AVR) system using the chaotic ant swarm (CAS) algorithm. In the tuning process of parameters, the CAS algorithm is iterated to give the optimal parameters of the PID controller based on the fitness theory, where the position vector of each ant in the CAS algorithm corresponds to the parameter vector of the PID controller. The proposed CAS-PID controllers can ensure better control system performance with respect to the reference input in comparison with GA-PID controllers. Numerical simulations are provided to verify the effectiveness and feasibility of PID controller based on CAS algorithm.
Active Noise Control Using Modified FsLMS and Hybrid PSOFF Algorithm
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Ranjan Walia
2018-04-01
Full Text Available Active noise control is an efficient technique for noise cancellation of the system, which has been defined in this paper with the aid of Modified Filtered-s Least Mean Square (MFsLMS algorithm. The Hybrid Particle Swarm Optimization and Firefly (HPSOFF algorithm are used to identify the stability factor of the MFsLMS algorithm. The computational difficulty of the modified algorithm is reduced when compared with the original Filtered-s Least Mean Square (FsLMS algorithm. The noise sources are removed from the signal and it is compared with the existing FsLMS algorithm. The performance of the system is established with the normalized mean square error for two different types of noises. The proposed method has also been compared with the existing algorithms for the same purposes.
Flow control and routing techniques for integrated voice and data networks
Ibe, O. C.
1981-10-01
We consider a model of integrated voice and data networks. In this model the network flow problem is formulated as a convex optimization problem. The objective function comprises two types of cost functions: the congestion cost functions, which limit the average input traffic to values compatible with the network conditions; and the rate limitation cost functions, which ensure that all conversations are fairly treated. A joint flow control and routing algorithm is constructed which determines the routes for each conversation, and effects flow control by setting voice packet lengths and data input rates in a manner that achieves optimal tradeoff between each user's satisfaction and the cost of network congestion. An additional congestion control protocol is specified which could be used in conjunction with the algorithm to make the latter respond more dynamically to network congestion.
Chest ultrasound and hidden lung congestion in peritoneal dialysis patients.
Panuccio, Vincenzo; Enia, Giuseppe; Tripepi, Rocco; Torino, Claudia; Garozzo, Maurizio; Battaglia, Giovanni Giorgio; Marcantoni, Carmelita; Infantone, Lorena; Giordano, Guido; De Giorgi, Maria Loreta; Lupia, Mario; Bruzzese, Vincenzo; Zoccali, Carmine
2012-09-01
Chest ultrasound (US) is a non-invasive well-validated technique for estimating extravascular lung water (LW) in patients with heart diseases and in end-stage renal disease. We systematically applied this technique to the whole peritoneal dialysis (PD) population of five dialysis units. We studied the cross-sectional association between LW, echocardiographic parameters, clinical [pedal oedema, New York Heart Association (NYHA) class] and bioelectrical impedance analysis (BIA) markers of volume status in 88 PD patients. Moderate to severe lung congestion was evident in 41 (46%) patients. Ejection fraction was the echocardiographic parameter with the strongest independent association with LW (r = -0.40 P = 0.002). Oedema did not associate with LW on univariate and multivariate analysis. NYHA class was slightly associated with LW (r = 0.21 P = 0.05). Among patients with severe lung congestion, only 27% had pedal oedema and the majority (57%) had no dyspnoea (NYHA Class I). Similarly, the prevalence of patients with BIA, evidence of volume excess was small (11%) and not significantly different (P = 0.79) from that observed in patients with mild or no congestion (9%). In PD patients, LW by chest US reveals moderate to severe lung congestion in a significant proportion of asymptomatic patients. Intervention studies are necessary to prove the usefulness of chest US for optimizing the control of fluid excess in PD patients.
Controller Parameter Optimization for Nonlinear Systems Using Enhanced Bacteria Foraging Algorithm
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V. Rajinikanth
2012-01-01
Full Text Available An enhanced bacteria foraging optimization (EBFO algorithm-based Proportional + integral + derivative (PID controller tuning is proposed for a class of nonlinear process models. The EBFO algorithm is a modified form of standard BFO algorithm. A multiobjective performance index is considered to guide the EBFO algorithm for discovering the best possible value of controller parameters. The efficiency of the proposed scheme has been validated through a comparative study with classical BFO, adaptive BFO, PSO, and GA based controller tuning methods proposed in the literature. The proposed algorithm is tested in real time on a nonlinear spherical tank system. The real-time results show that, EBFO tuned PID controller gives a smooth response for setpoint tracking performance.
Increased walking variability in elderly persons with congestive heart failure
Hausdorff, J. M.; Forman, D. E.; Ladin, Z.; Goldberger, A. L.; Rigney, D. R.; Wei, J. Y.
1994-01-01
OBJECTIVES: To determine the effects of congestive heart failure on a person's ability to walk at a steady pace while ambulating at a self-determined rate. SETTING: Beth Israel Hospital, Boston, a primary and tertiary teaching hospital, and a social activity center for elderly adults living in the community. PARTICIPANTS: Eleven elderly subjects (aged 70-93 years) with well compensated congestive heart failure (NY Heart Association class I or II), seven elderly subjects (aged 70-79 years) without congestive heart failure, and 10 healthy young adult subjects (aged 20-30 years). MEASUREMENTS: Subjects walked for 8 minutes on level ground at their own selected walking rate. Footswitches were used to measure the time between steps. Step rate (steps/minute) and step rate variability were calculated for the entire walking period, for 30 seconds during the first minute of the walk, for 30 seconds during the last minute of the walk, and for the 30-second period when each subject's step rate variability was minimal. Group means and 5% and 95% confidence intervals were computed. MAIN RESULTS: All measures of walking variability were significantly increased in the elderly subjects with congestive heart failure, intermediate in the elderly controls, and lowest in the young subjects. There was no overlap between the three groups using the minimal 30-second variability (elderly CHF vs elderly controls: P young: P < 0.001), and no overlap between elderly subjects with and without congestive heart failure when using the overall variability. For all four measures, there was no overlap in any of the confidence intervals, and all group means were significantly different (P < 0.05).
Genetic Algorithm Tuning of PID Controller in Smith Predictor for Glucose Concentration Control
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Tsonyo Slavov
2011-07-01
Full Text Available This paper focuses on design of a glucose concentration control system based on nonlinear model plant of E. coli MC4110 fed-batch cultivation process. Due to significant time delay in real time glucose concentration measurement, a correction is proposed in glucose concentration measurement and a Smith predictor (SP control structure based on universal PID controller is designed. To reduce the influence of model error in SP structure the estimate of measured glucose concentration is used. For the aim an extended Kalman filter (EKF is designed. To achieve good closed-loop system performance genetic algorithm (GA based optimal controller tuning procedure is applied. A standard binary encoding GA is applied. The GA parameters and operators are specified for the considered here problem. As a result the optimal PID controller settings are obtained. The simulation experiments of the control systems based on SP with EKF and without EKF are performed. The results show that the control system based on SP with EKF has a better performance than the one without EKF. For a short time the controller sets the control variable and maintains it at the desired set point during the cultivation process. As a result, a high biomass concentration of 48.3 g·l-1 is obtained at the end of the process.
Development of real-time plasma analysis and control algorithms for the TCV tokamak using SIMULINK
International Nuclear Information System (INIS)
Felici, F.; Le, H.B.; Paley, J.I.; Duval, B.P.; Coda, S.; Moret, J.-M.; Bortolon, A.; Federspiel, L.; Goodman, T.P.; Hommen, G.; Karpushov, A.; Piras, F.; Pitzschke, A.; Romero, J.; Sevillano, G.; Sauter, O.; Vijvers, W.
2014-01-01
Highlights: • A new digital control system for the TCV tokamak has been commissioned. • The system is entirely programmable by SIMULINK, allowing rapid algorithm development. • Different control system nodes can run different algorithms at varying sampling times. • The previous control system functions have been emulated and improved. • New capabilities include MHD control, profile control, equilibrium reconstruction. - Abstract: One of the key features of the new digital plasma control system installed on the TCV tokamak is the possibility to rapidly design, test and deploy real-time algorithms. With this flexibility the new control system has been used for a large number of new experiments which exploit TCV's powerful actuators consisting of 16 individually controllable poloidal field coils and 7 real-time steerable electron cyclotron (EC) launchers. The system has been used for various applications, ranging from event-based real-time MHD control to real-time current diffusion simulations. These advances have propelled real-time control to one of the cornerstones of the TCV experimental program. Use of the SIMULINK graphical programming language to directly program the control system has greatly facilitated algorithm development and allowed a multitude of different algorithms to be deployed in a short time. This paper will give an overview of the developed algorithms and their application in physics experiments
Battiste, Vernol; Lawton, George; Lachter, Joel; Brandt, Summer; Koteskey, Robert; Dao, Arik-Quang; Kraut, Josh; Ligda, Sarah; Johnson, Walter W.
2012-01-01
Managing the interval between arrival aircraft is a major part of the en route and TRACON controller s job. In an effort to reduce controller workload and low altitude vectoring, algorithms have been developed to allow pilots to take responsibility for, achieve and maintain proper spacing. Additionally, algorithms have been developed to create dynamic weather-free arrival routes in the presence of convective weather. In a recent study we examined an algorithm to handle dynamic re-routing in the presence of convective weather and two distinct spacing algorithms. The spacing algorithms originated from different core algorithms; both were enhanced with trajectory intent data for the study. These two algorithms were used simultaneously in a human-in-the-loop (HITL) simulation where pilots performed weather-impacted arrival operations into Louisville International Airport while also performing interval management (IM) on some trials. The controllers retained responsibility for separation and for managing the en route airspace and some trials managing IM. The goal was a stress test of dynamic arrival algorithms with ground and airborne spacing concepts. The flight deck spacing algorithms or controller managed spacing not only had to be robust to the dynamic nature of aircraft re-routing around weather but also had to be compatible with two alternative algorithms for achieving the spacing goal. Flight deck interval management spacing in this simulation provided a clear reduction in controller workload relative to when controllers were responsible for spacing the aircraft. At the same time, spacing was much less variable with the flight deck automated spacing. Even though the approaches taken by the two spacing algorithms to achieve the interval management goals were slightly different they seem to be simpatico in achieving the interval management goal of 130 sec by the TRACON boundary.
Traffic Congestion Detection System through Connected Vehicles and Big Data
Directory of Open Access Journals (Sweden)
Néstor Cárdenas-Benítez
2016-04-01
Full Text Available This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO2 and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur.
Data-Driven Participation: Algorithms, Cities, Citizens, and Corporate Control
Directory of Open Access Journals (Sweden)
Matthew Tenney
2016-07-01
Full Text Available In this paper, we critically explore the interplay of algorithms and civic participation in visions of a city governed by equation, sensor and tweet. We begin by discussing the rhetoric surrounding techno-enabled paths to participatory democracy. This leads to us interrogating how the city is impacted by a discourse that promises to harness social/human capital through data science. We move to a praxis level and examine the motivations of local planners to adopt and increasingly automate forms of VGI as a form of citizen engagement. We ground theory and praxis with a report on the uneven impacts of algorithmic civic participation underway in the Canadian city of Toronto.
Fuzzy Sets-based Control Rules for Terminating Algorithms
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Jose L. VERDEGAY
2002-01-01
Full Text Available In this paper some problems arising in the interface between two different areas, Decision Support Systems and Fuzzy Sets and Systems, are considered. The Model-Base Management System of a Decision Support System which involves some fuzziness is considered, and in that context the questions on the management of the fuzziness in some optimisation models, and then of using fuzzy rules for terminating conventional algorithms are presented, discussed and analyzed. Finally, for the concrete case of the Travelling Salesman Problem, and as an illustration of determination, management and using the fuzzy rules, a new algorithm easy to implement in the Model-Base Management System of any oriented Decision Support System is shown.
An approach of traffic signal control based on NLRSQP algorithm
Zou, Yuan-Yang; Hu, Yu
2017-11-01
This paper presents a linear program model with linear complementarity constraints (LPLCC) to solve traffic signal optimization problem. The objective function of the model is to obtain the minimization of total queue length with weight factors at the end of each cycle. Then, a combination algorithm based on the nonlinear least regression and sequence quadratic program (NLRSQP) is proposed, by which the local optimal solution can be obtained. Furthermore, four numerical experiments are proposed to study how to set the initial solution of the algorithm that can get a better local optimal solution more quickly. In particular, the results of numerical experiments show that: The model is effective for different arrival rates and weight factors; and the lower bound of the initial solution is, the better optimal solution can be obtained.
Genetic algorithms for optimal design and control of adaptive structures
Ribeiro, R; Dias-Rodrigues, J; Vaz, M
2000-01-01
Future High Energy Physics experiments require the use of light and stable structures to support their most precise radiation detection elements. These large structures must be light, highly stable, stiff and radiation tolerant in an environment where external vibrations, high radiation levels, material aging, temperature and humidity gradients are not negligible. Unforeseen factors and the unknown result of the coupling of environmental conditions, together with external vibrations, may affect the position stability of the detectors and their support structures compromising their physics performance. Careful optimization of static and dynamic behavior must be an essential part of the engineering design. Genetic Algorithms ( GA) belong to the group of probabilistic algorithms, combining elements of direct and stochastic search. They are more robust than existing directed search methods with the advantage of maintaining a population of potential solutions. There is a class of optimization problems for which Ge...
An improved cooperative adaptive cruise control (CACC) algorithm considering invalid communication
Wang, Pangwei; Wang, Yunpeng; Yu, Guizhen; Tang, Tieqiao
2014-05-01
For the Cooperative Adaptive Cruise Control (CACC) Algorithm, existing research studies mainly focus on how inter-vehicle communication can be used to develop CACC controller, the influence of the communication delays and lags of the actuators to the string stability. However, whether the string stability can be guaranteed when inter-vehicle communication is invalid partially has hardly been considered. This paper presents an improved CACC algorithm based on the sliding mode control theory and analyses the range of CACC controller parameters to maintain string stability. A dynamic model of vehicle spacing deviation in a platoon is then established, and the string stability conditions under improved CACC are analyzed. Unlike the traditional CACC algorithms, the proposed algorithm can ensure the functionality of the CACC system even if inter-vehicle communication is partially invalid. Finally, this paper establishes a platoon of five vehicles to simulate the improved CACC algorithm in MATLAB/Simulink, and the simulation results demonstrate that the improved CACC algorithm can maintain the string stability of a CACC platoon through adjusting the controller parameters and enlarging the spacing to prevent accidents. With guaranteed string stability, the proposed CACC algorithm can prevent oscillation of vehicle spacing and reduce chain collision accidents under real-world circumstances. This research proposes an improved CACC algorithm, which can guarantee the string stability when inter-vehicle communication is invalid.
Development of traffic light control algorithm in smart municipal network
Kuzminykh, Ievgeniia
2016-01-01
This paper presents smart system that bypasses the normal functioning algorithm of traffic lights, triggers a green light when the lights are red or reset the timer of the traffic lights when they are about to turn red. Different pieces of hardware like microcontroller units, transceivers, resistors, diodes, LEDs, a digital compass and accelerometer will be coupled together and programed to create unified complex intelligent system.
Sanjay Kr. Singh; D. Boolchandani; S.G. Modani; Nitish Katal
2014-01-01
This study focuses on multi-objective optimization of the PID controllers for optimal speed control for an isolated steam turbine. In complex operations, optimal tuning plays an imperative role in maintaining the product quality and process safety. This study focuses on the comparison of the optimal PID tuning using Multi-objective Genetic Algorithm (NSGA-II) against normal genetic algorithm and Ziegler Nichols methods for the speed control of an isolated steam turbine. Isolated steam turbine...
New mode switching algorithm for the JPL 70-meter antenna servo controller
Nickerson, J. A.
1988-01-01
The design of control mode switching algorithms and logic for JPL's 70 m antenna servo controller are described. The old control mode switching logic was reviewed and perturbation problems were identified. Design approaches for mode switching are presented and the final design is described. Simulations used to compare old and new mode switching algorithms and logic show that the new mode switching techniques will significantly reduce perturbation problems.
Cole, Robert; Wear, Mary; Young, Millennia; Cobel, Christopher; Mason, Sara
2017-01-01
Congestion is commonly reported during spaceflight, and most crewmembers have reported using medications for congestion during International Space Station (ISS) missions. Although congestion has been attributed to fluid shifts during spaceflight, fluid status reaches equilibrium during the first week after launch while congestion continues to be reported throughout long duration missions. Congestion complaints have anecdotally been reported in relation to ISS CO2 levels; this evaluation was undertaken to determine whether or not an association exists. METHODS: Reported headaches, congestion symptoms, and CO2 levels were obtained for ISS expeditions 2-31, and time-weighted means and single-point maxima were determined for 24-hour (24hr) and 7-day (7d) periods prior to each weekly private medical conference. Multiple imputation addressed missing data, and logistic regression modeled the relationship between probability of reported event of congestion or headache and CO2 levels, adjusted for possible confounding covariates. The first seven days of spaceflight were not included to control for fluid shifts. Data were evaluated to determine the concentration of CO2 required to maintain the risk of congestion below 1% to allow for direct comparison with a previously published evaluation of CO2 concentrations and headache. RESULTS: This study confirmed a previously identified significant association between CO2 and headache and also found a significant association between CO2 and congestion. For each 1-mm Hg increase in CO2, the odds of a crew member reporting congestion doubled. The average 7-day CO2 would need to be maintained below 1.5 mmHg to keep the risk of congestion below 1%. The predicted probability curves of ISS headache and congestion curves appear parallel when plotted against ppCO2 levels with congestion occurring at approximately 1mmHg lower than a headache would be reported. DISCUSSION: While the cause of congestion is multifactorial, this study showed
Noise filtering algorithm for the MFTF-B computer based control system
International Nuclear Information System (INIS)
Minor, E.G.
1983-01-01
An algorithm to reduce the message traffic in the MFTF-B computer based control system is described. The algorithm filters analog inputs to the control system. Its purpose is to distinguish between changes in the inputs due to noise and changes due to significant variations in the quantity being monitored. Noise is rejected while significant changes are reported to the control system data base, thus keeping the data base updated with a minimum number of messages. The algorithm is memory efficient, requiring only four bytes of storage per analog channel, and computationally simple, requiring only subtraction and comparison. Quantitative analysis of the algorithm is presented for the case of additive Gaussian noise. It is shown that the algorithm is stable and tends toward the mean value of the monitored variable over a wide variety of additive noise distributions
van Ophem, S.; Berkhoff, Arthur P.
2016-01-01
For broadband active noise control applications with a rapidly changing primary path, it is desirable to find algorithms with a rapid convergence, a fast tracking performance, and a low computational cost. Recently, a promising algorithm has been presented, called the fast-array Kalman filter, which
Data-driven gradient algorithm for high-precision quantum control
Wu, Re-Bing; Chu, Bing; Owens, David H.; Rabitz, Herschel
2018-04-01
In the quest to achieve scalable quantum information processing technologies, gradient-based optimal control algorithms (e.g., grape) are broadly used for implementing high-precision quantum gates, but their performance is often hindered by deterministic or random errors in the system model and the control electronics. In this paper, we show that grape can be taught to be more effective by jointly learning from the design model and the experimental data obtained from process tomography. The resulting data-driven gradient optimization algorithm (d-grape) can in principle correct all deterministic gate errors, with a mild efficiency loss. The d-grape algorithm may become more powerful with broadband controls that involve a large number of control parameters, while other algorithms usually slow down due to the increased size of the search space. These advantages are demonstrated by simulating the implementation of a two-qubit controlled-not gate.
Congested Aggregation via Newtonian Interaction
Craig, Katy; Kim, Inwon; Yao, Yao
2018-01-01
We consider a congested aggregation model that describes the evolution of a density through the competing effects of nonlocal Newtonian attraction and a hard height constraint. This provides a counterpoint to existing literature on repulsive-attractive nonlocal interaction models, where the repulsive effects instead arise from an interaction kernel or the addition of diffusion. We formulate our model as the Wasserstein gradient flow of an interaction energy, with a penalization to enforce the constraint on the height of the density. From this perspective, the problem can be seen as a singular limit of the Keller-Segel equation with degenerate diffusion. Two key properties distinguish our problem from previous work on height constrained equations: nonconvexity of the interaction kernel (which places the model outside the scope of classical gradient flow theory) and nonlocal dependence of the velocity field on the density (which causes the problem to lack a comparison principle). To overcome these obstacles, we combine recent results on gradient flows of nonconvex energies with viscosity solution theory. We characterize the dynamics of patch solutions in terms of a Hele-Shaw type free boundary problem and, using this characterization, show that in two dimensions patch solutions converge to a characteristic function of a disk in the long-time limit, with an explicit rate on the decay of the energy. We believe that a key contribution of the present work is our blended approach, combining energy methods with viscosity solution theory.
A Hierarchical Algorithm for Integrated Scheduling and Control With Applications to Power Systems
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Dinesen, Peter Juhler; Jørgensen, John Bagterp
2016-01-01
The contribution of this paper is a hierarchical algorithm for integrated scheduling and control via model predictive control of hybrid systems. The controlled system is a linear system composed of continuous control, state, and output variables. Binary variables occur as scheduling decisions in ...
Fuzzy PID control algorithm based on PSO and application in BLDC motor
Lin, Sen; Wang, Guanglong
2017-06-01
A fuzzy PID control algorithm is studied based on improved particle swarm optimization (PSO) to perform Brushless DC (BLDC) motor control which has high accuracy, good anti-jamming capability and steady state accuracy compared with traditional PID control. The mathematical and simulation model is established for BLDC motor by simulink software, and the speed loop of the fuzzy PID controller is designed. The simulation results show that the fuzzy PID control algorithm based on PSO has higher stability, high control precision and faster dynamic response speed.
Cull, R. C.; Eltimsahy, A. H.
1983-01-01
The present investigation is concerned with the formulation of energy management strategies for stand-alone photovoltaic (PV) systems, taking into account a basic control algorithm for a possible predictive, (and adaptive) controller. The control system controls the flow of energy in the system according to the amount of energy available, and predicts the appropriate control set-points based on the energy (insolation) available by using an appropriate system model. Aspects of adaptation to the conditions of the system are also considered. Attention is given to a statistical analysis technique, the analysis inputs, the analysis procedure, and details regarding the basic control algorithm.
Telban, Robert J.
While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. To address this, new human-centered motion cueing algorithms were developed. A revised "optimal algorithm" uses time-invariant filters developed by optimal control, incorporating human vestibular system models. The "nonlinear algorithm" is a novel approach that is also formulated by optimal control, but can also be updated in real time. It incorporates a new integrated visual-vestibular perception model that includes both visual and vestibular sensation and the interaction between the stimuli. A time-varying control law requires the matrix Riccati equation to be solved in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. As a result of unsatisfactory sensation, an augmented turbulence cue was added to the vertical mode for both the optimal and nonlinear algorithms. The relative effectiveness of the algorithms, in simulating aircraft maneuvers, was assessed with an eleven-subject piloted performance test conducted on the NASA Langley Visual Motion Simulator (VMS). Two methods, the quasi-objective NASA Task Load Index (TLX), and power spectral density analysis of pilot control, were used to assess pilot workload. TLX analysis reveals, in most cases, less workload and variation among pilots with the nonlinear algorithm. Control input
Directory of Open Access Journals (Sweden)
Shu-wei Wang
2013-01-01
Full Text Available A congestion phenomenon in a transit station could lead to low transfer efficiency as well as a hidden danger. Effective management of congestion phenomenon shall help to reduce the efficiency decline and danger risk. However, due to the difficulty in acquiring microcosmic pedestrian density, existing researches lack quantitative indicators to reflect congestion degree. This paper aims to solve this problem. Firstly, platform, stair, transfer tunnel, auto fare collection (AFC machine, and security check machine were chosen as key traffic facilities through large amounts of field investigation. Key facilities could be used to reflect the passenger density of a whole station. Secondly, the pedestrian density change law of each key traffic facility was analyzed using pedestrian simulation, and the load degree calculating method of each facility was defined, respectively, afterwards. Taking pedestrian density as basic data and gray clustering evaluation as algorithm, an index called Transit Station Congestion Index (TSCI was constructed to reflect the congestion degree of transit stations. Finally, an evaluation demonstration was carried out with five typical transit transfer stations in Beijing, and the evaluation results show that TSCI can objectively reflect the congestion degree of transit stations.
Cabaret, S; Coppier, H; Rachid, A; Barillère, R; CERN. Geneva. IT Department
2007-01-01
The GCS (Gas Control System) project team at CERN uses a Model Driven Approach with a Framework - UNICOS (UNified Industrial COntrol System) - based on PLC (Programming Language Controller) and SCADA (Supervisory Control And Data Acquisition) technologies. The first' UNICOS versions were able to provide a PID (Proportional Integrative Derivative) controller whereas the Gas Systems required more advanced control strategies. The MultiController is a new UNICOS object which provides the following advanced control algorithms: Smith Predictor, PFC (Predictive Function Control), RST* and GPC (Global Predictive Control). Its design is based on a monolithic entity with a global structure definition which is able to capture the desired set of parameters of any specific control algorithm supported by the object. The SCADA system -- PVSS - supervises the MultiController operation. The PVSS interface provides users with supervision faceplate, in particular it links any MultiController with recipes: the GCS experts are ab...
Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm
Directory of Open Access Journals (Sweden)
Feifei Dong
2014-01-01
Full Text Available Considering that common subsynchronous resonance controllers cannot adapt to the characteristics of the time-varying and nonlinear behavior of a power system, the cosine migration model, the improved migration operator, and the mutative scale of chaos and Cauchy mutation strategy are introduced into an improved biogeography-based optimization (IBBO algorithm in order to design an optimal subsynchronous damping controller based on the mechanism of suppressing SSR by static var compensator (SVC. The effectiveness of the improved controller is verified by eigenvalue analysis and electromagnetic simulations. The simulation results of Jinjie plant indicate that the subsynchronous damping controller optimized by the IBBO algorithm can remarkably improve the damping of torsional modes and thus effectively depress SSR, and ensure the safety and stability of units and power grid operation. Moreover, the IBBO algorithm has the merits of a faster searching speed and higher searching accuracy in seeking the optimal control parameters over traditional algorithms, such as BBO algorithm, PSO algorithm, and GA algorithm.
Investigation of an automatic trim algorithm for restructurable aircraft control
Weiss, J.; Eterno, J.; Grunberg, D.; Looze, D.; Ostroff, A.
1986-01-01
This paper develops and solves an automatic trim problem for restructurable aircraft control. The trim solution is applied as a feed-forward control to reject measurable disturbances following control element failures. Disturbance rejection and command following performances are recovered through the automatic feedback control redesign procedure described by Looze et al. (1985). For this project the existence of a failure detection mechanism is assumed, and methods to cope with potential detection and identification inaccuracies are addressed.
Optimization and Control of Bilinear Systems Theory, Algorithms, and Applications
Pardalos, Panos M
2008-01-01
Covers developments in bilinear systems theory Focuses on the control of open physical processes functioning in a non-equilibrium mode Emphasis is on three primary disciplines: modern differential geometry, control of dynamical systems, and optimization theory Includes applications to the fields of quantum and molecular computing, control of physical processes, biophysics, superconducting magnetism, and physical information science
Different Control Algorithms for a Platoon of Autonomous Vehicles
Directory of Open Access Journals (Sweden)
Zoran Gacovski
2014-05-01
Full Text Available This paper presents a concept of platoon movement of autonomous vehicles (smart cars. These vehicles have Adaptive or Advanced cruise control (ACC system also called Intelligent cruise control (ICC or Adaptive Intelligent cruise control (AICC system. The vehicles are suitable to follow other vehicles on desired distance and to be organized in platoons. To perform a research on the control and stability of an AGV (Automated Guided Vehicles string, we have developed a car-following model. To do this, first a single vehicle is modeled and since all cars in the platoon have the same dynamics, the single vehicle model is copied ten times to form model of platoon (string with ten vehicles. To control this string, we have applied equal PID controllers to all vehicles, except the leading vehicle. These controllers try to keep the headway distance as constant as possible and the velocity error between subsequent vehicles - small. For control of vehicle with nonlinear dynamics combination of feedforward control and feedback control approach is used. Feedforward control is based on the inverse model of nominal dynamics of the vehicle, and feedback PID control is designed based on the linearized model of the vehicle. For simulation and analysis of vehicle and platoon of vehicles – we have developed Matlab/Simulink models. Simulation results, discussions and conclusions are given at the end of the paper.
SVC control enhancement applying self-learning fuzzy algorithm for islanded microgrid
Directory of Open Access Journals (Sweden)
Hossam Gabbar
2016-03-01
Full Text Available Maintaining voltage stability, within acceptable levels, for islanded Microgrids (MGs is a challenge due to limited exchange power between generation and loads. This paper proposes an algorithm to enhance the dynamic performance of islanded MGs in presence of load disturbance using Static VAR Compensator (SVC with Fuzzy Model Reference Learning Controller (FMRLC. The proposed algorithm compensates MG nonlinearity via fuzzy membership functions and inference mechanism imbedded in both controller and inverse model. Hence, MG keeps the desired performance as required at any operating condition. Furthermore, the self-learning capability of the proposed control algorithm compensates for grid parameter’s variation even with inadequate information about load dynamics. A reference model was designed to reject bus voltage disturbance with achievable performance by the proposed fuzzy controller. Three simulations scenarios have been presented to investigate effectiveness of proposed control algorithm in improving steady-state and transient performance of islanded MGs. The first scenario conducted without SVC, second conducted with SVC using PID controller and third conducted using FMRLC algorithm. A comparison for results shows ability of proposed control algorithm to enhance disturbance rejection due to learning process.
The research of automatic speed control algorithm based on Green CBTC
Lin, Ying; Xiong, Hui; Wang, Xiaoliang; Wu, Youyou; Zhang, Chuanqi
2017-06-01
Automatic speed control algorithm is one of the core technologies of train operation control system. It’s a typical multi-objective optimization control algorithm, which achieve the train speed control for timing, comfort, energy-saving and precise parking. At present, the train speed automatic control technology is widely used in metro and inter-city railways. It has been found that the automatic speed control technology can effectively reduce the driver’s intensity, and improve the operation quality. However, the current used algorithm is poor at energy-saving, even not as good as manual driving. In order to solve the problem of energy-saving, this paper proposes an automatic speed control algorithm based on Green CBTC system. Based on the Green CBTC system, the algorithm can adjust the operation status of the train to improve the efficient using rate of regenerative braking feedback energy while ensuring the timing, comfort and precise parking targets. Due to the reason, the energy-using of Green CBTC system is lower than traditional CBTC system. The simulation results show that the algorithm based on Green CBTC system can effectively reduce the energy-using due to the improvement of the using rate of regenerative braking feedback energy.
Model Predictive Control Algorithms for Pen and Pump Insulin Administration
DEFF Research Database (Denmark)
Boiroux, Dimitri
at mealtime, and the case where the insulin sensitivity increases during the night. This thesis consists of a summary report, glucose and insulin proles of the clinical studies and research papers submitted, peer-reviewed and/or published in the period September 2009 - September 2012....... of current closed-loop controllers. In this thesis, we present different control strategies based on Model Predictive Control (MPC) for an artificial pancreas. We use Nonlinear Model Predictive Control (NMPC) in order to determine the optimal insulin and blood glucose profiles. The optimal control problem...
Active Engine Mounting Control Algorithm Using Neural Network
Directory of Open Access Journals (Sweden)
Fadly Jashi Darsivan
2009-01-01
Full Text Available This paper proposes the application of neural network as a controller to isolate engine vibration in an active engine mounting system. It has been shown that the NARMA-L2 neurocontroller has the ability to reject disturbances from a plant. The disturbance is assumed to be both impulse and sinusoidal disturbances that are induced by the engine. The performance of the neural network controller is compared with conventional PD and PID controllers tuned using Ziegler-Nichols. From the result simulated the neural network controller has shown better ability to isolate the engine vibration than the conventional controllers.
Modeling truck traffic volume growth congestion.
2009-05-01
Modeling of the statewide transportation system is an important element in understanding issues and programming of funds to thwart potential congestion. As Alabama grows its manufacturing economy, the number of heavy vehicles traversing its highways ...
Understanding congested travel in urban areas
Çolak, Serdar; Lima, Antonio; González, Marta C.
2016-03-01
Rapid urbanization and increasing demand for transportation burdens urban road infrastructures. The interplay of number of vehicles and available road capacity on their routes determines the level of congestion. Although approaches to modify demand and capacity exist, the possible limits of congestion alleviation by only modifying route choices have not been systematically studied. Here we couple the road networks of five diverse cities with the travel demand profiles in the morning peak hour obtained from billions of mobile phone traces to comprehensively analyse urban traffic. We present that a dimensionless ratio of the road supply to the travel demand explains the percentage of time lost in congestion. Finally, we examine congestion relief under a centralized routing scheme with varying levels of awareness of social good and quantify the benefits to show that moderate levels are enough to achieve significant collective travel time savings.
Congestion and cascades in payment systems
Beyeler, Walter E.; Glass, Robert J.; Bech, Morten L.; Soramäki, Kimmo
2007-10-01
We develop a parsimonious model of the interbank payment system. The model incorporates an endogenous instruction arrival process, a scale-free topology of payments between banks, a fixed total liquidity which limits banks’ capacity to process arriving instructions, and a global market that distributes liquidity. We find that at low liquidity the system becomes congested and payment settlement loses correlation with payment instruction arrival, becoming coupled across the network. The onset of congestion is evidently related to the relative values of three characteristic times: the time for banks’ net position to return to 0, the time for a bank to exhaust its liquidity endowment, and the liquidity market relaxation time. In the congested regime settlement takes place in cascades having a characteristic length scale. A global liquidity market substantially attenuates congestion, requiring only a small fraction of the payment-induced liquidity flow to achieve strong beneficial effects.
Mathematical principles of road congestion pricing
African Journals Online (AJOL)
route during the morning peak hour: cost and demand functions. the same at all traffic levels. Although car running costs rise with increases in travel time in congested urban travel conditions, they are usually regarded by road users as being.
Learning Mobility: Adaptive Control Algorithms for the Novel Unmanned Ground Vehicle (NUGV)
National Research Council Canada - National Science Library
Blackburn, Mike
2003-01-01
Mobility is a serious limiting factor in the usefulness of unmanned ground vehicles, This paper contains a description of our approach to develop control algorithms for the Novel Unmanned Ground Vehicle (NUGV...
Treatment of congestion in upper respiratory diseases
Directory of Open Access Journals (Sweden)
Eli O Meltzer
2010-02-01
Full Text Available Eli O Meltzer1, Fernan Caballero2, Leonard M Fromer3, John H Krouse4, Glenis Scadding51Allergy and Asthma Medical Group and Research Center, San Diego, CA and Department of Pediatrics, University of California, San Diego, USA; 2Allergy and Clinical Immunology Service, Centro Medico-Docente La Trinidad, Caracas, Venezuela; 3David Geffen School of Medicine, University of California, Los Angeles, USA; 4Wayne State University School of Medicine, Detroit, Michigan, USA; 5Department of Allergy and Rhinology, Royal National TNE Hospital, London, UKAbstract: Congestion, as a symptom of upper respiratory tract diseases including seasonal and perennial allergic rhinitis, acute and chronic rhinosinusitis, and nasal polyposis, is principally caused by mucosal inflammation. Though effective pharmacotherapy options exist, no agent is universally efficacious; therapeutic decisions must account for individual patient preferences. Oral H1-antihistamines, though effective for the common symptoms of allergic rhinitis, have modest decongestant action, as do leukotriene receptor antagonists. Intranasal antihistamines appear to improve congestion better than oral forms. Topical decongestants reduce congestion associated with allergic rhinitis, but local adverse effects make them unsuitable for long-term use. Oral decongestants show some efficacy against congestion in allergic rhinitis and the common cold, and can be combined with oral antihistamines. Intranasal corticosteroids have broad anti-inflammatory activities, are the most potent long-term pharmacologic treatment of congestion associated with allergic rhinitis, and show some congestion relief in rhinosinusitis and nasal polyposis. Immunotherapy and surgery may be used in some cases refractory to pharmacotherapy. Steps in congestion management include (1 diagnosis of the cause(s, (2 patient education and monitoring, (3 avoidance of environmental triggers where possible, (4 pharmacotherapy, and (5 immunotherapy
National Aeronautics and Space Administration — SSCI proposes to develop and test a framework referred to as the ADVANCE (Algorithm Design and Validation for Adaptive Nonlinear Control Enhancement), within which...
Study on improved Ip-iq APF control algorithm and its application in micro grid
Xie, Xifeng; Shi, Hua; Deng, Haiyingv
2018-01-01
In order to enhance the tracking velocity and accuracy of harmonic detection by ip-iq algorithm, a novel ip-iq control algorithm based on the Instantaneous reactive power theory is presented, the improved algorithm adds the lead correction link to adjust the zero point of the detection system, the Fuzzy Self-Tuning Adaptive PI control is introduced to dynamically adjust the DC-link Voltage, which meets the requirement of the harmonic compensation of the micro grid. Simulation and experimental results verify the proposed method is feasible and effective in micro grid.
Chaos control of ferroresonance system based on RBF-maximum entropy clustering algorithm
International Nuclear Information System (INIS)
Liu Fan; Sun Caixin; Sima Wenxia; Liao Ruijin; Guo Fei
2006-01-01
With regards to the ferroresonance overvoltage of neutral grounded power system, a maximum-entropy learning algorithm based on radial basis function neural networks is used to control the chaotic system. The algorithm optimizes the object function to derive learning rule of central vectors, and uses the clustering function of network hidden layers. It improves the regression and learning ability of neural networks. The numerical experiment of ferroresonance system testifies the effectiveness and feasibility of using the algorithm to control chaos in neutral grounded system
Implementation Of Fuzzy Automated Brake Controller Using TSK Algorithm
Mittal, Ruchi; Kaur, Magandeep
2010-11-01
In this paper an application of Fuzzy Logic for Automatic Braking system is proposed. Anti-blocking system (ABS) brake controllers pose unique challenges to the designer: a) For optimal performance, the controller must operate at an unstable equilibrium point, b) Depending on road conditions, the maximum braking torque may vary over a wide range, c) The tire slippage measurement signal, crucial for controller performance, is both highly uncertain and noisy. A digital controller design was chosen which combines a fuzzy logic element and a decision logic network. The controller identifies the current road condition and generates a command braking pressure signal Depending upon the speed and distance of train. This paper describes design criteria, and the decision and rule structure of the control system. The simulation results present the system's performance depending upon the varying speed and distance of the train.
Adaptive Dynamic Programming for Control Algorithms and Stability
Zhang, Huaguang; Luo, Yanhong; Wang, Ding
2013-01-01
There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming for Control approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-...
Focus on renal congestion in heart failure.
Afsar, Baris; Ortiz, Alberto; Covic, Adrian; Solak, Yalcin; Goldsmith, David; Kanbay, Mehmet
2016-02-01
Hospitalizations due to heart failure are increasing steadily despite advances in medicine. Patients hospitalized for worsening heart failure have high mortality in hospital and within the months following discharge. Kidney dysfunction is associated with adverse outcomes in heart failure patients. Recent evidence suggests that both deterioration in kidney function and renal congestion are important prognostic factors in heart failure. Kidney congestion in heart failure results from low cardiac output (forward failure), tubuloglomerular feedback, increased intra-abdominal pressure or increased venous pressure. Regardless of the cause, renal congestion is associated with increased morbidity and mortality in heart failure. The impact on outcomes of renal decongestion strategies that do not compromise renal function should be explored in heart failure. These studies require novel diagnostic markers that identify early renal damage and renal congestion and allow monitoring of treatment responses in order to avoid severe worsening of renal function. In addition, there is an unmet need regarding evidence-based therapeutic management of renal congestion and worsening renal function. In the present review, we summarize the mechanisms, diagnosis, outcomes, prognostic markers and treatment options of renal congestion in heart failure.
Evaluation of pulmonary congestion by computed tomography
International Nuclear Information System (INIS)
Morooka, Nobuhiro; Yamamoto, Hironori; Yoshida, Hideo; Watanabe, Shigeru; Nakamura, Mamoru
1980-01-01
Pulmonary congestion and pulmonary water distribution of lung fields were evaluated by computed tomography (CT) in 31 patients with congestive heart failure and 19 normal subjects in the supine position. In normal subjects, no difference was noted in the CT value between levels of intercostal spaces as well as between right and left lung fields. CT values were greater in posterior lung fields than in anterior lung fields. A significant increase of CT values at both anterior and posterior lung fields was shown in patients with congestive heart failure compared to normal subjects. In congestive heart failure, pulmonary CT values were correlated with various clinical parameters in the order of chest X-ray findings, NYHA functional classification, venous pressure, right heart catheter findings and circulation time. CT values were decreased with the improvement of parameters by medical treatment. Thus, the increase of pulmonary CT values in patients with congestive heart failure indicated the increase of pulmonary blood content and pulmonary tissue edema in a unit volume. This method was particularly useful for the evaluation of pulmonary congestion and pulmonary water distribution. (author)
Directory of Open Access Journals (Sweden)
Christopher Dyke
2015-05-01
Full Text Available Currently, there is no manual blind control guideline used consistently throughout the energy modeling community. This paper identifies and compares five manual blind control algorithms with unique control patterns and reports blind occlusion, rate of change data, and annual building energy consumption. The blind control schemes detailed here represent five reasonable candidates for use in lighting and energy simulation based on difference driving factors. This study was performed on a medium-sized office building using EnergyPlus with the internal daylight harvesting engine. Results show that applying manual blind control algorithms affects the total annual consumption of the building by as much as 12.5% and 11.5% for interior and exterior blinds respectively, compared to the Always Retracted blinds algorithm. Peak demand was also compared showing blind algorithms affected zone load sizing by as much as 9.8%. The alternate algorithms were tested for their impact on American Society of Heating, Refrigeration and Air-Conditioning Engineers (ASHRAE Guideline 14 calibration metrics and all models were found to differ from the original calibrated baseline by more than the recommended ±15% for coefficient of variance of the mean square error (CVRMSE and ±5% for normalized mean bias error (NMBE. The paper recommends that energy modelers use one or more manual blind control algorithms during design stages when making decisions about energy efficiency and other design alternatives.
Energy efficient topology control algorithm for wireless mesh networks
CSIR Research Space (South Africa)
Aron, FO
2008-08-01
Full Text Available The control of the topology of a network makes it possible for the network nodes to reduce their power of transmission while ensuring that network connectivity is preserved. This paper explains the need for energy consumption control in Wireless...
Benchmarking Advanced Control Algorithms for a Laser Scanner System
DEFF Research Database (Denmark)
Stoustrup, Jakob; Ordys, A.W.; Smillie, I.
1996-01-01
The paper describes tests performed on the laser scanner system toassess feasibility of modern control techniques in achieving a requiredperformance in the trajectory following problem. The two methods tested areQTR H-infinity and Predictive Control. The results are ilustated ona simulation example....
Developed adaptive neuro-fuzzy algorithm to control air conditioning ...
African Journals Online (AJOL)
The paper developed artificial intelligence technique adaptive neuro-fuzzy controller for air conditioning systems at different pressures. The first order Sugeno fuzzy inference system was implemented and utilized for modeling and controller design. In addition, the estimation of the heat transfer rate and water mass flow rate ...
International Nuclear Information System (INIS)
Ghoudjehbaklou, H.; Danai, B.
2001-01-01
Reactive power dispatch for voltage profile modification has been of interest to power utilities. Usually local bus voltages can be altered by changing generator voltages, reactive shunts, ULTC transformers and SVCs. Determination of optimum values for control parameters, however, is not simple for modern power system networks. Heuristic and rather intelligent algorithms have to be sought. In this paper a new algorithm is proposed that is based on a variant of a genetic algorithm combined with simulated annealing updates. In this algorithm a fuzzy multi-objective a approach is used for the fitness function of the genetic algorithm. This fuzzy multi-objective function can efficiently modify the voltage profile in order to minimize transmission lines losses, thus reducing the operating costs. The reason for such a combination is to utilize the best characteristics of each method and overcome their deficiencies. The proposed algorithm is much faster than the classical genetic algorithm and cna be easily integrated into existing power utilities software. The proposed algorithm is tested on an actual system model of 1284 buses, 799 lines, 1175 fixed and ULTC transformers, 86 generators, 181 controllable shunts and 425 loads
Making the error-controlling algorithm of observable operator models constructive.
Zhao, Ming-Jie; Jaeger, Herbert; Thon, Michael
2009-12-01
Observable operator models (OOMs) are a class of models for stochastic processes that properly subsumes the class that can be modeled by finite-dimensional hidden Markov models (HMMs). One of the main advantages of OOMs over HMMs is that they admit asymptotically correct learning algorithms. A series of learning algorithms has been developed, with increasing computational and statistical efficiency, whose recent culmination was the error-controlling (EC) algorithm developed by the first author. The EC algorithm is an iterative, asymptotically correct algorithm that yields (and minimizes) an assured upper bound on the modeling error. The run time is faster by at least one order of magnitude than EM-based HMM learning algorithms and yields significantly more accurate models than the latter. Here we present a significant improvement of the EC algorithm: the constructive error-controlling (CEC) algorithm. CEC inherits from EC the main idea of minimizing an upper bound on the modeling error but is constructive where EC needs iterations. As a consequence, we obtain further gains in learning speed without loss in modeling accuracy.
A Novel Control Algorithm for Static Series Compensators by Use of PQR Instantaneous Power Theory
DEFF Research Database (Denmark)
Lee, Sang-Joon; Kim, Hyosung; Sul, Seung-Ki
2004-01-01
in coordinates is very simple and clear, has better steady state and dynamic performance. The controlled variables in coordinates are then inversely transformed to the original coordinates without time delay, generating control signals to SSCs. The control algorithm can be used for various kinds of SSCs...
Automatic Tuning of PID Controller for a 1-D Levitation System Using a Genetic Algorithm
DEFF Research Database (Denmark)
Yang, Zhenyu; Pedersen, Gerulf K.m.
2006-01-01
The automatic PID control design for a onedimensional magnetic levitation system is investigated. The PID controller is automatically tuned using the non-dominated sorting genetic algorithm (NSGA-II) based on a nonlinear system model. The developed controller is digitally implemented and tested...
Congestion patterns of electric vehicles with limited battery capacity
2018-01-01
The path choice behavior of battery electric vehicle (BEV) drivers is influenced by the lack of public charging stations, limited battery capacity, range anxiety and long battery charging time. This paper investigates the congestion/flow pattern captured by stochastic user equilibrium (SUE) traffic assignment problem in transportation networks with BEVs, where the BEV paths are restricted by their battery capacities. The BEV energy consumption is assumed to be a linear function of path length and path travel time, which addresses both path distance limit problem and road congestion effect. A mathematical programming model is proposed for the path-based SUE traffic assignment where the path cost is the sum of the corresponding link costs and a path specific out-of-energy penalty. We then apply the convergent Lagrangian dual method to transform the original problem into a concave maximization problem and develop a customized gradient projection algorithm to solve it. A column generation procedure is incorporated to generate the path set. Finally, two numerical examples are presented to demonstrate the applicability of the proposed model and the solution algorithm. PMID:29543875
Congestion patterns of electric vehicles with limited battery capacity.
Jing, Wentao; Ramezani, Mohsen; An, Kun; Kim, Inhi
2018-01-01
The path choice behavior of battery electric vehicle (BEV) drivers is influenced by the lack of public charging stations, limited battery capacity, range anxiety and long battery charging time. This paper investigates the congestion/flow pattern captured by stochastic user equilibrium (SUE) traffic assignment problem in transportation networks with BEVs, where the BEV paths are restricted by their battery capacities. The BEV energy consumption is assumed to be a linear function of path length and path travel time, which addresses both path distance limit problem and road congestion effect. A mathematical programming model is proposed for the path-based SUE traffic assignment where the path cost is the sum of the corresponding link costs and a path specific out-of-energy penalty. We then apply the convergent Lagrangian dual method to transform the original problem into a concave maximization problem and develop a customized gradient projection algorithm to solve it. A column generation procedure is incorporated to generate the path set. Finally, two numerical examples are presented to demonstrate the applicability of the proposed model and the solution algorithm.
A chaos-based image encryption algorithm with variable control parameters
International Nuclear Information System (INIS)
Wang Yong; Wong, K.-W.; Liao Xiaofeng; Xiang Tao; Chen Guanrong
2009-01-01
In recent years, a number of image encryption algorithms based on the permutation-diffusion structure have been proposed. However, the control parameters used in the permutation stage are usually fixed in the whole encryption process, which favors attacks. In this paper, a chaos-based image encryption algorithm with variable control parameters is proposed. The control parameters used in the permutation stage and the keystream employed in the diffusion stage are generated from two chaotic maps related to the plain-image. As a result, the algorithm can effectively resist all known attacks against permutation-diffusion architectures. Theoretical analyses and computer simulations both confirm that the new algorithm possesses high security and fast encryption speed for practical image encryption.
Scalable algorithms for optimal control of stochastic PDEs
Ghattas, Omar
2016-01-07
We present methods for the optimal control of systems governed by partial differential equations with infinite-dimensional uncertain parameters. We consider an objective function that involves the mean and variance of the control objective, leading to a risk-averse optimal control formulation. To make the optimal control problem computationally tractable, we employ a local quadratic approximation of the objective with respect to the uncertain parameter. This enables computation of the mean and variance of the control objective analytically. The resulting risk-averse optimization problem is formulated as a PDE-constrained optimization problem with constraints given by the forward and adjoint PDEs for the first and second-order derivatives of the quantity of interest with respect to the uncertain parameter, and with an objective that involves the trace of a covariance-preconditioned Hessian (of the objective with respect to the uncertain parameters) operator. A randomized trace estimator is used to make tractable the trace computation. Adjoint-based techniques are used to derive an expression for the infinite-dimensional gradient of the risk-averse objective function via the Lagrangian, leading to a quasi-Newton method for solution of the optimal control problem. A specific problem of optimal control of a linear elliptic PDE that describes flow of a fluid in a porous medium with uncertain permeability field is considered. We present numerical results to study the consequences of the local quadratic approximation and the efficiency of the method.
Scalable algorithms for optimal control of stochastic PDEs
Ghattas, Omar; Alexanderian, Alen; Petra, Noemi; Stadler, Georg
2016-01-01
We present methods for the optimal control of systems governed by partial differential equations with infinite-dimensional uncertain parameters. We consider an objective function that involves the mean and variance of the control objective, leading to a risk-averse optimal control formulation. To make the optimal control problem computationally tractable, we employ a local quadratic approximation of the objective with respect to the uncertain parameter. This enables computation of the mean and variance of the control objective analytically. The resulting risk-averse optimization problem is formulated as a PDE-constrained optimization problem with constraints given by the forward and adjoint PDEs for the first and second-order derivatives of the quantity of interest with respect to the uncertain parameter, and with an objective that involves the trace of a covariance-preconditioned Hessian (of the objective with respect to the uncertain parameters) operator. A randomized trace estimator is used to make tractable the trace computation. Adjoint-based techniques are used to derive an expression for the infinite-dimensional gradient of the risk-averse objective function via the Lagrangian, leading to a quasi-Newton method for solution of the optimal control problem. A specific problem of optimal control of a linear elliptic PDE that describes flow of a fluid in a porous medium with uncertain permeability field is considered. We present numerical results to study the consequences of the local quadratic approximation and the efficiency of the method.
Development of fuzzy algorithm with learning function for nuclear steam generator level control
International Nuclear Information System (INIS)
Park, Gee Yong; Seong, Poong Hyun
1993-01-01
A fuzzy algorithm with learning function is applied to the steam generator level control of nuclear power plant. This algorithm can make its rule base and membership functions suited for steam generator level control by use of the data obtained from the control actions of a skilled operator or of other controllers (i.e., PID controller). The rule base of fuzzy controller with learning function is divided into two parts. One part of the rule base is provided to level control of steam generator at low power level (0 % - 30 % of full power) and the other to level control at high power level (30 % - 100 % of full power). Response time of steam generator level control at low power range with this rule base is shown to be shorter than that of fuzzy controller with direct inference. (Author)
A review on control system algorithm for building automation systems
CSIR Research Space (South Africa)
Noubissie-Tientcheu, SI
2016-09-01
Full Text Available The building with its components such as Heating Ventilation Air Conditioning (HVAC) and lighting constitute a bigger part of energy consumption in Southern Africa. Control system in a building reduced the energy consumption, according to different...
Benefits from coordinating congestion management-The Nordic power market
International Nuclear Information System (INIS)
Bjorndal, Mette; Joernsten, Kurt
2007-01-01
We consider the possibility of improving the utilization of the capacity of the Nordic transmission grid, by improving on the methods for congestion management. We use a simplified model of the Nordic power market, and different load-scenarios are developed in order to illustrate the effects. By improving the coordination of the system operator function, we may achieve that the actual bottlenecks, both as regards to the location and capacity, form the basis for the definition of price areas. This may result in a better partition of the grid, not necessarily following the borders between the control areas of today's system operators. We also consider solving intra zonal bottlenecks 'directly', through the area prices and 'indirectly' by 'moving' internal capacity constraints to the borders between price areas. The examples illustrate that this 'indirect' congestion management may be costly, and result in larger price differences than necessary
International Nuclear Information System (INIS)
Coban, Ramazan
2011-01-01
Research highlights: → A closed-loop fuzzy logic controller based on the particle swarm optimization algorithm was proposed for controlling the power level of nuclear research reactors. → The proposed control system was tested for various initial and desired power levels, and it could control the reactor successfully for most situations. → The proposed controller is robust against the disturbances. - Abstract: In this paper, a closed-loop fuzzy logic controller based on the particle swarm optimization algorithm is proposed for controlling the power level of nuclear research reactors. The principle of the fuzzy logic controller is based on the rules constructed from numerical experiments made by means of a computer code for the core dynamics calculation and from human operator's experience and knowledge. In addition to these intuitive and experimental design efforts, consequent parts of the fuzzy rules are optimally (or near optimally) determined using the particle swarm optimization algorithm. The contribution of the proposed algorithm to a reactor control system is investigated in details. The performance of the controller is also tested with numerical simulations in numerous operating conditions from various initial power levels to desired power levels, as well as under disturbance. It is shown that the proposed control system performs satisfactorily under almost all operating conditions, even in the case of very small initial power levels.
State-Space Equations and the First-Phase Algorithm for Signal Control of Single Intersections
Institute of Scientific and Technical Information of China (English)
LI Jinyuan; PAN Xin; WANG Xiqin
2007-01-01
State-space equations were applied to formulate the queuing and delay of traffic at a single intersection in this paper. The signal control of a single intersection was then modeled as a discrete-time optimal control problem, with consideration of the constraints of stream conflicts, saturation flow rate, minimum green time, and maximum green time. The problem cannot be solved directly due to the nonlinear constraints.However, the results of qualitative analysis were used to develop a first-phase signal control algorithm. Simulation results show that the algorithm substantially reduces the total delay compared to fixed-time control.
Moore, J H
1995-06-01
A genetic algorithm for instrumentation control and optimization was developed using the LabVIEW graphical programming environment. The usefulness of this methodology for the optimization of a closed loop control instrument is demonstrated with minimal complexity and the programming is presented in detail to facilitate its adaptation to other LabVIEW applications. Closed loop control instruments have variety of applications in the biomedical sciences including the regulation of physiological processes such as blood pressure. The program presented here should provide a useful starting point for those wishing to incorporate genetic algorithm approaches to LabVIEW mediated optimization of closed loop control instruments.
Extracting quantum dynamics from genetic learning algorithms through principal control analysis
International Nuclear Information System (INIS)
White, J L; Pearson, B J; Bucksbaum, P H
2004-01-01
Genetic learning algorithms are widely used to control ultrafast optical pulse shapes for photo-induced quantum control of atoms and molecules. An unresolved issue is how to use the solutions found by these algorithms to learn about the system's quantum dynamics. We propose a simple method based on covariance analysis of the control space, which can reveal the degrees of freedom in the effective control Hamiltonian. We have applied this technique to stimulated Raman scattering in liquid methanol. A simple model of two-mode stimulated Raman scattering is consistent with the results. (letter to the editor)
Quadratic Stabilization of LPV System by an LTI Controller Based on ILMI Algorithm
Directory of Open Access Journals (Sweden)
Wei Xie
2007-01-01
Full Text Available A linear time-invariant (LTI output feedback controller is designed for a linear parameter-varying (LPV control system to achieve quadratic stability. The LPV system includes immeasurable dependent parameters that are assumed to vary in a polytopic space. To solve this control problem, a heuristic algorithm is proposed in the form of an iterative linear matrix inequality (ILMI formulation. Furthermore, an effective method of setting an initial value of the ILMI algorithm is also proposed to increase the probability of getting an admissible solution for the controller design problem.
Lung congestion in chronic heart failure: haemodynamic, clinical, and prognostic implications
DEFF Research Database (Denmark)
Melenovsky, Vojtech; Andersen, Mads Jønsson; Andress, Krystof
2015-01-01
AIMS:The goal of the study was to examine the prognostic impact, haemodynamic and clinical features associated with lung congestion in patients with chronic heart failure (HF). METHODS AND RESULTS:HF patients (n = 186) and HF-free controls (n = 21) underwent right heart catheterization...... days (interquartile range 80-875), 59 patients (32%) died. Lung congestion was associated with reduced survival (P renal dysfunction. CONCLUSION:Interstitial lung oedema is associated with pulmonary vascular disease, RV overload...
Pan, Indranil; Das, Saptarshi; Gupta, Amitava
2011-01-01
An optimal PID and an optimal fuzzy PID have been tuned by minimizing the Integral of Time multiplied Absolute Error (ITAE) and squared controller output for a networked control system (NCS). The tuning is attempted for a higher order and a time delay system using two stochastic algorithms viz. the Genetic Algorithm (GA) and two variants of Particle Swarm Optimization (PSO) and the closed loop performances are compared. The paper shows that random variation in network delay can be handled efficiently with fuzzy logic based PID controllers over conventional PID controllers. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.
Optimization of type-2 fuzzy controllers using the bee colony algorithm
Amador, Leticia
2017-01-01
This book focuses on the fields of fuzzy logic, bio-inspired algorithm; especially bee colony optimization algorithm and also considering the fuzzy control area. The main idea is that this areas together can to solve various control problems and to find better results. In this book we test the proposed method using two benchmark problems; the problem for filling a water tank and the problem for controlling the trajectory in an autonomous mobile robot. When Interval Type-2 Fuzzy Logic System is implemented to model the behavior of systems, the results show a better stabilization, because the analysis of uncertainty is better. For this reason we consider in this book the proposed method using fuzzy systems, fuzzy controllers, and bee colony optimization algorithm improve the behavior of the complex control problems.
Randomized Algorithms for Analysis and Control of Uncertain Systems With Applications
Tempo, Roberto; Dabbene, Fabrizio
2013-01-01
The presence of uncertainty in a system description has always been a critical issue in control. The main objective of Randomized Algorithms for Analysis and Control of Uncertain Systems, with Applications (Second Edition) is to introduce the reader to the fundamentals of probabilistic methods in the analysis and design of systems subject to deterministic and stochastic uncertainty. The approach propounded by this text guarantees a reduction in the computational complexity of classical control algorithms and in the conservativeness of standard robust control techniques. The second edition has been thoroughly updated to reflect recent research and new applications with chapters on statistical learning theory, sequential methods for control and the scenario approach being completely rewritten. Features: · self-contained treatment explaining Monte Carlo and Las Vegas randomized algorithms from their genesis in the principles of probability theory to their use for system analysis; · ...
Velocity control of servo systems using an integral retarded algorithm.
Ramírez, Adrián; Garrido, Rubén; Mondié, Sabine
2015-09-01
This paper presents a design technique for the delay-based controller called Integral Retarded (IR), and its applications to velocity control of servo systems. Using spectral analysis, the technique yields a tuning strategy for the IR by assigning a triple real dominant root for the closed-loop system. This result ultimately guarantees a desired exponential decay rate σ(d) while achieving the IR tuning as explicit function of σ(d) and system parameters. The intentional introduction of delay allows using noisy velocity measurements without additional filtering. The structure of the controller is also able to avoid velocity measurements by using instead position information. The IR is compared to a classical PI, both tested in a laboratory prototype. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Advanced algorithm for MPPT control of photovoltaic systems
Energy Technology Data Exchange (ETDEWEB)
Liu, C.; Wu, B.; Cheung, R. [Ryerson Polytechnic Univ., Toronto, ON (Canada). Dept. of Electrical and Computer Engineering
2006-07-01
Although photovoltaic (PV) energy is a renewable, environmentally sound source of electricity, it is relatively costly. The maximum power point tracking (MPPT) of the PV output for all sunshine conditions is key to keeping the output power per unit cost low for successful PV applications. The MPPT control is challenging, because the sunshine condition that determines the amount of sun energy into the PV array may change at any time, and the voltage/current characteristic of PV arrays is highly nonlinear. The 5 components of a PV system for the grid-connected applications are a PV array that converts solar energy to electric energy; a dc-dc converter that converts low dc voltages produced by the PV arrays to a high dc voltage; an inverter that converts the high dc voltage to a single- or three-phase ac voltage; a digital controller that controls the converter operation with MPPT capability; and, an ac filter that absorbs voltage/current harmonics generated by the inverter. The technical requirements in developing a practical PV system include an optimal control that can extract the maximum output power from the PV arrays under all operating and weather conditions, and a high performance-to-cost ratio to help commercialize developed PV technologies. This paper proposed a new method for the MPPT control of PV systems. The new method uses one estimate process for every two perturb processes in search of the maximum PV output for all sunshine conditions. In this estimate-perturb-perturb (EPP) method, the perturb process conducts the search over a highly nonlinear PV characteristic, and the estimate process compensates the perturb process for irradiance-changing conditions. The EPP method improves the tracking accuracy and speed of the MPPT control compared to other methods. This paper demonstrated that the EPP method can provide accurate and reliable MPPT even under rapidly changing irradiance conditions. A grid-connected PV system using three MPPT controls was
An Algorithm for Creating Virtual Controls Using Integrated and Harmonized Longitudinal Data.
Hansen, William B; Chen, Shyh-Huei; Saldana, Santiago; Ip, Edward H
2018-06-01
We introduce a strategy for creating virtual control groups-cases generated through computer algorithms that, when aggregated, may serve as experimental comparators where live controls are difficult to recruit, such as when programs are widely disseminated and randomization is not feasible. We integrated and harmonized data from eight archived longitudinal adolescent-focused data sets spanning the decades from 1980 to 2010. Collectively, these studies examined numerous psychosocial variables and assessed past 30-day alcohol, cigarette, and marijuana use. Additional treatment and control group data from two archived randomized control trials were used to test the virtual control algorithm. Both randomized controlled trials (RCTs) assessed intentions, normative beliefs, and values as well as past 30-day alcohol, cigarette, and marijuana use. We developed an algorithm that used percentile scores from the integrated data set to create age- and gender-specific latent psychosocial scores. The algorithm matched treatment case observed psychosocial scores at pretest to create a virtual control case that figuratively "matured" based on age-related changes, holding the virtual case's percentile constant. Virtual controls matched treatment case occurrence, eliminating differential attrition as a threat to validity. Virtual case substance use was estimated from the virtual case's latent psychosocial score using logistic regression coefficients derived from analyzing the treatment group. Averaging across virtual cases created group estimates of prevalence. Two criteria were established to evaluate the adequacy of virtual control cases: (1) virtual control group pretest drug prevalence rates should match those of the treatment group and (2) virtual control group patterns of drug prevalence over time should match live controls. The algorithm successfully matched pretest prevalence for both RCTs. Increases in prevalence were observed, although there were discrepancies between live
Acikmese, Behcet A.; Carson, John M., III
2005-01-01
A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees the resolvability of the associated finite-horizon optimal control problem in a receding-horizon implementation. The control consists of two components; (i) feedforward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives, and derivatives in polytopes. An illustrative numerical example is also provided.
Directory of Open Access Journals (Sweden)
Jinzhi Feng
2015-02-01
Full Text Available A new hierarchical control strategy for active hydropneumatic suspension systems is proposed. This strategy considers the dynamic characteristics of the actuator. The top hierarchy controller uses a combined control scheme: a genetic algorithm- (GA- based self-tuning proportional-integral-derivative controller and a fuzzy logic controller. For practical implementations of the proposed control scheme, a GA-based self-learning process is initiated only when the defined performance index of vehicle dynamics exceeds a certain debounce time threshold. The designed control algorithm is implemented on a virtual prototype and cosimulations are performed with different road disturbance inputs. Cosimulation results show that the active hydropneumatic suspension system designed in this study significantly improves riding comfort characteristics of vehicles. The robustness and adaptability of the proposed controller are also examined when the control system is subjected to extremely rough road conditions.
A semi-active suspension control algorithm for vehicle comprehensive vertical dynamics performance
Nie, Shida; Zhuang, Ye; Liu, Weiping; Chen, Fan
2017-08-01
Comprehensive performance of the vehicle, including ride qualities and road-holding, is essentially of great value in practice. Many up-to-date semi-active control algorithms improve vehicle dynamics performance effectively. However, it is hard to improve comprehensive performance for the conflict between ride qualities and road-holding around the second-order resonance. Hence, a new control algorithm is proposed to achieve a good trade-off between ride qualities and road-holding. In this paper, the properties of the invariant points are analysed, which gives an insight into the performance conflicting around the second-order resonance. Based on it, a new control algorithm is proposed. The algorithm employs a novel frequency selector to balance suspension ride and handling performance by adopting a medium damping around the second-order resonance. The results of this study show that the proposed control algorithm could improve the performance of ride qualities and suspension working space up to 18.3% and 8.2%, respectively, with little loss of road-holding compared to the passive suspension. Consequently, the comprehensive performance can be improved by 6.6%. Hence, the proposed algorithm is of great potential to be implemented in practice.
Distributed topology control algorithm for multihop wireless netoworks
Borbash, S. A.; Jennings, E. H.
2002-01-01
We present a network initialization algorithmfor wireless networks with distributed intelligence. Each node (agent) has only local, incomplete knowledge and it must make local decisions to meet a predefined global objective. Our objective is to use power control to establish a topology based onthe relative neighborhood graph which has good overall performance in terms of power usage, low interference, and reliability.
Developed adaptive neuro-fuzzy algorithm to control air conditioning ...
African Journals Online (AJOL)
user
... conditioning system is highly appreciated and essential in most of our daily life. ... (Hossien and Karla, 2012) presented an overview work which provides an .... energy balance for SSSF and the mass flow balance for the water in the air are ..... of Automatic Control and Electrical Engineering at Siegen University, Germany.
Scheduling algorithms for automatic control systems for technological processes
Chernigovskiy, A. S.; Tsarev, R. Yu; Kapulin, D. V.
2017-01-01
Wide use of automatic process control systems and the usage of high-performance systems containing a number of computers (processors) give opportunities for creation of high-quality and fast production that increases competitiveness of an enterprise. Exact and fast calculations, control computation, and processing of the big data arrays - all of this requires the high level of productivity and, at the same time, minimum time of data handling and result receiving. In order to reach the best time, it is necessary not only to use computing resources optimally, but also to design and develop the software so that time gain will be maximal. For this purpose task (jobs or operations), scheduling techniques for the multi-machine/multiprocessor systems are applied. Some of basic task scheduling methods for the multi-machine process control systems are considered in this paper, their advantages and disadvantages come to light, and also some usage considerations, in case of the software for automatic process control systems developing, are made.
Efficient Algorithms for Network-Wide Road Traffic Control
van de Weg, G.S.
2017-01-01
Controlling road traffic networks is a complex problem. One of the difficulties is the coordination of actuators, such as traffic lights, variables speed limits, ramp metering and route guidance, with the aim to improve the network performance over a near-future time horizon. This dissertation
Developed adaptive neuro-fuzzy algorithm to control air conditioning ...
African Journals Online (AJOL)
user
The paper developed artificial intelligence technique adaptive neuro-fuzzy ... system is highly appreciated and essential in most of our daily life. ... It can construct an input-output mapping based on human knowledge and specific input-output data ... fuzzy controllers to produce desirable internal temperature and air quality, ...
Instructional Regulation and Control: Cybernetics, Algorithmization and Heuristics in Education.
Landa, L. N.; And Others
This book on the aspects of instructional processes focuses on control of student cognitive activity during instruction. Chapter 1 introduces the cybernetic approach to the theory of instruction. It is followed by a chapter on instructional effectiveness and efficiency. The third chapter discusses cognitive processes and thinking. Chapter 4…
Efficient Algorithms for Distributed Control : A Structured Matrix Approach
Rice, J.K.
2010-01-01
Distributed systems are all around us, and they are fascinating, and have an enormous potential to improve our lives, if their complexity can be properly harnessed. All scientists and engineers are aware of the great potential of this subject, since we witness fantastic distributed control systems
Online learning algorithms : For passivity-based and distributed control
Nageshrao, S.P.
2016-01-01
Over the last couple of decades the demand for high precision and enhanced performance of physical systems has been steadily increasing. This demand often results in miniaturization and complex design, thus increasing the need for complex nonlinear control methods. Some of the state of the art
A Modified LQG Algorithm (MLQG for Robust Control of Nonlinear Multivariable Systems
Directory of Open Access Journals (Sweden)
Jens G. Balchen
1993-07-01
Full Text Available The original LQG algorithm is often characterized for its lack of robustness. This is because in the design of the estimator (Kalman filter the process disturbance is assumed to be white noise. If the estimator is to give good estimates, the Kalman gain is increased which means that the estimator fails to become robust. A solution to this problem is to replace the proportional Kalman gain matrix by a dynamic PI algorithm and the proportional LQ feedback gain matrix by a PI algorithm. A tuning method is developed which facilitates the tuning of a modified LQG control system (MLQG by only two tuning parameters.
Analysis of the Command and Control Segment (CCS) attitude estimation algorithm
Stockwell, Catherine
1993-01-01
This paper categorizes the qualitative behavior of the Command and Control Segment (CCS) differential correction algorithm as applied to attitude estimation using simultaneous spin axis sun angle and Earth cord length measurements. The categories of interest are the domains of convergence, divergence, and their boundaries. Three series of plots are discussed that show the dependence of the estimation algorithm on the vehicle radius, the sun/Earth angle, and the spacecraft attitude. Common qualitative dynamics to all three series are tabulated and discussed. Out-of-limits conditions for the estimation algorithm are identified and discussed.
A homotopy algorithm for digital optimal projection control GASD-HADOC
Collins, Emmanuel G., Jr.; Richter, Stephen; Davis, Lawrence D.
1993-01-01
The linear-quadratic-gaussian (LQG) compensator was developed to facilitate the design of control laws for multi-input, multi-output (MIMO) systems. The compensator is computed by solving two algebraic equations for which standard closed-loop solutions exist. Unfortunately, the minimal dimension of an LQG compensator is almost always equal to the dimension of the plant and can thus often violate practical implementation constraints on controller order. This deficiency is especially highlighted when considering control-design for high-order systems such as flexible space structures. This deficiency motivated the development of techniques that enable the design of optimal controllers whose dimension is less than that of the design plant. A homotopy approach based on the optimal projection equations that characterize the necessary conditions for optimal reduced-order control. Homotopy algorithms have global convergence properties and hence do not require that the initializing reduced-order controller be close to the optimal reduced-order controller to guarantee convergence. However, the homotopy algorithm previously developed for solving the optimal projection equations has sublinear convergence properties and the convergence slows at higher authority levels and may fail. A new homotopy algorithm for synthesizing optimal reduced-order controllers for discrete-time systems is described. Unlike the previous homotopy approach, the new algorithm is a gradient-based, parameter optimization formulation and was implemented in MATLAB. The results reported may offer the foundation for a reliable approach to optimal, reduced-order controller design.
Design and experimental evaluation of flexible manipulator control algorithms
International Nuclear Information System (INIS)
Kwon, D.S.; Hwang, D.H.; Babcock, S.M.; Kress, R.L.
1995-01-01
Within the Environmental Restoration and Waste Management Program of the US Department of Energy, the remediation of single-shell radioactive waste storage tanks is one of the areas that challenge state-of-the-art equipment and methods. The use of long-reach manipulators is being seriously considered for this task. Because of high payload capacity and high length-to-cross-section ratio requirements, these long-reach manipulator systems are expected to use hydraulic actuators and to exhibit significant structural flexibility. The controller has been designed to compensate for the hydraulic actuator dynamics by using a load-compensated velocity feedforward loop and to increase the bandwidth by using an inner pressure feedback loop. Shaping filter techniques have been applied as feedforward controllers to avoid structural vibrations during operation. Various types of shaping filter methods have been investigated. Among them, a new approach, referred to as a ''feedforward simulation filter'' that uses embedded simulation, has been presented
Algorithm for motion control of an exoskeleton during verticalization
Directory of Open Access Journals (Sweden)
Jatsun Sergey
2016-01-01
Full Text Available This paper considers lower limb exoskeleton that performs sit-to-stand motion. The work is focused on the control system design. An application of a null space projection methods for solving inverse kinematics problem is discussed. An adaptive multi-input multi-output regulator for the system is presented with the motivation for that choice. Results of the simulation for different versions of the regulator are shown.
Robust PD Sway Control of a Lifted Load for a Crane Using a Genetic Algorithm
Kawada, Kazuo; Sogo, Hiroyuki; Yamamoto, Toru; Mada, Yasuhiro
PID control schemes still continue to be widely used for most industrial control systems. This is mainly because PID controllers have simple control structures, and are simple to maintain and tune. However, it is difficult to find a set of suitable control parameters in the case of time-varying and/or nonlinear systems. For such a problem, the robust controller has been proposed.Although it is important to choose the suitable nominal model in designing the robust controller, it is not usually easy.In this paper, a new robust PD controller design scheme is proposed, which utilizes a genetic algorithm.
Traffic congestion and blood pressure elevation: A comparative cross-sectional study in Lebanon.
Bou Samra, Patrick; El Tomb, Paul; Hosni, Mohammad; Kassem, Ahmad; Rizk, Robin; Shayya, Sami; Assaad, Sarah
2017-12-01
This comparative cross-sectional study examines the association between traffic congestion and elevation of systolic and/or diastolic blood pressure levels among a convenience sample of 310 drivers. Data collection took place during a gas station pause at a fixed time of day. Higher average systolic (142 vs 123 mm Hg) and diastolic (87 vs 78 mm Hg) blood pressures were detected among drivers exposed to traffic congestion compared with those who were not exposed (P<.001), while controlling for body mass index, age, sex, pack-year smoking, driving hours per week, and occupational driving. Moreover, among persons exposed to traffic congestion, longer exposure time was associated with higher systolic and diastolic blood pressures. Further studies are needed to better understand the mechanisms of the significant association between elevated blood pressure and traffic congestion. ©2017 Wiley Periodicals, Inc.
Modeling and Design of MPPT Controller Using Stepped P&O Algorithm in Solar Photovoltaic System
R. Prakash; B. Meenakshipriya; R. Kumaravelan
2014-01-01
This paper presents modeling and simulation of Grid Connected Photovoltaic (PV) system by using improved mathematical model. The model is used to study different parameter variations and effects on the PV array including operating temperature and solar irradiation level. In this paper stepped P&O algorithm is proposed for MPPT control. This algorithm will identify the suitable duty ratio in which the DC-DC converter should be operated to maximize the power output. Photo voltaic array with pro...
A controlled genetic algorithm by fuzzy logic and belief functions for job-shop scheduling.
Hajri, S; Liouane, N; Hammadi, S; Borne, P
2000-01-01
Most scheduling problems are highly complex combinatorial problems. However, stochastic methods such as genetic algorithm yield good solutions. In this paper, we present a controlled genetic algorithm (CGA) based on fuzzy logic and belief functions to solve job-shop scheduling problems. For better performance, we propose an efficient representational scheme, heuristic rules for creating the initial population, and a new methodology for mixing and computing genetic operator probabilities.
Method to evaluate steering and alignment algorithms for controlling emittance growth
International Nuclear Information System (INIS)
Adolphsen, C.; Raubenheimer, T.
1993-04-01
Future linear colliders will likely use sophisticated beam-based alignment and/or steering algorithms to control the growth of the beam emittance in the linac. In this paper, a mathematical framework is presented which simplifies the evaluation of the effectiveness of these algorithms. As an application, a quad alignment that uses beam data taken with the nominal linac optics, and with a scaled optics, is evaluated in terms of the dispersive emittance growth remaining after alignment
A parallel adaptive quantum genetic algorithm for the controllability of arbitrary networks
Li, Yuhong
2018-01-01
In this paper, we propose a novel algorithm—parallel adaptive quantum genetic algorithm—which can rapidly determine the minimum control nodes of arbitrary networks with both control nodes and state nodes. The corresponding network can be fully controlled with the obtained control scheme. We transformed the network controllability issue into a combinational optimization problem based on the Popov-Belevitch-Hautus rank condition. A set of canonical networks and a list of real-world networks were experimented. Comparison results demonstrated that the algorithm was more ideal to optimize the controllability of networks, especially those larger-size networks. We demonstrated subsequently that there were links between the optimal control nodes and some network statistical characteristics. The proposed algorithm provides an effective approach to improve the controllability optimization of large networks or even extra-large networks with hundreds of thousands nodes. PMID:29554140
Congestion transition in air traffic networks.
Directory of Open Access Journals (Sweden)
Bernardo Monechi
Full Text Available Air Transportation represents a very interesting example of a complex techno-social system whose importance has considerably grown in time and whose management requires a careful understanding of the subtle interplay between technological infrastructure and human behavior. Despite the competition with other transportation systems, a growth of air traffic is still foreseen in Europe for the next years. The increase of traffic load could bring the current Air Traffic Network above its capacity limits so that safety standards and performances might not be guaranteed anymore. Lacking the possibility of a direct investigation of this scenario, we resort to computer simulations in order to quantify the disruptive potential of an increase in traffic load. To this end we model the Air Transportation system as a complex dynamical network of flights controlled by humans who have to solve potentially dangerous conflicts by redirecting aircraft trajectories. The model is driven and validated through historical data of flight schedules in a European national airspace. While correctly reproducing actual statistics of the Air Transportation system, e.g., the distribution of delays, the model allows for theoretical predictions. Upon an increase of the traffic load injected in the system, the model predicts a transition from a phase in which all conflicts can be successfully resolved, to a phase in which many conflicts cannot be resolved anymore. We highlight how the current flight density of the Air Transportation system is well below the transition, provided that controllers make use of a special re-routing procedure. While the congestion transition displays a universal scaling behavior, its threshold depends on the conflict solving strategy adopted. Finally, the generality of the modeling scheme introduced makes it a flexible general tool to simulate and control Air Transportation systems in realistic and synthetic scenarios.
Congestion transition in air traffic networks.
Monechi, Bernardo; Servedio, Vito D P; Loreto, Vittorio
2015-01-01
Air Transportation represents a very interesting example of a complex techno-social system whose importance has considerably grown in time and whose management requires a careful understanding of the subtle interplay between technological infrastructure and human behavior. Despite the competition with other transportation systems, a growth of air traffic is still foreseen in Europe for the next years. The increase of traffic load could bring the current Air Traffic Network above its capacity limits so that safety standards and performances might not be guaranteed anymore. Lacking the possibility of a direct investigation of this scenario, we resort to computer simulations in order to quantify the disruptive potential of an increase in traffic load. To this end we model the Air Transportation system as a complex dynamical network of flights controlled by humans who have to solve potentially dangerous conflicts by redirecting aircraft trajectories. The model is driven and validated through historical data of flight schedules in a European national airspace. While correctly reproducing actual statistics of the Air Transportation system, e.g., the distribution of delays, the model allows for theoretical predictions. Upon an increase of the traffic load injected in the system, the model predicts a transition from a phase in which all conflicts can be successfully resolved, to a phase in which many conflicts cannot be resolved anymore. We highlight how the current flight density of the Air Transportation system is well below the transition, provided that controllers make use of a special re-routing procedure. While the congestion transition displays a universal scaling behavior, its threshold depends on the conflict solving strategy adopted. Finally, the generality of the modeling scheme introduced makes it a flexible general tool to simulate and control Air Transportation systems in realistic and synthetic scenarios.
National Research Council Canada - National Science Library
Floodeen, David
1998-01-01
The objective of this thesis is two-fold. The first goal is to expand the operational capabilities of the Ship's Service Converter Module control algorithm for a DC-to-DC converter using the Universal Controller...
An on-line modified least-mean-square algorithm for training neurofuzzy controllers.
Tan, Woei Wan
2007-04-01
The problem hindering the use of data-driven modelling methods for training controllers on-line is the lack of control over the amount by which the plant is excited. As the operating schedule determines the information available on-line, the knowledge of the process may degrade if the setpoint remains constant for an extended period. This paper proposes an identification algorithm that alleviates "learning interference" by incorporating fuzzy theory into the normalized least-mean-square update rule. The ability of the proposed methodology to achieve faster learning is examined by employing the algorithm to train a neurofuzzy feedforward controller for controlling a liquid level process. Since the proposed identification strategy has similarities with the normalized least-mean-square update rule and the recursive least-square estimator, the on-line learning rates of these algorithms are also compared.
Directory of Open Access Journals (Sweden)
Rabindra Kumar Sahu
2014-09-01
Full Text Available An attempt is made for the effective application of Gravitational Search Algorithm (GSA to optimize PI/PIDF controller parameters in Automatic Generation Control (AGC of interconnected power systems. Initially, comparison of several conventional objective functions reveals that ITAE yields better system performance. Then, the parameters of GSA technique are properly tuned and the GSA control parameters are proposed. The superiority of the proposed approach is demonstrated by comparing the results of some recently published techniques such as Differential Evolution (DE, Bacteria Foraging Optimization Algorithm (BFOA and Genetic Algorithm (GA. Additionally, sensitivity analysis is carried out that demonstrates the robustness of the optimized controller parameters to wide variations in operating loading condition and time constants of speed governor, turbine, tie-line power. Finally, the proposed approach is extended to a more realistic power system model by considering the physical constraints such as reheat turbine, Generation Rate Constraint (GRC and Governor Dead Band nonlinearity.
Machine vision algorithms applied to dynamic traffic light control
Directory of Open Access Journals (Sweden)
Fabio Andrés Espinosa Valcárcel
2013-01-01
número de autos presentes en imágenes capturadas por un conjunto de cámaras estratégicamente ubicadas en cada intersección. Usando esta información, el sistema selecciona la secuencia de acciones que optimicen el flujo vehicular dentro de la zona de control, en un escenario simulado. Los resultados obtenidos muestran que el sistema disminuye en un 20% los tiempos de retraso para cada vehículo y que además es capaz de adaptarse rápida y eficientemente a los cambios de flujo.
Yanagisawa, Masahiro
2007-01-01
We provide a control theoretical method for a computational lower bound of quantum algorithms based on quantum walks of a finite time horizon. It is shown that given a quantum network, there exists a control theoretical expression of the quantum system and the transition probability of the quantum walk is related to a norm of the associated transfer function.
Saltik, M.B.; Özkan, L.; Ludlage, J.H.A.; Weiland, S.; Van den Hof, P.M.J.
2018-01-01
In this paper, we discuss the model predictive control algorithms that are tailored for uncertain systems. Robustness notions with respect to both deterministic (or set based) and stochastic uncertainties are discussed and contributions are reviewed in the model predictive control literature. We
Control Algorithms Along Relative Equilibria of Underactuated Lagrangian Systems on Lie Groups
DEFF Research Database (Denmark)
Nordkvist, Nikolaj; Bullo, F.
2008-01-01
We present novel algorithms to control underactuated mechanical systems. For a class of invariant systems on Lie groups, we design iterative small-amplitude control forces to accelerate along, decelerate along, and stabilize relative equilibria. The technical approach is based upon a perturbation...
Control algorithms along relative equilibria of underactuated Lagrangian systems on Lie groups
DEFF Research Database (Denmark)
Nordkvist, Nikolaj; Bullo, Francesco
2007-01-01
We present novel algorithms to control underactuated mechanical systems. For a class of invariant systems on Lie groups, we design iterative small-amplitude control forces to accelerate along, decelerate along, and stabilize relative equilibria. The technical approach is based upon a perturbation...
Cohesive Motion Control Algorithm for Formation of Multiple Autonomous Agents
Directory of Open Access Journals (Sweden)
Debabrata Atta
2010-01-01
Full Text Available This paper presents a motion control strategy for a rigid and constraint consistent formation that can be modeled by a directed graph whose each vertex represents individual agent kinematics and each of directed edges represents distance constraints maintained by an agent, called follower, to its neighbouring agent. A rigid and constraint consistent graph is called persistent graph. A persistent graph is minimally persistent if it is persistent, and no edge can be removed without losing its persistence. An acyclic (free of cycles in its sensing pattern minimally persistent graph of Leader-Follower structure has been considered here which can be constructed from an initial Leader-Follower seed (initial graph with two vertices, one is Leader and another one is First Follower and one edge in between them is directed towards Leader by Henneberg sequence (a procedure of growing a graph containing only vertex additions. A set of nonlinear optimization-based decentralized control laws for mobile autonomous point agents in two dimensional plane have been proposed. An infinitesimal deviation in formation shape created continuous motion of Leader is compensated by corresponding continuous motion of other agents fulfilling the shortest path criteria.
Output Feedback Control of Electro-Hydraulic Cylinder Drives using the Twisting Algorithm
DEFF Research Database (Denmark)
Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.
2014-01-01
contributions in literature. This paper considers the twisting algorithm when applied directly for output feedback control, and with the design based on a reduced order model representation of an arbitrary valve driven hydraulic cylinder drive. The consequence of implementing such a controller with the well......This paper discusses the utilization of the so-called twisting algorithm when applied in output feedback position control schemes for electro-hydraulic cylinder drives. The twisting controller was the first second order sliding controller ever introduced, and can structure-wise be considered...... feedback controller may be successfully applied to hydraulic valve driven cylinder drives, with performance being on the level with a conventional surface based first order sliding mode controller....
Stochastic Control of Multi-Scale Networks: Modeling, Analysis and Algorithms
2014-10-20
correlation, protocol behavior (e.g., retransmissions), and network congestion ; and statistically analyzed the properties of LRD traffic from empirical data...traffic correlation, protocol behavior (e.g., retransmissions), and network congestion ; and statistically analyzed the properties of LRD traffic...Maximization in Wireless Networks, IEEE Transactions on Vehicular Technology, (07 2011): 0. doi: 10.1109/TVT.2011.2157544 Sugumar Murugesan, Philip
Controller tuning based on optimization algorithms of a novel spherical rolling robot
Energy Technology Data Exchange (ETDEWEB)
Sadegjian, Rasou [Dept. of Electrical, Biomedical, and Mechatronics Engineering, Qazvin Branch, Islamic Azad University, QazvinI (Iran, Islamic Republic of); Masouleh, Mehdi Tale [Human and Robot Interaction Laboratory, Faculty of New Sciences and Technologies, University of Tehran, Tehran (Iran, Islamic Republic of)
2016-11-15
This study presents the construction process of a novel spherical rolling robot and control strategies that are used to improve robot locomotion. The proposed robot drive mechanism is constructed based on a combination of the pendulum and wheel drive mechanisms. The control model of the proposed robot is developed, and the state space model is calculated based on the obtained control model. Two control strategies are defined to improve the synchronization performance of the proposed robot motors. The proportional-derivative and proportional-integral-derivative controllers are designed based on the pole placement method. The proportional-integral-derivative controller leads to a better step response than the proportional-derivative controller. The controller parameters are tuned with genetic and differential evaluation algorithms. The proportional-integral-derivative controller which is tuned based on the differential evaluation algorithm leads to a better step response than the proportional-integral-derivative controller that is tuned based on genetic algorithm. Fuzzy logics are used to reduce the robot drive mechanism motors synchronizing process time to the end of achieving a high-performance controller. The experimental implementation results of fuzzy-proportional-integral-derivative on the proposed spherical rolling robot resulted in a desirable synchronizing performance in a short time.
Controller tuning based on optimization algorithms of a novel spherical rolling robot
International Nuclear Information System (INIS)
Sadegjian, Rasou; Masouleh, Mehdi Tale
2016-01-01
This study presents the construction process of a novel spherical rolling robot and control strategies that are used to improve robot locomotion. The proposed robot drive mechanism is constructed based on a combination of the pendulum and wheel drive mechanisms. The control model of the proposed robot is developed, and the state space model is calculated based on the obtained control model. Two control strategies are defined to improve the synchronization performance of the proposed robot motors. The proportional-derivative and proportional-integral-derivative controllers are designed based on the pole placement method. The proportional-integral-derivative controller leads to a better step response than the proportional-derivative controller. The controller parameters are tuned with genetic and differential evaluation algorithms. The proportional-integral-derivative controller which is tuned based on the differential evaluation algorithm leads to a better step response than the proportional-integral-derivative controller that is tuned based on genetic algorithm. Fuzzy logics are used to reduce the robot drive mechanism motors synchronizing process time to the end of achieving a high-performance controller. The experimental implementation results of fuzzy-proportional-integral-derivative on the proposed spherical rolling robot resulted in a desirable synchronizing performance in a short time
Congestive Heart Failure and Central Sleep Apnea.
Sands, Scott A; Owens, Robert L
2016-03-01
Congestive heart failure (CHF) is among the most common causes of admission to hospitals in the United States, especially in those over age 65. Few data exist regarding the prevalence CHF of Cheyne-Stokes respiration (CSR) owing to congestive heart failure in the intensive care unit (ICU). Nevertheless, CSR is expected to be highly prevalent among those with CHF. Treatment should focus on the underlying mechanisms by which CHF increases loop gain and promotes unstable breathing. Few data are available to determine prevalence of CSR in the ICU, or how CSR might affect clinical management and weaning from mechanical ventilation. Copyright © 2016 Elsevier Inc. All rights reserved.
Control and monitoring of On-line Trigger Algorithms using gaucho
Van Herwijnen, Eric
2005-01-01
In the LHCb experiment, the trigger decisions are computed by Gaudi (the LHCb software framework) algorithms running on an event filter farm of around 2000 PCs. The control and monitoring of these algorithms has to be integrated in the overall experiment control system (ECS). To enable and facilitate this integration Gaucho, the GAUdi Component Helping Online, was developed. Gaucho consists of three parts: a C++ package integrated with Gaudi, the communications package DIM, and a set of PVSS panels and libraries. PVSS is a commercial SCADA system chosen as toolkit and framework for the LHCb controls system. The C++ package implements monitor service interface (IMonitorSvc) following the Gaudi specifications, with methods to declare variables and histograms for monitoring. Algorithms writers use them to indicate which quantities should be monitored. Since the interface resides in the GaudiKernel the code does not need changing if the monitoring services are not present. The Gaudi main job implements a state ma...
3 x 3 free-space optical router based on crossbar network and its control algorithm
Hou, Peipei; Sun, Jianfeng; Yu, Zhou; Lu, Wei; Wang, Lijuan; Liu, Liren
2015-08-01
A 3 × 3 free-space optical router, which comprises optical switches and polarizing beam splitter (PBS) and based on crossbar network, is proposed in this paper. A control algorithm for the 3 × 3 free-space optical router is also developed to achieve rapid control without rearrangement. In order to test the performance of the network based on 3 × 3 free-space optical router and that of the algorithm developed for the optical router, experiments are designed. The experiment results show that the interconnection network based on the 3 × 3 free-space optical router has low cross talk, fast connection speed. Under the control of the algorithm developed, a non-block and real free interconnection network is obtained based on the 3 × 3 free-space optical router we proposed.
Dynamic traffic assignment : genetic algorithms approach
1997-01-01
Real-time route guidance is a promising approach to alleviating congestion on the nations highways. A dynamic traffic assignment model is central to the development of guidance strategies. The artificial intelligence technique of genetic algorithm...
Directory of Open Access Journals (Sweden)
Gimazov Ruslan
2018-01-01
Full Text Available The paper considers the issue of supplying autonomous robots by solar batteries. Low efficiency of modern solar batteries is a critical issue for the whole industry of renewable energy. The urgency of solving the problem of improved energy efficiency of solar batteries for supplying the robotic system is linked with the task of maximizing autonomous operation time. Several methods to improve the energy efficiency of solar batteries exist. The use of MPPT charge controller is one these methods. MPPT technology allows increasing the power generated by the solar battery by 15 – 30%. The most common MPPT algorithm is the perturbation and observation algorithm. This algorithm has several disadvantages, such as power fluctuation and the fixed time of the maximum power point tracking. These problems can be solved by using a sufficiently accurate predictive and adaptive algorithm. In order to improve the efficiency of solar batteries, autonomous power supply system was developed, which included an intelligent MPPT charge controller with the fuzzy logic-based perturbation and observation algorithm. To study the implementation of the fuzzy logic apparatus in the MPPT algorithm, in Matlab/Simulink environment, we developed a simulation model of the system, including solar battery, MPPT controller, accumulator and load. Results of the simulation modeling established that the use of MPPT technology had increased energy production by 23%; introduction of the fuzzy logic algorithm to MPPT controller had greatly increased the speed of the maximum power point tracking and neutralized the voltage fluctuations, which in turn reduced the power underproduction by 2%.
A new home energy management algorithm with voltage control in a smart home environment
International Nuclear Information System (INIS)
Elma, Onur; Selamogullari, Ugur Savas
2015-01-01
Energy management in electrical systems is one of the important issues for energy efficiency and future grid systems. Energy management is defined as a HEM (home energy management) on the residential consumer side. The HEM system plays a key role in residential demand response applications. In this study, a new HEM algorithm is proposed for smart home environments to reduce peak demand and increase the energy efficiency. The proposed algorithm includes VC (voltage control) methodology to reduce the power consumption of residential appliances so that the shifting of appliances is minimized. The results of the survey are used to produce representative load profiles for a weekday and for a weekend. Then, case studies are completed to test the proposed HEM algorithm in reducing the peak demand in the house. The main aim of the proposed HEM algorithm is to minimize the number of turned-off appliances to decrease demand so that the customer comfort is maximized. The smart home laboratory at Yildiz Technical University, Istanbul, Turkey is used in case studies. Experimental results show that the proposed HEM algorithm reduces the peak demand by 17.5% with the voltage control and by 38% with both the voltage control and the appliance shifting. - Highlights: • A new HEM (home energy management) algorithm is proposed. • Voltage control in the HEM is introduced as a solution for peak load reduction. • Customer comfort is maximized by minimizing the number of turned-off appliances. • The proposed HEM algorithm is experimentally validated at a smart home laboratory. • A survey is completed to produce typical load profiles of a Turkish family.
Adaptive Neural Network Algorithm for Power Control in Nuclear Power Plants
International Nuclear Information System (INIS)
Husam Fayiz, Al Masri
2017-01-01
The aim of this paper is to design, test and evaluate a prototype of an adaptive neural network algorithm for the power controlling system of a nuclear power plant. The task of power control in nuclear reactors is one of the fundamental tasks in this field. Therefore, researches are constantly conducted to ameliorate the power reactor control process. Currently, in the Department of Automation in the National Research Nuclear University (NRNU) MEPhI, numerous studies are utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems and genetic algorithms) to enhance the performance, safety, efficiency and reliability of nuclear power plants. In particular, a study of an adaptive artificial intelligent power regulator in the control systems of nuclear power reactors is being undertaken to enhance performance and to minimize the output error of the Automatic Power Controller (APC) on the grounds of a multifunctional computer analyzer (simulator) of the Water-Water Energetic Reactor known as Vodo-Vodyanoi Energetichesky Reaktor (VVER) in Russian. In this paper, a block diagram of an adaptive reactor power controller was built on the basis of an intelligent control algorithm. When implementing intelligent neural network principles, it is possible to improve the quality and dynamic of any control system in accordance with the principles of adaptive control. It is common knowledge that an adaptive control system permits adjusting the controller’s parameters according to the transitions in the characteristics of the control object or external disturbances. In this project, it is demonstrated that the propitious options for an automatic power controller in nuclear power plants is a control system constructed on intelligent neural network algorithms. (paper)
Sum-of-squares-based fuzzy controller design using quantum-inspired evolutionary algorithm
Yu, Gwo-Ruey; Huang, Yu-Chia; Cheng, Chih-Yung
2016-07-01
In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi-Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used.
Fuzzy algorithms to generate level controllers for nuclear power plant steam generators
International Nuclear Information System (INIS)
Moon, Byung Soo; Park, Jae Chang; Kim, Dong Hwa; Kim, Byung Koo
1993-01-01
In this paper, we present two sets of fuzzy algorithms for the steam generater level control; one for the high power operations where the flow error is available and the other for the low power operations where the flow error is not available. These are converted to a PID type controller for the high power case and to a quadratic function form of a controller for the low power case. These controllers are implemented on the Compact Nuclear Simulator at Korea Atomic Energy Research Institute and tested by a set of four simulation experiments for each. For both cases, the results show that the total variation of the level error and of the flow error are about 50% of those by the PI controllers with about one half of the control action. For the high power case, this is mainly due to the fact that a combination of two PD type controllers in the velocity algorithm form rather than a combination of two PI type controllers in the position algorithm form is used. For the low power case, the controller is essentially a PID type with a very small integral component where the average values for the derivative component input and for the controller output are used. (Author)
Optimization of Aero Engine Acceleration Control in Combat State Based on Genetic Algorithms
Li, Jie; Fan, Ding; Sreeram, Victor
2012-03-01
In order to drastically exploit the potential of the aero engine and improve acceleration performance in the combat state, an on-line optimized controller based on genetic algorithms is designed for an aero engine. For testing the validity of the presented control method, detailed joint simulation tests of the designed controller and the aero engine model are performed in the whole flight envelope. Simulation test results show that the presented control algorithm has characteristics of rapid convergence speed, high efficiency and can fully exploit the acceleration performance potential of the aero engine. Compared with the former controller, the designed on-line optimized controller (DOOC) can improve the security of the acceleration process and greatly enhance the aero engine thrust in the whole range of the flight envelope, the thrust increases an average of 8.1% in the randomly selected working states. The plane which adopts DOOC can acquire better fighting advantage in the combat state.
International Nuclear Information System (INIS)
Machnes, S.; Sander, U.; Glaser, S. J.; Schulte-Herbrueggen, T.; Fouquieres, P. de; Gruslys, A.; Schirmer, S.
2011-01-01
For paving the way to novel applications in quantum simulation, computation, and technology, increasingly large quantum systems have to be steered with high precision. It is a typical task amenable to numerical optimal control to turn the time course of pulses, i.e., piecewise constant control amplitudes, iteratively into an optimized shape. Here, we present a comparative study of optimal-control algorithms for a wide range of finite-dimensional applications. We focus on the most commonly used algorithms: GRAPE methods which update all controls concurrently, and Krotov-type methods which do so sequentially. Guidelines for their use are given and open research questions are pointed out. Moreover, we introduce a unifying algorithmic framework, DYNAMO (dynamic optimization platform), designed to provide the quantum-technology community with a convenient matlab-based tool set for optimal control. In addition, it gives researchers in optimal-control techniques a framework for benchmarking and comparing newly proposed algorithms with the state of the art. It allows a mix-and-match approach with various types of gradients, update and step-size methods as well as subspace choices. Open-source code including examples is made available at http://qlib.info.
DC Voltage Droop Control Implementation in the AC/DC Power Flow Algorithm: Combinational Approach
DEFF Research Database (Denmark)
Akhter, F.; Macpherson, D.E.; Harrison, G.P.
2015-01-01
of operational flexibility, as more than one VSC station controls the DC link voltage of the MTDC system. This model enables the study of the effects of DC droop control on the power flows of the combined AC/DC system for steady state studies after VSC station outages or transient conditions without needing...... to use its complete dynamic model. Further, the proposed approach can be extended to include multiple AC and DC grids for combined AC/DC power flow analysis. The algorithm is implemented by modifying the MATPOWER based MATACDC program and the results shows that the algorithm works efficiently....
Chaotic queue-based genetic algorithm for design of a self-tuning fuzzy logic controller
Saini, Sanju; Saini, J. S.
2012-11-01
This paper employs a chaotic queue-based method using logistic equation in a non-canonical genetic algorithm for optimizing the performance of a self-tuning Fuzzy Logic Controller, used for controlling a nonlinear double-coupled system. A comparison has been made with a standard canonical genetic algorithm implemented on the same plant. It has been shown that chaotic queue-method brings an improvement in the performance of the FLC for wide range of set point changes by a more profound initial population spread in the search space.
He, Huaguang; Li, Taoshen; Feng, Luting; Ye, Jin
2017-07-15
Different from the traditional wired network, the fundamental cause of transmission congestion in wireless ad hoc networks is medium contention. How to utilize the congestion state from the MAC (Media Access Control) layer to adjust the transmission rate is core work for transport protocol design. However, recent works have shown that the existing cross-layer congestion detection solutions are too complex to be deployed or not able to characterize the congestion accurately. We first propose a new congestion metric called frame transmission efficiency (i.e., the ratio of successful transmission delay to the frame service delay), which describes the medium contention in a fast and accurate manner. We further present the design and implementation of RECN (ECN and the ratio of successful transmission delay to the frame service delay in the MAC layer, namely, the frame transmission efficiency), a general supporting scheme that adjusts the transport sending rate through a standard ECN (Explicit Congestion Notification) signaling method. Our method can be deployed on commodity switches with small firmware updates, while making no modification on end hosts. We integrate RECN transparently (i.e., without modification) with TCP on NS2 simulation. The experimental results show that RECN remarkably improves network goodput across multiple concurrent TCP flows.
Genetic Algorithm Based PID Controller Tuning Approach for Continuous Stirred Tank Reactor
A. Jayachitra; R. Vinodha
2014-01-01
Genetic algorithm (GA) based PID (proportional integral derivative) controller has been proposed for tuning optimized PID parameters in a continuous stirred tank reactor (CSTR) process using a weighted combination of objective functions, namely, integral square error (ISE), integral absolute error (IAE), and integrated time absolute error (ITAE). Optimization of PID controller parameters is the key goal in chemical and biochemical industries. PID controllers have narrowed down the operating r...
Computational issues in alternating projection algorithms for fixed-order control design
DEFF Research Database (Denmark)
Beran, Eric Bengt; Grigoriadis, K.
1997-01-01
Alternating projection algorithms have been introduced recently to solve fixed-order controller design problems described by linear matrix inequalities and non-convex coupling rank constraints. In this work, an extensive numerical experimentation using proposed benchmark fixed-order control design...... examples is used to indicate the computational efficiency of the method. These results indicate that the proposed alternating projections are effective in obtaining low-order controllers for small and medium order problems...
An Overview of the Automated Dispatch Controller Algorithms in the System Advisor Model (SAM)
Energy Technology Data Exchange (ETDEWEB)
DiOrio, Nicholas A [National Renewable Energy Lab. (NREL), Golden, CO (United States)
2017-11-22
Three automatic dispatch modes have been added to the battery model within the System Adviser Model. These controllers have been developed to perform peak shaving in an automated fashion, providing users with a way to see the benefit of reduced demand charges without manually programming a complicated dispatch control. A flexible input option allows more advanced interaction with the automated controller. This document will describe the algorithms in detail and present brief results on its use and limitations.
DEFF Research Database (Denmark)
Meng, Lexuan; Dragicevic, Tomislav; Roldan Perez, Javier
2016-01-01
Distributed control methods based on consensus algorithms have become popular in recent years for microgrid (MG) systems. These kinds of algorithms can be applied to share information in order to coordinate multiple distributed generators within a MG. However, stability analysis becomes a challen......Distributed control methods based on consensus algorithms have become popular in recent years for microgrid (MG) systems. These kinds of algorithms can be applied to share information in order to coordinate multiple distributed generators within a MG. However, stability analysis becomes...... in the communication network, continuous-time methods can be inaccurate for this kind of dynamic study. Therefore, this paper aims at modeling a complete DC MG using a discrete-time approach in order to perform a sensitivity analysis taking into account the effects of the consensus algorithm. To this end......, a generalized modeling method is proposed and the influence of key control parameters, the communication topology and the communication speed are studied in detail. The theoretical results obtained with the proposed model are verified by comparing them with the results obtained with a detailed switching...
International Nuclear Information System (INIS)
Crawford, Kevan C.; Sandquist, Gary M.
1990-01-01
The emphasis of this work is the development and implementation of an automatic control philosophy which uses the classical operational philosophies as a foundation. Three control algorithms were derived based on various simplifying assumptions. Two of the algorithms were tested in computer simulations. After realizing the insensitivity of the system to the simplifications, the most reduced form of the algorithms was implemented on the computer control system at the University of Utah (UNEL). Since the operational philosophies have a higher priority than automatic control, they determine when automatic control may be utilized. Unlike the operational philosophies, automatic control is not concerned with component failures. The object of this philosophy is the movement of absorber rods to produce a requested power. When the current power level is compared to the requested power level, an error may be detected which will require the movement of a control rod to correct the error. The automatic control philosophy adds another dimension to the classical operational philosophies. Using this philosophy, normal operator interactions with the computer would be limited only to run parameters such as power, period, and run time. This eliminates subjective judgements, objective judgements under pressure, and distractions to the operator and insures the reactor will be operated in a safe and controlled manner as well as providing reproducible operations
International Nuclear Information System (INIS)
Ahn, Myunghoon; Kim, Woogoon; Yim, Hyeongsoon
2016-01-01
The PI (Proportional plus Integral) controller, which is the essential functional block in control systems, can automatically perform the stable control of an important plant process while reducing the steady state error and improving the transient response. However, if the received input PV (Process Variable) is not normal due to input channel trouble, it will be difficult to control the system automatically. For this reason, many control systems are implemented to change the operation mode from automatic to manual mode in the PI controller when the failed input PV is detected. If the PI controller is in automatic mode for all the time, the control signal varies as the change of the input PV is continuously reflected in the control algorithm. In the other cases, since the controller changes into the manual mode at t=0, the control signal is fixed at the last PI controller output and thus the feedback control is not performed anymore until the operator takes an action such as the operation mode change. As a result of analysis and simulations for the controller’s operation modes in all the cases of input channel trouble, we discovered that it is more appropriate to maintain the automatic mode despite the bad quality in the PV. Therefore, we improved the control system algorithm reflecting the analysis results for the operator’s convenience and the stability of a control system
Energy Technology Data Exchange (ETDEWEB)
Ahn, Myunghoon; Kim, Woogoon; Yim, Hyeongsoon [KEPCO Engineering and Construction Co., Deajeon (Korea, Republic of)
2016-10-15
The PI (Proportional plus Integral) controller, which is the essential functional block in control systems, can automatically perform the stable control of an important plant process while reducing the steady state error and improving the transient response. However, if the received input PV (Process Variable) is not normal due to input channel trouble, it will be difficult to control the system automatically. For this reason, many control systems are implemented to change the operation mode from automatic to manual mode in the PI controller when the failed input PV is detected. If the PI controller is in automatic mode for all the time, the control signal varies as the change of the input PV is continuously reflected in the control algorithm. In the other cases, since the controller changes into the manual mode at t=0, the control signal is fixed at the last PI controller output and thus the feedback control is not performed anymore until the operator takes an action such as the operation mode change. As a result of analysis and simulations for the controller’s operation modes in all the cases of input channel trouble, we discovered that it is more appropriate to maintain the automatic mode despite the bad quality in the PV. Therefore, we improved the control system algorithm reflecting the analysis results for the operator’s convenience and the stability of a control system.
Fuzzy Tracking and Control Algorithm for an SSVEP-Based BCI System
Directory of Open Access Journals (Sweden)
Yeou-Jiunn Chen
2016-09-01
Full Text Available Subjects with amyotrophic lateral sclerosis (ALS consistently experience decreasing quality of life because of this distinctive disease. Thus, a practical brain-computer interface (BCI application can effectively help subjects with ALS to participate in communication or entertainment. In this study, a fuzzy tracking and control algorithm is proposed for developing a BCI remote control system. To represent the characteristics of the measured electroencephalography (EEG signals after visual stimulation, a fast Fourier transform is applied to extract the EEG features. A self-developed fuzzy tracking algorithm quickly traces the changes of EEG signals. The accuracy and stability of a BCI system can be greatly improved by using a fuzzy control algorithm. Fifteen subjects were asked to attend a performance test of this BCI system. The canonical correlation analysis (CCA was adopted to compare the proposed approach, and the average recognition rates are 96.97% and 94.49% for proposed approach and CCA, respectively. The experimental results showed that the proposed approach is preferable to CCA. Overall, the proposed fuzzy tracking and control algorithm applied in the BCI system can profoundly help subjects with ALS to control air swimmer drone vehicles for entertainment purposes.
Real time driver information for congestion management.
2015-07-01
Traffic demand in the U.S. has grown substantially over the past few years because of the increase in population and : urbanization in large cities. This causes traffic congestion to spread out over U.S. highways and arterials, and subsequently : lea...
Measuring accessibility and congestion in Accra
DEFF Research Database (Denmark)
Møller-Jensen, Lasse; Kofie, Richard Y.; Allotey, Albert N.M.
2012-01-01
Based on extensive gps-measurements, the paper addresses the level of intra-urban accessibility and provides indications of the level of congestion in Accra, Ghana. Traffic flows within the urban area are analyzed with respect to speed, time-of-day, direction, road type and land cover type. The s...... and less during off-peak hours. Delays are frequently found within the inner fringe areas. The paper discusses the methodological potentials and barriers for applying gps tracklog points for analysing traffic flows within an urban road network........ The speed information is extrapolated to cover the total mapped urban road net¬work with time- and direction-specific data. A series of time-distance maps are created using network analysis to illustrate the level of accessibility at different times of the day and at different directions relative...... to the city centre. Peak hour traffic speeds are compared with off-peak levels and theoretical free-flow estimations to provide an indica-tion of the level of congestion. It is found that the core areas are somewhat congested during the day period, while the fringe areas are more congested during peak hours...
Update in cardiomyopathies and congestive heart failure
Directory of Open Access Journals (Sweden)
The Heart Hospital, London, UK and Monaldi Hospital, Naples, Italy
2012-05-01
Full Text Available This abstract book contains four reports and all abstracts presented to the Joint Meeting: Update in cardiomyopathies and congestive heart failure, 22-23 September 2011 - Naples, Italy, endorsed by the Working Group on Myocardial and Pericardial Diseases (WG 21 of the European Society of Cardiology (ESC.
International Nuclear Information System (INIS)
Vilkov, N.Ya.; Kryukov, Yu.V.; Cheshun, A.V.
2001-01-01
When elaborating software for the standard algorithms of the information support of the efficient control (keeping) of water chemistry operation (WCO) at the NPP power units one introduces an approach when the systems of chemical control are realized as the systems of quality control of in-loop physical and chemical processes gathering force in the course of time. Elaboration of algorithms to proceed data of the operational chemical control seeks for elaboration of the statistic procedures to detect anomalies of the processes at the early stages of their development more efficient in contrast to the standard procedures of control. The introduced procedure is used in the demonstration model of the system for diagnostics of some typical reasons of violation of the first circuit WCO of WWER-1000 power units [ru
A robust controller design method for feedback substitution schemes using genetic algorithms
Energy Technology Data Exchange (ETDEWEB)
Trujillo, Mirsha M; Hadjiloucas, Sillas; Becerra, Victor M, E-mail: s.hadjiloucas@reading.ac.uk [Cybernetics, School of Systems Engineering, University of Reading, RG6 6AY (United Kingdom)
2011-08-17
Controllers for feedback substitution schemes demonstrate a trade-off between noise power gain and normalized response time. Using as an example the design of a controller for a radiometric transduction process subjected to arbitrary noise power gain and robustness constraints, a Pareto-front of optimal controller solutions fulfilling a range of time-domain design objectives can be derived. In this work, we consider designs using a loop shaping design procedure (LSDP). The approach uses linear matrix inequalities to specify a range of objectives and a genetic algorithm (GA) to perform a multi-objective optimization for the controller weights (MOGA). A clonal selection algorithm is used to further provide a directed search of the GA towards the Pareto front. We demonstrate that with the proposed methodology, it is possible to design higher order controllers with superior performance in terms of response time, noise power gain and robustness.
AN ALGORITHM OF ADAPTIVE TORQUE CONTROL IN INJECTOR INTERNAL COMBUSTION ENGINE
Directory of Open Access Journals (Sweden)
D. N. Gerasimov
2015-07-01
Full Text Available Subject of Research. Internal combustion engine as a plant is a highly nonlinear complex system that works mostly in dynamic regimes in the presence of noise and disturbances. A number of engine characteristics and parameters is not known or known approximately due to the complex structure and multimode operating of the engine. In this regard the problem of torque control is not trivial and motivates the use of modern techniques of control theory that give the possibility to overcome the mentioned problems. As a consequence, a relatively simple algorithm of adaptive torque control of injector engine is proposed in the paper. Method. Proposed method is based on nonlinear dynamic model with parametric and functional uncertainties (static characteristics which are suppressed by means of adaptive control algorithm with single adjustable parameter. The algorithm is presented by proportional control law with adjustable feedback gain and provides the exponential convergence of the control error to the neighborhood of zero equilibrium. It is shown that the radius of the neighborhood can be arbitrary reduced by the change of controller design parameters. Main Results. A dynamical nonlinear model of the engine has been designed for the purpose of control synthesis and simulation of the closed-loop system. The parameters and static functions of the model are identified with the use of data aquired during Federal Test Procedure (USA of Chevrolet Tahoe vehicle with eight cylinders 5,7L engine. The algorithm of adaptive torque control is designed, and the properties of the closed-loop system are analyzed with the use of Lyapunov functions approach. The closed-loop system operating is verified by means of simulation in the MatLab/Simulink environment. Simulation results show that the controller provides the boundedness of all signals and convergence of the control error to the neighborhood of zero equilibrium despite significant variations of engine speed. The
Zamani, Abbasali; Barakati, S Masoud; Yousofi-Darmian, Saeed
2016-09-01
Load-frequency control is one of the most important issues in power system operation. In this paper, a Fractional Order PID (FOPID) controller based on Gases Brownian Motion Optimization (GBMO) is used in order to mitigate frequency and exchanged power deviation in two-area power system with considering governor saturation limit. In a FOPID controller derivative and integrator parts have non-integer orders which should be determined by designer. FOPID controller has more flexibility than PID controller. The GBMO algorithm is a recently introduced search method that has suitable accuracy and convergence rate. Thus, this paper uses the advantages of FOPID controller as well as GBMO algorithm to solve load-frequency control. However, computational load will higher than conventional controllers due to more complexity of design procedure. Also, a GBMO based fuzzy controller is designed and analyzed in detail. The performance of the proposed controller in time domain and its robustness are verified according to comparison with other controllers like GBMO based fuzzy controller and PI controller that used for load-frequency control system in confronting with model parameters variations. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Benjamin M. Cowan
2013-04-01
Full Text Available We describe a modification to the finite-difference time-domain algorithm for electromagnetics on a Cartesian grid which eliminates numerical dispersion error in vacuum for waves propagating along a grid axis. We provide details of the algorithm, which generalizes previous work by allowing 3D operation with a wide choice of aspect ratio, and give conditions to eliminate dispersive errors along one or more of the coordinate axes. We discuss the algorithm in the context of laser-plasma acceleration simulation, showing significant reduction—up to a factor of 280, at a plasma density of 10^{23} m^{-3}—of the dispersion error of a linear laser pulse in a plasma channel. We then compare the new algorithm with the standard electromagnetic update for laser-plasma accelerator stage simulations, demonstrating that by controlling numerical dispersion, the new algorithm allows more accurate simulation than is otherwise obtained. We also show that the algorithm can be used to overcome the critical but difficult challenge of consistent initialization of a relativistic particle beam and its fields in an accelerator simulation.
Li, Ning; Cürüklü, Baran; Bastos, Joaquim; Sucasas, Victor; Fernandez, Jose Antonio Sanchez; Rodriguez, Jonathan
2017-05-04
The aim of the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) project is to make autonomous underwater vehicles (AUVs), remote operated vehicles (ROVs) and unmanned surface vehicles (USVs) more accessible and useful. To achieve cooperation and communication between different AUVs, these must be able to exchange messages, so an efficient and reliable communication network is necessary for SWARMs. In order to provide an efficient and reliable communication network for mission execution, one of the important and necessary issues is the topology control of the network of AUVs that are cooperating underwater. However, due to the specific properties of an underwater AUV cooperation network, such as the high mobility of AUVs, large transmission delays, low bandwidth, etc., the traditional topology control algorithms primarily designed for terrestrial wireless sensor networks cannot be used directly in the underwater environment. Moreover, these algorithms, in which the nodes adjust their transmission power once the current transmission power does not equal an optimal one, are costly in an underwater cooperating AUV network. Considering these facts, in this paper, we propose a Probabilistic Topology Control (PTC) algorithm for an underwater cooperating AUV network. In PTC, when the transmission power of an AUV is not equal to the optimal transmission power, then whether the transmission power needs to be adjusted or not will be determined based on the AUV's parameters. Each AUV determines their own transmission power adjustment probability based on the parameter deviations. The larger the deviation, the higher the transmission power adjustment probability is, and vice versa. For evaluating the performance of PTC, we combine the PTC algorithm with the Fuzzy logic Topology Control (FTC) algorithm and compare the performance of these two algorithms. The simulation results have demonstrated that the PTC is efficient at reducing the transmission power
Directory of Open Access Journals (Sweden)
Ning Li
2017-05-01
Full Text Available The aim of the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs project is to make autonomous underwater vehicles (AUVs, remote operated vehicles (ROVs and unmanned surface vehicles (USVs more accessible and useful. To achieve cooperation and communication between different AUVs, these must be able to exchange messages, so an efficient and reliable communication network is necessary for SWARMs. In order to provide an efficient and reliable communication network for mission execution, one of the important and necessary issues is the topology control of the network of AUVs that are cooperating underwater. However, due to the specific properties of an underwater AUV cooperation network, such as the high mobility of AUVs, large transmission delays, low bandwidth, etc., the traditional topology control algorithms primarily designed for terrestrial wireless sensor networks cannot be used directly in the underwater environment. Moreover, these algorithms, in which the nodes adjust their transmission power once the current transmission power does not equal an optimal one, are costly in an underwater cooperating AUV network. Considering these facts, in this paper, we propose a Probabilistic Topology Control (PTC algorithm for an underwater cooperating AUV network. In PTC, when the transmission power of an AUV is not equal to the optimal transmission power, then whether the transmission power needs to be adjusted or not will be determined based on the AUV’s parameters. Each AUV determines their own transmission power adjustment probability based on the parameter deviations. The larger the deviation, the higher the transmission power adjustment probability is, and vice versa. For evaluating the performance of PTC, we combine the PTC algorithm with the Fuzzy logic Topology Control (FTC algorithm and compare the performance of these two algorithms. The simulation results have demonstrated that the PTC is efficient at reducing the
How Congested Jakarta is? Perception of Jakarta’s Citizen on Traffic Congestion
Directory of Open Access Journals (Sweden)
Muhammad Halley Yudhistira
2017-11-01
Full Text Available This paper aims to reveal the behavior and perception of Jakarta’s citizens on traffic congestion in Jakarta. Although this approach is somewhat well-developed in behavioral science, its utilization in urban economics study, is still limited. Detecting the traffic congestion and its cause mainly relies on physical (engineering methods, i.e V/C ratio. Here, we define the traffic congestion through two variables; ordinal traffic congestion perception and proportion of expected travel time to perceived travel time. Using a non-probabilistic sampling survey held in one of densest business district in Jakarta called Sudirman-Thamrin Golden Triangle Area; the estimation results show that travel behavior plays a major role in affecting travel time perceptions.
The economic cost of traffic congestion in Florida.
2010-08-01
Traffic congestion in the U.S. is bad and getting worse, and it is expensive. Appropriate solutions to this problem require appropriate information. A comprehensive and accurate analysis of congestion costs is a critical tool for planning and impleme...
Statewide GIS mapping of recurring congestion corridors : final report.
2009-07-01
Recurring congestion occurs when travel demand reaches or exceeds the available roadway : capacity. This project developed an interactive geographic information system (GIS) map of the : recurring congestion corridors (labeled herein as hotspots) in ...
Research on Segmentation Monitoring Control of IA-RWA Algorithm with Probe Flow
Ren, Danping; Guo, Kun; Yao, Qiuyan; Zhao, Jijun
2018-04-01
The impairment-aware routing and wavelength assignment algorithm with probe flow (P-IA-RWA) can make an accurate estimation for the transmission quality of the link when the connection request comes. But it also causes some problems. The probe flow data introduced in the P-IA-RWA algorithm can result in the competition for wavelength resources. In order to reduce the competition and the blocking probability of the network, a new P-IA-RWA algorithm with segmentation monitoring-control mechanism (SMC-P-IA-RWA) is proposed. The algorithm would reduce the holding time of network resources for the probe flow. It segments the candidate path suitably for the data transmitting. And the transmission quality of the probe flow sent by the source node will be monitored in the endpoint of each segment. The transmission quality of data can also be monitored, so as to make the appropriate treatment to avoid the unnecessary probe flow. The simulation results show that the proposed SMC-P-IA-RWA algorithm can effectively reduce the blocking probability. It brings a better solution to the competition for resources between the probe flow and the main data to be transferred. And it is more suitable for scheduling control in the large-scale network.
A Biologically-Inspired Power Control Algorithm for Energy-Efficient Cellular Networks
Directory of Open Access Journals (Sweden)
Hyun-Ho Choi
2016-03-01
Full Text Available Most of the energy used to operate a cellular network is consumed by a base station (BS, and reducing the transmission power of a BS can therefore afford a substantial reduction in the amount of energy used in a network. In this paper, we propose a distributed transmit power control (TPC algorithm inspired by bird flocking behavior as a means of improving the energy efficiency of a cellular network. Just as each bird in a flock attempts to match its velocity with the average velocity of adjacent birds, in the proposed algorithm, each mobile station (MS in a cell matches its rate with the average rate of the co-channel MSs in adjacent cells by controlling the transmit power of its serving BS. We verify that this bio-inspired TPC algorithm using a local rate-average process achieves an exponential convergence and maximizes the minimum rate of the MSs concerned. Simulation results show that the proposed TPC algorithm follows the same convergence properties as the flocking algorithm and also effectively reduces the power consumption at the BSs while maintaining a low outage probability as the inter-cell interference increases; in so doing, it significantly improves the energy efficiency of a cellular network.
Comparison of Algorithms for the Optimal Location of Control Valves for Leakage Reduction in WDNs
Directory of Open Access Journals (Sweden)
Enrico Creaco
2018-04-01
Full Text Available The paper presents the comparison of two different algorithms for the optimal location of control valves for leakage reduction in water distribution networks (WDNs. The former is based on the sequential addition (SA of control valves. At the generic step Nval of SA, the search for the optimal combination of Nval valves is carried out, while containing the optimal combination of Nval − 1 valves found at the previous step. Therefore, only one new valve location is searched for at each step of SA, among all the remaining available locations. The latter algorithm consists of a multi-objective genetic algorithm (GA, in which valve locations are encoded inside individual genes. For the sake of consistency, the same embedded algorithm, based on iterated linear programming (LP, was used inside SA and GA, to search for the optimal valve settings at various time slots in the day. The results of applications to two WDNs show that SA and GA yield identical results for small values of Nval. When this number grows, the limitations of SA, related to its reduced exploration of the research space, emerge. In fact, for higher values of Nval, SA tends to produce less beneficial valve locations in terms of leakage abatement. However, the smaller computation time of SA may make this algorithm preferable in the case of large WDNs, for which the application of GA would be overly burdensome.
International Nuclear Information System (INIS)
Moon, Jin Woo; Yoon, Younju; Jeon, Young-Hoon; Kim, Sooyoung
2017-01-01
Highlights: • Initial ANN model was developed for predicting the time to the setback temperature. • Initial model was optimized for producing accurate output. • Optimized model proved its prediction accuracy. • ANN-based algorithms were developed and tested their performance. • ANN-based algorithms presented superior thermal comfort or energy efficiency. - Abstract: In this study, a temperature control algorithm was developed to apply a setback temperature predictively for the cooling system of a residential building during occupied periods by residents. An artificial neural network (ANN) model was developed to determine the required time for increasing the current indoor temperature to the setback temperature. This study involved three phases: development of the initial ANN-based prediction model, optimization and testing of the initial model, and development and testing of three control algorithms. The development and performance testing of the model and algorithm were conducted using TRNSYS and MATLAB. Through the development and optimization process, the final ANN model employed indoor temperature and the temperature difference between the current and target setback temperature as two input neurons. The optimal number of hidden layers, number of neurons, learning rate, and moment were determined to be 4, 9, 0.6, and 0.9, respectively. The tangent–sigmoid and pure-linear transfer function was used in the hidden and output neurons, respectively. The ANN model used 100 training data sets with sliding-window method for data management. Levenberg-Marquart training method was employed for model training. The optimized model had a prediction accuracy of 0.9097 root mean square errors when compared with the simulated results. Employing the ANN model, ANN-based algorithms maintained indoor temperatures better within target ranges. Compared to the conventional algorithm, the ANN-based algorithms reduced the duration of time, in which the indoor temperature
Robotic Arm Control Algorithm Based on Stereo Vision Using RoboRealm Vision
Directory of Open Access Journals (Sweden)
SZABO, R.
2015-05-01
Full Text Available The goal of this paper is to present a stereo computer vision algorithm intended to control a robotic arm. Specific points on the robot joints are marked and recognized in the software. Using a dedicated set of mathematic equations, the movement of the robot is continuously computed and monitored with webcams. Positioning error is finally analyzed.
DEFF Research Database (Denmark)
Endelt, Benny Ørtoft; Volk, Wolfram
2013-01-01
, there is a number of obstacles which need to be addressed before an industrial implementation is possible, e.g. the proposed control algorithms are often limited by the ability to sample process data with both sufficient accuracy and robustness - this lack of robust sampling technologies is one of the main barriers...
Software and hardware platform for testing of Automatic Generation Control algorithms
Directory of Open Access Journals (Sweden)
Vasiliev Alexey
2017-01-01
Full Text Available Development and implementation of new Automatic Generation Control (AGC algorithms requires testing them on a model that adequately simulates primary energetic, information and control processes. In this article an implementation of a test platform based on HRTSim (Hybrid Real Time Simulator and SCADA CK-2007 (which is widely used by the System Operator of Russia is proposed. Testing of AGC algorithms on the test platform based on the same SCADA system that is used in operation allows to exclude errors associated with the transfer of AGC algorithms and settings from the test platform to a real power system. A power system including relay protection, automatic control systems and emergency control automatics can be accurately simulated on HRTSim. Besides the information commonly used by conventional AGC systems HRTSim is able to provide a resemblance of Phasor Measurement Unit (PMU measurements (information about rotor angles, magnitudes and phase angles of currents and voltages etc.. The additional information significantly expands the number of possible AGC algorithms so the test platform is useful in modern AGC system developing. The obtained test results confirm that the proposed system is applicable for the tasks mentioned above.
Dynamic model to tune a climate control algorithm in pig houses with natural ventilation
Klooster, van 't C.E.; Bontsema, J.; Salomons, L.
1995-01-01
Algorithms for environmental control in livestock buildings have to be tuned for optimum response of actuators. For tuning, a simple, but dynamic, climate model for a pig house was formulated and validated to predict the
environmental changes in a pig house with natural ventilation under varying
The design of control algorithm for automatic start-up model of HWRR
International Nuclear Information System (INIS)
Guo Wenqi
1990-01-01
The design of control algorithm for automatic start-up model of HWRR (Heavy Water Research Reactor), the calculation of μ value and the application of digital compensator are described. Finally The flow diagram of the automatic start-up and digital compensator program for HWRR are given
An implicit adaptation algorithm for a linear model reference control system
Mabius, L.; Kaufman, H.
1975-01-01
This paper presents a stable implicit adaptation algorithm for model reference control. The constraints for stability are found using Lyapunov's second method and do not depend on perfect model following between the system and the reference model. Methods are proposed for satisfying these constraints without estimating the parameters on which the constraints depend.