Optimal admission control algorithms for scheduling burst data in CDMA multimedia systems
Kwok, YK; Lau, VKN
2001-01-01
3rd generation mobile systems are mostly based on the wideband CDMA platform to support high bit rate packet data services. One important component to offer packet data service in CDMA is a burst admission control algorithm. In this paper, we propose and study a novel jointly adaptive burst admission algorithm, namely the jointly adaptive burst admission-spatial dimension algorithm (JABA-SD) to effectively allocate valuable resources in wideband CDMA systems to burst requests. In the physical...
A New Self-Adapting Admission Control Algorithm for Differential Service in Web Clusters
LIU An-feng; CHEN Zhi-gang; LONG Guo-ping
2004-01-01
A new admission control algorithm considering the network self-similar access characteristics is proposed.Taking advantage of the mathematical model of the network traffic admission control which can effectively overcome the self-similar characteristics of the network requests, through the scheduling of the differential service queue based on priority while at the same time taking into account various factors including access characteristics of requests, load information, etc, smoothness of the admission control is ensured by the algorithm proposed in this paper.We design a non-linear self-adapting control algorithm by introducing an exponential admission function, thus overcomes the negative aspects introduced by static threshold parameters.Simulation results show that the scheme proposed in this paper can effectively improve the resource utilization of the clusters, while at the same time protecting the service with high priority.Our simulation results also show that this algorithm can improve system stability and reliability too.
A COMBINED ADMISSION CONTROL ALGORITHM WITH DA PROTOCOL FOR SATELLITE ATM NETWORKS
Lu Rong; Cao Zhigang
2006-01-01
Admission control is an important strategy for Quality of Service (QoS) provisioning in Asynchronous Transfer Mode (ATM) networks. Based on a control-theory model of resources on-Demand Allocation (DA) protocol, the paper studies the effect of the protocol on the statistical characteristics of network traffic,and proposes a combined connection admission control algorithm with the DA protocol to achieve full utilization of link resources in satellite communication systems. The proposed algorithm is based on the cross-layer-design approach. Theoretical analysis and system simulation results show that the proposed algorithm can admit more connections within certain admission thresholds than one that does not take into account the DA protocol. Thus, the proposed algorithm can increase admission ratio of traffic sources for satellite ATM networks and improve satellite link utilization.
A Study of Equivalence of Measurement-Based Admission Control Algorithms
GUI Zhi-bo; ZHOU Li-chao
2003-01-01
Measurement-Based Admission Control (MBAC) algorithms, as opposed to the more conservative worstcase parameter-based approach, are expressly designed to achieve high levels of network utilization for the controlledload service, a real-time service with very relaxed service guarantee. Most researchers studying MBAC algorithms(MBAC's) have focused primarily on the design of the Admission Control Equations (ACE's) using a variety of principled and ad hoc motivations. In this paper, we prove theoretically that the ACE's, even though derived and motivated in quite different ways, are equivalent by tuning the adjustable parameters of MBAC's. We also use simulations to confirm our work. The simulation results show that MBAC's may have the same utilization for a given packet loss rate through tuning the relevant parameters.
Algorithms for Deterministic Call Admission Control of Pre-stored VBR Video Streams
Christos Tryfonas
2009-08-01
Full Text Available We examine the problem of accepting a new request for a pre-stored VBR video stream that has been smoothed using any of the smoothing algorithms found in the literature. The output of these algorithms is a piecewise constant-rate schedule for a Variable Bit-Rate (VBR stream. The schedule guarantees that the decoder buffer does not overflow or underflow. The problem addressed in this paper is the determination of the minimal time displacement of each new requested VBR stream so that it can be accommodated by the network and/or the video server without overbooking the committed traffic. We prove that this call-admission control problem for multiple requested VBR streams is NP-complete and inapproximable within a constant factor, by reducing it from the VERTEX COLOR problem. We also present a deterministic morphology-sensitive algorithm that calculates the minimal time displacement of a VBR stream request. The complexity of the proposed algorithm along with the experimental results we provide indicate that the proposed algorithm is suitable for real-time determination of the time displacement parameter during the call admission phase.
Call Admission Control Algorithm for pre-stored VBR video streams
Tryfonas, Christos; Mehler, Andrew; Skiena, Steven
2008-01-01
We examine the problem of accepting a new request for a pre-stored VBR video stream that has been smoothed using any of the smoothing algorithms found in the literature. The output of these algorithms is a piecewise constant-rate schedule for a Variable Bit-Rate (VBR) stream. The schedule guarantees that the decoder buffer does not overflow or underflow. The problem addressed in this paper is the determination of the minimal time displacement of each new requested VBR stream so that it can be accomodated by the network and/or the video server without overbooking the committed traffic. We prove that this call-admission control problem for multiple requested VBR streams is NP-complete and inapproximable within a constant factor, by reducing it from the VERTEX COLOR problem. We also present a deterministic morphology-sensitive algorithm that calculates the minimal time displacement of a VBR stream request. The complexity of the proposed algorithm make it suitable for real-time determination of the time displacem...
GUIZhibo; ZHOULichao
2005-01-01
The advantage of Measurement-based admission control algorithms (MBACs) is that they are able to improve network utilization for the controlled-load service. Most researchers have focused primarily on designs of the Admission control equations (ACEs) of MBACs using a variety of principled and ad hoc motivations. In this paper, six typical MBACs, namely MS, HB, TP, TO, TE and MC algorithms, are discussed. First, we have proven analytically that the ACEs of TE and MC have the same structural form as the ACEs of the other four MBACs above. Second, through formal analysis we have theoretically proven that the ACEs of TE and MC, even though they are derived and motivated in quite different ways, are equivalent to the other four MBACs by tuning the adjustable parameters of MBACs. Finally, we have used also simulations to confirm our work.
Hong, X.; Xiao, Y; Ni, Q
2006-01-01
Call admission control in a wireless cell in a personal communication system (PCS) can be modeled as an M/M/C/C queuing system with m classes of users. Semi-Markov Decision Process (SMDP) can be used to optimize channel utilization with upper bounds on handoff blocking probabilities as Quality of Service constraints. However, this method is too time-consuming and therefore it fails when state space and action space are large. In this paper, we apply a genetic algorithm approach to address the...
Admission Control Techniques for UMTS System
P. Kejik
2010-09-01
Full Text Available Universal mobile telecommunications system (UMTS is one of the 3rd generation (3G cell phone technologies. The capacity of UMTS is interference limited. Radio resources management (RRM functions are therefore used. They are responsible for supplying optimum coverage, ensuring efficient use of physical resources, and providing the maximum planned capacity. This paper deals with admission control techniques for UMTS. An own UMTS simulation program and several versions of proposed admission control algorithms are presented in this paper. These algorithms are based on fuzzy logic and genetic algorithms. The performance of algorithms is verified via simulations.
Call Admission Control in Mobile Wireless
Goril, J.; Dobos, L.
2002-01-01
Some problems related to wireless network access are discussed in the article. Special attention is paid to Medium Access Control and Call Admission Control. Both have direct impact on communication link accession. While the first one dictates how to, the second one decides who can access the link. The problems with wireless medium access are mentioned and requirements on MAC protocols are named. Also need for CAC algorithms is illustrated and simple functional example is proposed. Finally, t...
Implementation av Network Admission Control
Sandqvist, Mattias; Johansson, Robert
2007-01-01
This examination work is about implementation of Cisco Systems Network Admission Control (NAC) within a leading IT-company in region of Jönköping. NAC is a technique that is used for securing the internal network from the inside. NAC can verify that the client who connects to the network has the latest antivirus updates and latest operative system hotfixes. Clients who don’t meet the criteria can be placed in quarantine VLAN where they only have access to the update servers. There are also fu...
A NEW ADMISSION CONTROL APPROACH BASED ON PREDICTION
Lu Kaining; Jin Zhigang; Zou Jun
2002-01-01
Admission control plays an important role in providing QoS to network users. Motivated by the measurement-based admission control algorithm, this letter proposed a new admission control approach for integrated service packet network based on traffic prediction. In the letter, FARIMA(p, d, q) models in the admission control algorithm is deployed. A method to simplify the FARIMA model fitting procedure and hence to reduce the time of traffic modeling and prediction is suggested. The feasibility-study experiments show that FARIMA models which have less number of parameters can be used to model and predict actual traffic on quite a large time scale. Simulation results validate the promising approach.
On channel-adaptive multiple burst admission control for mobile computing based on wideband CDMA
Lau, VKN; Kwok, YK
2001-01-01
Mobile computing systems built using third generation wireless standards are mostly based on the wideband CDMA platform to support high bit rate packet data services. One important component offering packet data service in CDMA is a burst admission control algorithm. We formulate the multiple-burst admission control problem as an integer programming problem, which induces our novel jointly adaptive burst admission algorithm, called the jointly adaptive burst admission-spatial dimension algori...
Efficient Admission Control for Next Generation Cellular Networks
Ramkumar, Venkata; Stefan, Andrei Lucian; Nielsen, Rasmus Hjorth; Prasad, Neeli R.; Prasad, Ramjee
This paper proposes a novel efficient admission control (AC) algorithm, which guarantees quality of service (QoS) for new users while maintaining QoS for existing users and also increases the number of users admitted in to the system. To guarantee the QoS, a Markov based modeling of the queue in...
An Intelligent Call Admission Control Decision Mechanism for Wireless Networks
S., Ramesh Babu H; S, Satyanarayana P
2010-01-01
The Call admission control (CAC) is one of the Radio Resource Management (RRM) techniques plays instrumental role in ensuring the desired Quality of Service (QoS) to the users working on different applications which have diversified nature of QoS requirements. This paper proposes a fuzzy neural approach for call admission control in a multi class traffic based Next Generation Wireless Networks (NGWN). The proposed Fuzzy Neural Call Admission Control (FNCAC) scheme is an integrated CAC module that combines the linguistic control capabilities of the fuzzy logic controller and the learning capabilities of the neural networks .The model is based on Recurrent Radial Basis Function Networks (RRBFN) which have better learning and adaptability that can be used to develop the intelligent system to handle the incoming traffic in the heterogeneous network environment. The proposed FNCAC can achieve reduced call blocking probability keeping the resource utilisation at an optimal level. In the proposed algorithm we have c...
Call Admission Control in Mobile Cellular Networks
Ghosh, Sanchita
2013-01-01
Call Admission Control (CAC) and Dynamic Channel Assignments (DCA) are important decision-making problems in mobile cellular communication systems. Current research in mobile communication considers them as two independent problems, although the former greatly depends on the resulting free channels obtained as the outcome of the latter. This book provides a solution to the CAC problem, considering DCA as an integral part of decision-making for call admission. Further, current technical resources ignore movement issues of mobile stations and fluctuation in network load (incoming calls) in the control strategy used for call admission. In addition, the present techniques on call admission offers solution globally for the entire network, instead of considering the cells independently. CAC here has been formulated by two alternative approaches. The first approach aimed at handling the uncertainty in the CAC problem by employing fuzzy comparators. The second approach is concerned with formulation of CAC ...
Admission Control of VL in AFDX Under HRT Constraints
ZHOU Qiang; QU Zhenliang; LIN Hengqing
2011-01-01
Avionics full duplex switched ethernet (AFDX) is a switched interconnection technology developed to provide reliable data exchange with strong data transmission time guarantees in internal communication of the spacecraft or aircraft. Virtual link (VL) is an important concept of AFDX to meet quality of service (QoS) requirements in terms of end-to-end message deadlines. A VL admission control algorithm in AFDX network under hard real-time (HRT) constraints is studied. Based on the scheduling principle of AFDX protocol, a packet scheduling scheme under HRT constraints is proposed, and after that an efficient VL admission control algorithm is presented. Analytical proof that the algorithm can effectively determine whether VL should be admitted is given. Finally simulative examples are presented to promote the conclusion.
Lau, VKN; Kwok, YK
2001-01-01
In our recent study, we have formulated the burst admission control problem for wideband CDMA systems as an integer programming problem. In this paper, we propose and analyze the performance of a novel burst admission technique, called the multiple-burst admission-spatial dimension algorithm (MBA-SD) to judiciously allocate the previous channels in wideband CDMA systems to burst requests. Both the forward link and the reverse link burst requests are considered and the system is simulated by d...
TCP-Call Admission Control Interaction in Multiplatform Space Architectures
Georgios Theodoridis
2007-06-01
Full Text Available The implementation of efficient call admission control (CAC algorithms is useful to prevent congestion and guarantee target quality of service (QoS. When TCP protocol is adopted, some inefficiencies can arise due to the peculiar evolution of the congestion window. The development of cross-layer techniques can greatly help to improve efficiency and flexibility for wireless networks. In this frame, the present paper addresses the introduction of TCP feedback into the CAC procedures in different nonterrestrial wireless architectures. CAC performance improvement is shown for different space-based architectures, including both satellites and high altitude platform (HAP systems.
Development of a validation algorithm for 'present on admission' flagging
Cheng Diana
2009-12-01
Full Text Available Abstract Background The use of routine hospital data for understanding patterns of adverse outcomes has been limited in the past by the fact that pre-existing and post-admission conditions have been indistinguishable. The use of a 'Present on Admission' (or POA indicator to distinguish pre-existing or co-morbid conditions from those arising during the episode of care has been advocated in the US for many years as a tool to support quality assurance activities and improve the accuracy of risk adjustment methodologies. The USA, Australia and Canada now all assign a flag to indicate the timing of onset of diagnoses. For quality improvement purposes, it is the 'not-POA' diagnoses (that is, those acquired in hospital that are of interest. Methods Our objective was to develop an algorithm for assessing the validity of assignment of 'not-POA' flags. We undertook expert review of the International Classification of Diseases, 10th Revision, Australian Modification (ICD-10-AM to identify conditions that could not be plausibly hospital-acquired. The resulting computer algorithm was tested against all diagnoses flagged as complications in the Victorian (Australia Admitted Episodes Dataset, 2005/06. Measures reported include rates of appropriate assignment of the new Australian 'Condition Onset' flag by ICD chapter, and patterns of invalid flagging. Results Of 18,418 diagnosis codes reviewed, 93.4% (n = 17,195 reflected agreement on status for flagging by at least 2 of 3 reviewers (including 64.4% unanimous agreement; Fleiss' Kappa: 0.61. In tests of the new algorithm, 96.14% of all hospital-acquired diagnosis codes flagged were found to be valid in the Victorian records analysed. A lower proportion of individual codes was judged to be acceptably flagged (76.2%, but this reflected a high proportion of codes used Conclusion An indicator variable about the timing of occurrence of diagnoses can greatly expand the use of routinely coded data for hospital quality
The admissible portfolio selection problem with transaction costs and an improved PSO algorithm
Chen, Wei; Zhang, Wei-Guo
2010-05-01
In this paper, we discuss the portfolio selection problem with transaction costs under the assumption that there exist admissible errors on expected returns and risks of assets. We propose a new admissible efficient portfolio selection model and design an improved particle swarm optimization (PSO) algorithm because traditional optimization algorithms fail to work efficiently for our proposed problem. Finally, we offer a numerical example to illustrate the proposed effective approaches and compare the admissible portfolio efficient frontiers under different constraints.
Power Control Technique for Efficient Call Admission Control in Advanced Wirless Networks
Ch. Sreenivasa Rao
2012-06-01
Full Text Available In 4G networks, call admission control techniques have been proposed to provide Quality of Service (QoS in a network by restricting the access to network resources. Power control is essential in call admission control in order to provide fair access to all users, improve battery lifetime and system performance. But the existing call admission control algorithms rarely consider the power controlling techniques in the handoff process for different traffic classes. In this paper, we propose to develop a power controlled call admission control scheme for handoff in the advanced wireless networks. The incoming call measures the initial interference on it and then the base station starts transmitting the packets to the new call. The new call is rejected when the interference reaches a threshold value.Whenever an existing call meets the power constraint, the transmit power is decremented based on thetraffic class and incoming call obtains this information by monitoring the interference received on it. Theconvergence of the power control algorithm is checked and the power levels of all incoming calls areadjusted. From our simulation results we prove that this power control technique provides efficienthandoff in the 4G networks by increasing the throughput and reducing the delay of the existing users.
Admission Control and Interference Management in Dynamic Spectrum Access Networks
Jorge Martinez-Bauset
2010-01-01
Full Text Available We study two important aspects to make dynamic spectrum access work in practice: the admission policy of secondary users (SUs to achieve a certain degree of quality of service and the management of the interference caused by SUs to primary users (PUs. In order to limit the forced termination probability of SUs, we evaluate the Fractional Guard Channel reservation scheme to give priority to spectrum handovers over new arrivals. We show that, contrary to what has been proposed, the throughput of SUs cannot be maximized by configuring the reservation parameter. We also study the interference caused by SUs to PUs. We propose and evaluate different mechanisms to reduce the interference, which are based on simple spectrum access algorithms for both PUs and SUs and channel repacking algorithms for SUs. Numerical results show that the reduction can be of one order of magnitude or more with respect to the random access case. Finally, we propose an adaptive admission control scheme that is able to limit simultaneously the forced termination probability of SUs and what we define as the probability of interference. Our scheme does not require any configuration parameters beyond the probability objectives. Besides, it is simple to implement and it can operate with any arrival process and distribution of the session duration.
Integrated Proactive Admission Control Technique For both UDP And TCP Traffic Flows
Lakshmanan Senthilkumar
2007-02-01
Full Text Available Real time traffic adopting UDP at the transport layer needs some quality of service. It is offered through an admission control scheme. This paper adopts one such scheme which is extended for elastic traffics adopting TCP at the transport layer. The proposed scheme operates on reserving network resources on a proactive manner. It is based on the principle of telephone networks Erlang-B model. The blocking probability measured is used as a flow admission decision parameter. The effectiveness of the proposed admission control algorithm is determined here through simulation. It offers a fair admission rate to both UDP and TCP traffic flows. It also results in a better bottleneck link utilization at a comparatively lower overhead traffic.
Improving Experience-Based Admission Control through Traffic Type Awareness
Jens Milbrandt; Michael Menth; Jan Junker
2007-01-01
Experience-based admission control (EBAC) is a hybrid approach combining the classical parameter-based and measurement-based admission control. EBAC calculates an appropriate overbooking factor used to overbook link capacities with resource reservations in packet-switched networks. This overbooking factor correlates with the average peak-to-mean rate ratio of all admitted traffic flows on the link. So far, a single overbooking factor is calculated for the entire traffic aggregate. In this pap...
A lexicographic approach to constrained MDP admission control
Panfili, Martina; Pietrabissa, Antonio; Oddi, Guido; Suraci, Vincenzo
2016-02-01
This paper proposes a reinforcement learning-based lexicographic approach to the call admission control problem in communication networks. The admission control problem is modelled as a multi-constrained Markov decision process. To overcome the problems of the standard approaches to the solution of constrained Markov decision processes, based on the linear programming formulation or on a Lagrangian approach, a multi-constraint lexicographic approach is defined, and an online implementation based on reinforcement learning techniques is proposed. Simulations validate the proposed approach.
SIMULATION MODELS OF CALL ADMISSION CONTROL SCHEMES USING GPSS
Vassilya ABDULOVA
2014-01-01
Full Text Available In cellular wireless networks, a variety of channel allocation schemes have been developed for achieving high capacity with minimal interference. The choice of channel allocation scheme impacts the performance of the system, particularly as how calls are managed when a mobile user is handed off from one cell to another. Call Admission Control schemes take into account the effect of handoffs in the performance of the system, particularly call blocking probability and call dropping probability. In this study, we present simulation models and programs of some popular Call Admission Control schemes using GPSS simulation tool.
Karipidis, Eleftherios; Sidiropoulos, Nicholas; Tassiulas, Leandros
2008-01-01
The joint power control and base station (BS) assignment problem is considered under Quality-of-Service (QoS) constraints. If a feasible solution exists, the problem can be efficiently solved using existing distributed algorithms. Infeasibility is often encountered in practice, however, which brings up the issue of optimal admission control. The joint problem is NP-hard, yet important for QoS provisioning and bandwidth-efficient operation of existing and emerging cellular and overlay/underlay...
Admission control in multiservice IP networks : architectural issues and trends
Lima, Solange; Carvalho, Paulo; Freitas, Vasco
2007-01-01
The trend toward the integration of current and emerging applications and services in the Internet has launched new challenges regarding service deployment and management. Within service management, admission control (AC) has been recognized as a convenient mechanism to keep services under controlled load and assure the required QoS levels, bringing consistency to the services offered. In this context, this article discusses the role of AC in multiservice IP networks and surveys current and r...
Measurement Based Admission Control Methods in IP Networks
Erik Chromy
2013-09-01
Full Text Available Trends in telecommunications show that customers require still more and more bandwidth. If the telecommunication operators want to be successful, they must invest a lot of money to their infrastructure and they must ensure required quality of service. The telecommunication operators would devote to development in this area. The article deals with quality of service in IP networks. Problems of quality of service can be solved through admission control methods based on measurements. These admission control methods take care of control of incoming traffic load. New flow can be accepted only if needed quality of service is ensured for it and without quality of service breach causing of already accepted flows. In the article were made description of simulations and results of simulations for Voice over IP, constant bit rate and video sources. Simulations were realized in Network simulator 2 environment. These simulations were evaluated on the base of some parameters such as: estimated bandwidth, utilization and loss rate.
Cross-Layer Connection Admission Control Policies for Packetized Systems
SHENG, WEI; Blostein, Steven
2010-01-01
In summary, this chapter provides a framework for joint optimization of packet-switched multiple-antenna systems across physical, packet and connection levels. We extend the existing CAC policies in packet-switched networks to more general cases, where the SINR may vary quickly relative to the connection time, as encountered in multiple antenna base stations. Compared with the CAC policy for circuit-switched networks, the proposed connection admission control policy allows dynamical allocatio...
Maximally Stabilizing Admission Control Policy for a Dynamical Queue
Savla, Ketan
2009-01-01
In this paper, we consider the following stability problem for a novel dynamical queue. Independent and identical tasks arrive for a queue at a deterministic rate. The server spends deterministic state-dependent times to service these tasks, where the server state is governed by its utilization history through a simple dynamical model. Inspired by empirical laws for human performance as a function of mental arousal, we let the service time be related to the server state by a continuous convex function. We consider an admission control architecture which regulates task entry into service. The objective in this paper is to design such admission control policies that can stabilize the dynamical queue for the maximum possible arrival rate, where the queue is said to be stable if the number of tasks awaiting service does not grow unbounded over time. First, we prove an upper bound on the maximum stabilizable arrival rate for any admission control policy by postulating a notion of one-task equilibrium for the dynam...
Admission Control to Minimize Rejections and Online Set Cover with Repetitions
Alon, Noga; Gutner, Shai
2008-01-01
We study the admission control problem in general networks. Communication requests arrive over time, and the online algorithm accepts or rejects each request while maintaining the capacity limitations of the network. The admission control problem has been usually analyzed as a benefit problem, where the goal is to devise an online algorithm that accepts the maximum number of requests possible. The problem with this objective function is that even algorithms with optimal competitive ratios may reject almost all of the requests, when it would have been possible to reject only a few. This could be inappropriate for settings in which rejections are intended to be rare events. In this paper, we consider preemptive online algorithms whose goal is to minimize the number of rejected requests. Each request arrives together with the path it should be routed on. We show an $O(\\log^2 (mc))$-competitive randomized algorithm for the weighted case, where $m$ is the number of edges in the graph and $c$ is the maximum edge ca...
A QoS Provisioning Recurrent Neural Network based Call Admission Control for beyond 3G Networks
Ramesh Babu H. S.
2010-03-01
Full Text Available The Call admission control (CAC is one of the Radio Resource Management (RRM techniques that plays influential role in ensuring the desired Quality of Service (QoS to the users and applications in next generation networks. This paper proposes a fuzzy neural approach for making the call admission control decision in multi class traffic based Next Generation Wireless Networks (NGWN. The proposed Fuzzy Neural call admission control (FNCAC scheme is an integrated CAC module that combines the linguistic control capabilities of the fuzzy logic controller and the learning capabilities of the neural networks. The model is based on recurrent radial basis function networks which have better learning and adaptability that can be used to develop intelligent system to handle the incoming traffic in an heterogeneous network environment. The simulation results are optimistic and indicates that the proposed FNCAC algorithm performs better than the other two methods and the call blocking probability is minimal when compared to other two methods.
Power Admission Control with Predictive Thermal Management in Smart Buildings
Yao, Jianguo; Costanzo, Giuseppe Tommaso; Zhu, Guchuan;
2015-01-01
This paper presents a control scheme for thermal management in smart buildings based on predictive power admission control. This approach combines model predictive control with budget-schedulability analysis in order to reduce peak power consumption as well as ensure thermal comfort. First, the...... power budget with a given thermal comfort constraint is optimized through budget-schedulability analysis which amounts to solving a constrained linear programming problem. Second, the effective peak power demand is reduced by means of the optimal scheduling and cooperative operation of multiple thermal...... appliances. The performance of the proposed control scheme is assessed by simulation based on the thermal dynamics of a real eight-room office building located at Danish Technical University....
Improving Experience-Based Admission Control through Traffic Type Awareness
Jens Milbrandt
2007-04-01
Full Text Available Experience-based admission control (EBAC is a hybrid approach combining the classical parameter-based and measurement-based admission control. EBAC calculates an appropriate overbooking factor used to overbook link capacities with resource reservations in packet-switched networks. This overbooking factor correlates with the average peak-to-mean rate ratio of all admitted traffic flows on the link. So far, a single overbooking factor is calculated for the entire traffic aggregate. In this paper, we propose typespecific EBAC which provides a compound overbooking factor considering different types of traffic that subsume flows with similar peak-to-mean rate ratios. The concept can be well implemented since it does not require measurements of type-specific traffic aggregates. We give a proof of concept for this extension and compare it with the conventional EBAC approach. We show that EBAC with type-specific overbooking leads to better resource utilization under normal conditions and to faster response times for changing traffic mixes.
Optimizing Voip Using A Cross Layer Call Admission Control Scheme
Mumtaz AL-Mukhtar
2013-07-01
Full Text Available Deployingwireless campus network becomes popular in many world universities for the services that areprovided.However, it suffers from different issues such as low VoIP network capacity, network congestioneffect on VoIP QoS and WLAN multi rate issue due to linkadaptation technique. In this paper a cross layercall admission control (CCAC scheme is proposed to reduce the effects of these problems on VoWLANbased on monitoring RTCPRR(RealTime Control Protocol ReceiverReportthat provides the QoS levelfor VoIP and monitoring the MAC layer for any change in the data rate. If the QoS level degrades due toone of the aforementioned reasons, a considerable change in the packet size or the codec type will be thesolution. A wireless campus network issimulatedusing OPNET 14.5 modeler and many scenarios aremodeled to improve this proposed scheme.
UTILITY BASED SCHEDULING AND CALL ADMISSION CONTROL FOR LONG TERM EVOLUTION NETWORKS
J. Vijay Franklin
2012-01-01
Full Text Available In this study, we propose to design a call admission control algorithm which schedules the channels for Real time and non-real time users. In Long Term Evolution (LTE 3GPP Networks, several works were done on call admission control but these works rarely considers scheduling of resources to the real time and non-real time users.When the system meets traffic oriented performance degration, maximum resources are utilized for load balancing and to maintain the consistent quality. In order to avoid the channel degradation and improve the Quality of Service (QoS, the call requests are classified into New Call (NC request and Handoff Call (HC request and the type of services are classified as VoIP and video. Then based upon the Received Signal Strength (RSS value, the channel is estimated as good channel or bad channel. Resource allocation is made for VoIP users based on traffic density. Then non-VoIP users and the non-real time users are allocated resource blocks using the channel condition based marginal utility function. When there are no sufficient resources to allocate, it allocates the resources of bad channel users there by degrading their service. We have designed the network topology with G (n and B (n for representing the available good and bad channels. We investigate the performance degradation when the real time, Non real Time, video and VOIP environments based on RSS threshold value.Comparison is made with the VOS in terms of the paramenters like throughput,bandwidth,delay,fairness and rate. Our proposed method provides good performance and quality.From our simulation results we show that this admission control algorithm provides channel quality and prioritizes the handover calls over new calls which allocates resources to all kinds of users.
The Value of Service Rate Flexibility in an M/M/1 Queue with Admission Control
Dimitrakopoulos, Yiannis
2012-01-01
We consider a single server queueing system with admission control and the possibility to switch dynamically between a low and a high service rate, and examine the benefit of this service rate flexibility. We formulate a discounted Markov Decision Process model for the problem of joint admission and service control, and show that the optimal policy has a threshold structure for both controls. Regarding the benefit due to flexibility, we show that it is increasing in system congestion, and that its effect on the admission policy is to increase the admission threshold. We also derive a simple approximate condition between the admission reward and the relative cost of service rate increase, so that the service rate flexibility is beneficial. We finally show that the results extend to the expected average reward case.
QoS awared power and admission controls based on non-cooperative game theory in wireless networks
2008-01-01
In order to better accommodate heterogeneous quality of service (QoS) in wireless networks, an algorithm called QeS-aware power and admission controls (QAPAC) is proposed. The system is modeled as u non- cooperative game where the users adjust their transmit powers to maximize the utility, thus restraining the interferences. By using adaptive utility functions and tunable pricing parameters according to QoS levels, this algorithm can well meet different QoS reqniremcnts and improve system capacity compared with those that ignore the QoS differ- ences.
QoS awared power and admission controls based on non-cooperative game theory in wireless networks
无
2008-01-01
In order to better accommodate heterogeneous quality of service (QoS) in wireless networks, an algorithm called QoS-aware power and admission controls (QAPAC) is proposed. The system is modeled as a non-cooperative game where the users adjust their transmit powers to maximize the utility, thus restraining the interferences. By using adaptive utility functions and tunable pricing parameters according to QoS levels, this algorithm can well meet different QoS requirements and improve system capacity compared w...
A framework of call admission control procedures for integrated services mobile wireless networks
This paper presents a general framework for a wide range of call admission control (CAC) algorithms. For several CAC schemes, which are a subset of this general framework, an analytical performance evaluation is presented for a multi-traffic mobile wireless network. These CAC algorithms consider a variety of mechanisms to prioritize traffic in an attempt to support different levels of quality of service (QoS) for different types of calls. These mechanisms include dividing the handoff traffic into more than one class and using guard channels or allowing channel splitting to admit more handoff calls. Other mechanisms aimed at adding priority for handoff calls consider employing queuing of handoff calls or dynamically reducing the number lower priority calls. Furthermore our analysis relaxes the typically used assumptions of equal channel holding time and equal resource usage for voice and data calls. The main contribution of this paper is the development of an analytical model for each of the three CAC algorithms specified in this study. In addition to the call blocking and termination probabilities which are usually cited as the performance metrics, in this work we derive and evaluate other metrics that not have be considered by the previous work such as the average queue length, the average queue residency, and the time-out probability for handoff calls. We also develop a simulation tool to test and verify our results. Finally, we present numerical examples to demonstrate the performance of the proposed CAG algorithms and we show that analytical and simulation results are in total agreement. (author)
A Policy-Based Admission Control Scheme for Voice over IP Networks
Sami Alwakeel; Agung Prasetijo
2009-01-01
Problem statement: In Voice Over IP (VOIP) network, when more calls are admitted to the network, more voice packet traffic is created. Since bandwidth is always limited, this may result network congestion and/or may affect voice quality. Thus, we needed a mechanism for improving the Quality of Service (QoS) by controlling VOIP calls admission. Approach: Given a specified bandwidth and a constant background data rate, we attempted to explore the effect of Open Window and Leaky Bucket admission...
AMPLE Using BGP Based Traffic Engineering with Admission Control Algorithm
Dr.V. Palanisamy#1 , K. Gowri
2013-01-01
Traffic engineering is an important mechanism for Internet network providers seeking to optimize network performance and traffic delivery. Routing optimization plays a key role in traffic engineering, finding efficient routes so as to achieve the desired network performance. BGP is the de facto protocol used for inter-autonomous system routing in the Internet. BGP has been proven to be secure, efficient, scalable, and robust. In proposed introduced AMPLE – an efficient traffic engineering and...
Continuous non contacting control of the degree of admission of filler rods
In laboratory tests a method was found to control continuously and non-contacting the degree of admission of filler rods. Behind the filling station the absorption of the ionizing radiation of a 90Sr beta source is measured. After successful tests with the laboratory equipment on the manufacturing machine of filler rods a prototype plant was constructed. The calibration is made by setting the measuring value of the empty filler rod equal to 0% and the measuring value of the optimum degree of admission equal to 100%. Between these two joints a scale is calculated so that to each measuring value a degree of admission can be assigned. The measuring time is 1 s. The limits of the allowable degrees of admission are freely adjustable. The construction of the plant is described. (authors)
DSTATCOM Control Algorithms: A Review
Ambarnath Banerji
2012-06-01
Full Text Available The concept that an inverter can be used as a generalized impedance converter to realize either inductive or capacitive reactance has been widely used to mitigate power quality issues of distribution networks. One such device is the DSTATCOM which is connected in shunt at the load end. The heart of the DSTATCOM is a converter. The control algorithm of the converter is very important. It causes the converter to address the power quality problems in efficient manner. This paper discusses the various control algorithms of the converter. The manners in which the power quality issues are mitigated by the converter are also explored. Simulations of the control algorithms are made on MATLAB platform to ascertain the effectiveness of each control method for power quality mitigation.
Subcubic Control Flow Analysis Algorithms
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...
SERVICE-AWARE BASED FUZZY ADMISSION CONTROL SCHEME IN MULTI-SERVICE NETWORKS
Qiu Gongan; Zhang Shunyi; Liu Shidong
2007-01-01
Multi-service aggregated transmission is the direction of IP network. Providing different Quality of Service (QoS) assurance for different services has become a crucial problem in future network.Admission control is a vital function for multi-service IP network. This paper proposes a novel fuzzy admission control scheme based on coarse granularity service-aware technique. Different service has discriminative sensitivity to the same QoS characteristic parameter in general. The traffic class can be perceived by the service request parameter and the proposed QoS function. And requirements of different applications can be met by maintaining the life parameter. From simulation results, the proposed scheme shows a better QoS provisioning than those traditional fuzzy logic based methods under the same admission probability.
Seo, Dong-Chul; Torabi, Mohammad R.
2007-01-01
There has been no research linking implementation of a public smoking ban and reduced incidence of acute myocardial infarction (AMI) among nonsmoking patients. An ex post facto matched control group study was conducted to determine whether there was a change in hospital admissions for AMI among nonsmoking patients after a public smoking ban was…
FUZZY-LOGIC BASED CALL ADMISSION CONTROL FOR A HETEROGENEOUS RADIO ENVIRONMENT
Ramkumar, Venkata; Mihovska, Albena D.; Prasad, Neeli R.;
Dette dokument foreslår et nyt opkald Admission Control (CAC) algoritme, der finder forskellige typer af applikationer med forskellige QoS parametre, som en bruger og giver de nødvendige QoS til nyankomne brugere uden en forringelse af de QoS at der allerede er optaget dem. Den foreslåede CAC er ...
A service-oriented admission control strategy for class-based IP networks
Lima, Solange; Carvalho, Paulo; Freitas, Vasco
2008-01-01
The clear trend toward the integration of current and emerging applications and services in the Internet launches new demands on service deployment and management. Distributed service-oriented traffic control mechanisms, operating with minimum impact on network performance, assume a crucial role as regards controlling services quality and network resources transparently and efficiently. In this paper, we describe and specify a lightweight distributed admission control (AC) model based on ...
Cognitive interference modeling with applications in power and admission control
Mahmood, Nurul Huda
2012-10-01
One of the key design challenges in a cognitive radio network is controlling the interference generated at coexisting primary receivers. In order to design efficient cognitive radio systems and to minimize their unwanted consequences, it is therefore necessary to effectively control the secondary interference at the primary receivers. In this paper, a generalized framework for the interference analysis of a cognitive radio network where the different secondary transmitters may transmit with different powers and transmission probabilities, is presented and various applications of this interference model are demonstrated. The findings of the analytical performance analyses are confirmed through selected computer-based Monte-Carlo simulations. © 2012 IEEE.
BARTER: Behavior Profile Exchange for Behavior-Based Admission and Access Control in MANETs
Frias-Martinez, Vanessa; Stolfo, Salvatore J.; Keromytis, Angelos D.
Mobile Ad-hoc Networks (MANETs) are very dynamic networks with devices continuously entering and leaving the group. The highly dynamic nature of MANETs renders the manual creation and update of policies associated with the initial incorporation of devices to the MANET (admission control) as well as with anomaly detection during communications among members (access control) a very difficult task. In this paper, we present BARTER, a mechanism that automatically creates and updates admission and access control policies for MANETs based on behavior profiles. BARTER is an adaptation for fully distributed environments of our previously introduced BB-NAC mechanism for NAC technologies. Rather than relying on a centralized NAC enforcer, MANET members initially exchange their behavior profiles and compute individual local definitions of normal network behavior. During admission or access control, each member issues an individual decision based on its definition of normalcy. Individual decisions are then aggregated via a threshold cryptographic infrastructure that requires an agreement among a fixed amount of MANET members to change the status of the network. We present experimental results using content and volumetric behavior profiles computed from the ENRON dataset. In particular, we show that the mechanism achieves true rejection rates of 95% with false rejection rates of 9%.
A LP-RR Principle-Based Admission Control for a Mobile Network
Kumar, Vijay BP; Venkataram, Pallapa
2002-01-01
In mobile networks, the traffic fluctuation is unpredictable due to mobility and varying resource requirement of multimedia applications. Hence, it is essential to maintain traffic within the network capacity to provide service guarantees to running applications. This paper proposes an admission control (AC) scheme in a mobile cellular environment supporting hand-off and new application traffic. In the case of multimedia applications, each applications has its own distinct range of acceptable...
Huang, Qian; Huang, Yue-Cai; Ko, King-Tim; Iversen, Villy Bæk
2011-01-01
A hierarchical overlay structure is an alternative solution that integrates existing and future heterogeneous wireless networks to provide subscribers with better mobile broadband services. Traffic loss performance in such integrated heterogeneous networks is necessary for an operator's network...... dimensioning and planning. This paper investigates the computationally efficient loss performance modeling for multiservice in hierarchical heterogeneous wireless networks. A speed-sensitive call admission control (CAC) scheme is considered in our model to assign overflowed calls to appropriate tiers. This...
Control algorithms for dynamic attenuators
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
Sánchez, M.; Esteban, L.; Kornejew, P.; Hirsch, M.
2008-03-01
Mid Infrared (10,6 μm CO2 laser lines) interferometers as a plasma density diagnostic must use two-colour systems with superposed interferometers beams at different wavelengths in order to cope with mechanical vibrations and drifts. They require a highly precise phase difference measurement where all sources of error must be reduced. One of these is the cross-talk between the signals which creates nonlinear spurious periodic mixing products. The reason may be either optical or electrical crosstalk both resulting in similar perturbations of the measurement. In the TJII interferometer a post-processing algorithm is used to reduce the crosstalk in the data. This post-processing procedure is not appropriate for very long pulses, as it is the case for in new tokamak (ITER) or stellarator (W7-X) projects. In both cases an on-line reduction process is required or—even better—the unwanted signal components must be reduced in the system itself CO2 laser interferometers which as the second wavelength use the CO laser line (5,3 μm), may apply a single common detector sensitive to both wavelengths and separate the corresponding IF signals by appropriate bandpass filters. This reduces complexity of the optical arrangement and avoids a possible source of vibration induced phase noise as both signals share the same beam path. To avoid cross talk in this arrangement filtering must be appropriate. In this paper we present calculations to define the limits of crosstalk for a desired plasma density precision. A crosstalk reduction algorithm has been developed and is applied to experimental results from TJ-II pulses. Results from a single detector arrangement as under investigation for the CO2/CO laser interferometer developed for W7-X are presented.
Estimated Bandwidth Distribution with Admission Control for Enhanced QoS Multicast Routing in MANETs
P.Revathi
2009-09-01
Full Text Available Wireless networks become more widely used to support advanced services. Traditional approaches to guarantee quality of service (QoS work well only with predictable channel and network access. The Multicast transmission is a more efficient mechanism when compared to uni-casting in supporting group communication applications and hence is an important aspect of future network developments. To enable high QoS for all admitted traffic, the Admission Control monitors the wireless channel and dynamically adapts admission control decisions to enable high network utilization while preventing congestion. Mobile Adhoc networks can provide multimedia users with mobility, if efficient QoS multicast strategies were developed. In load balancing QoS Multicast Routing QMR, constant available bandwidth for the link is assumed. A cross-layer framework to support QoS multicasting is extended for more effective than QMR. The extension reflects good packet delivery ratios associated with lower control overhead and lower packet delivery delay. If minimum real-time requirements are not met, these unusable packets waste scarce bandwidth and hinder other traffic, compounding the problem. Whereas the dynamically adapted mobility with control overhead monitors the high QoS for all admitted traffic, and the bandwidth for each node is enhanced to reflect the good packet delivery ratio associated with lower control overhead and lower packet delivery delay.
Stabilizing the Richardson Algorithm by Controlling Chaos
He, Song
1996-01-01
By viewing the operations of the Richardson purification algorithm as a discrete time dynamical process, we propose a method to overcome the instability of the algorithm by controlling chaos. We present theoretical analysis and numerical results on the behavior and performance of the stabilized algorithm.
Fast Algorithm of Multivariable Generalized Predictive Control
Jin,Yuanyu; Pang,Zhonghua; Cui,Hong
2005-01-01
To avoid the shortcoming of the traditional (previous)generalized predictive control (GPC) algorithms, too large amounts of computation, a fast algorithm of multivariable generalized predictive control is presented in which only the current control actions are computed exactly on line and the rest (the future control actions) are approximately done off line. The algorithm is simple and can be used in the arbitary-dimension input arbitary-dimension output (ADIADO) linear systems. Because it dose not need solving Diophantine equation and reduces the dimension of the inverse matrix, it decreases largely the computational burden. Finally, simulation results show that the presented algorithm is effective and practicable.
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.
Dynamic admission control for differentiated quality of video in IEEE 802.11e wireless LANs
Yoon, Hayoung; Kim, JongWon
2004-10-01
In this paper, we are investigating a dynamic admission control (DAC) scheme that is designed for guaranteed wireless video transmission over the IEEE 802.11e wireless LAN (WLAN) environment. To guarantee differentiated QoS services for network-adaptive video streaming, the proposed DAC is designed to utilize the video codec's layering characteristic as well as differentiation-capability of IEEE 802.11e MAC (multiple access control). Especially in order to match the time-varying hostile wireless environment, limited wireless resources for transmission opportunities are required to be dynamically reserved, coordinated, and utilized. Proposed realization of DAC is composed with three sub modules: reservation-based call admission control (CAC), dynamic service resource allocation, and on-flow service differentiation modules. To evaluate the performance of proposed DAC, we apply it to the wireless streaming of ITU-T H.263+ streams over the IEEE 802.11e WLAN, network simulator (NS-2) based simulation results show that it achieves both acceptable receiver-side video quality and efficient resource utilization in face of network loads and channel variations.
Singular formalism and admissible control of spacecraft with rotating flexible solar array
Lu Dongning
2014-02-01
Full Text Available This paper is concerned with the attitude control of a three-axis-stabilized spacecraft which consists of a central rigid body and a flexible sun-tracking solar array driven by a solar array drive assembly. Based on the linearization of the dynamics of the spacecraft and the modal identities about the flexible and rigid coupling matrices, the spacecraft attitude dynamics is reduced to a formally singular system with periodically varying parameters, which is quite different from a spacecraft with fixed appendages. In the framework of the singular control theory, the regularity and impulse-freeness of the singular system is analyzed and then admissible attitude controllers are designed by Lyapunov’s method. To improve the robustness against system uncertainties, an H∞ optimal control is designed by optimizing the H∞ norm of the system transfer function matrix. Comparative numerical experiments are performed to verify the theoretical results.
HUMAN-SIMULATING VEHICLE STEERING CONTROL ALGORITHM
XU Youchun; LI Keqiang; CHANG Ming; CHEN Jun
2006-01-01
A new vehicle steering control algorithm is presented. Unlike the traditional methods do,the algorithm uses a sigmoid function to describe the principle of the human driver's steering strategy.Based on this function, a human simulating vehicle steering model, human-simulating steering control(HS) algorithm is designed. In order to improve the adaptability to different environments, a parameter adaptive adjustment algorithm is presented. This algorithm can online modify the value of the key parameters of the HS real time. HS controller is used on a vehicle equipped with computer vision system and computer controlled steering actuator system, the result from the automatic vehicle steering experiment shows that the HS algorithm gives good performance at different speed, even at the maximum speed of 172 km/h.
Performance of a Two-Level Call Admission Control Scheme for DS-CDMA Wireless Networks
Abraham O. Fapojuwo
2007-11-01
Full Text Available We propose a two-level call admission control (CAC scheme for direct sequence code division multiple access (DS-CDMA wireless networks supporting multimedia traffic and evaluate its performance. The first-level admission control assigns higher priority to real-time calls (also referred to as class 0 calls in gaining access to the system resources. The second level admits nonreal-time calls (or class 1 calls based on the resources remaining after meeting the resource needs for real-time calls. However, to ensure some minimum level of performance for nonreal-time calls, the scheme reserves some resources for such calls. The proposed two-level CAC scheme utilizes the delay-tolerant characteristic of non-real-time calls by incorporating a queue to temporarily store those that cannot be assigned resources at the time of initial access. We analyze and evaluate the call blocking, outage probability, throughput, and average queuing delay performance of the proposed two-level CAC scheme using Markov chain theory. The analytic results are validated by simulation results. The numerical results show that the proposed two-level CAC scheme provides better performance than the single-level CAC scheme. Based on these results, it is concluded that the proposed two-level CAC scheme serves as a good solution for supporting multimedia applications in DS-CDMA wireless communication systems.
Performance of a Two-Level Call Admission Control Scheme for DS-CDMA Wireless Networks
Fapojuwo Abraham O
2007-01-01
Full Text Available We propose a two-level call admission control (CAC scheme for direct sequence code division multiple access (DS-CDMA wireless networks supporting multimedia traffic and evaluate its performance. The first-level admission control assigns higher priority to real-time calls (also referred to as class 0 calls in gaining access to the system resources. The second level admits nonreal-time calls (or class 1 calls based on the resources remaining after meeting the resource needs for real-time calls. However, to ensure some minimum level of performance for nonreal-time calls, the scheme reserves some resources for such calls. The proposed two-level CAC scheme utilizes the delay-tolerant characteristic of non-real-time calls by incorporating a queue to temporarily store those that cannot be assigned resources at the time of initial access. We analyze and evaluate the call blocking, outage probability, throughput, and average queuing delay performance of the proposed two-level CAC scheme using Markov chain theory. The analytic results are validated by simulation results. The numerical results show that the proposed two-level CAC scheme provides better performance than the single-level CAC scheme. Based on these results, it is concluded that the proposed two-level CAC scheme serves as a good solution for supporting multimedia applications in DS-CDMA wireless communication systems.
Jung-Shyr Wu
2012-01-01
Full Text Available CAC (Call Admission Control plays a significant role in providing QoS (Quality of Service in mobile wireless networks. In addition to much research that focuses on modified Mobile IP to get better efficient handover performance, CAC should be introduced to Mobile IP-based network to guarantee the QoS for users. In this paper, we propose a CAC scheme which incorporates multiple traffic types and adjusts the admission threshold dynamically using fuzzy control logic to achieve better usage of resources. The method can provide QoS in Mobile IPv6 networks with few modifications on MAP (Mobility Anchor Point functionality and slight change in BU (Binding Update message formats. According to the simulation results, the proposed scheme presents good performance of voice and video traffic at the expenses of poor performance on data traffic. It is evident that these CAC schemes can reduce the probability of the handoff dropping and the cell overload and limit the probability of the new call blocking.
Call Admission Control performance model for Beyond 3G Wireless Networks
Babu, H S Ramesh; Satyanarayana, P S
2010-01-01
The Next Generation Wireless Networks (NGWN) will be heterogeneous in nature where the different Radio Access Technologies (RATs) operate together .The mobile terminals operating in this heterogeneous environment will have different QoS requirements to be handled by the system. These QoS requirements are determined by a set of QoS parameters. The radio resource management is one of the key challenges in NGWN. Call admission control is one of the radio resource management technique plays instrumental role in ensure the desired QoS to the users working on different applications which have diversified QoS requirements from the wireless networks . The call blocking probability is one such QoS parameter for the wireless network. For better QoS it is desirable to reduce the call blocking probability. In this customary scenario it is highly desirable to obtain analytic Performance model. In this paper we propose a higher order Markov chain based performance model for call admission control in a heterogeneous wireles...
El-Qulity, Said Ali; Mohamed, Ali Wagdy
2016-01-01
This paper proposes a nonlinear integer goal programming model (NIGPM) for solving the general problem of admission capacity planning in a country as a whole. The work aims to satisfy most of the required key objectives of a country related to the enrollment problem for higher education. The system general outlines are developed along with the solution methodology for application to the time horizon in a given plan. The up-to-date data for Saudi Arabia is used as a case study and a novel evolutionary algorithm based on modified differential evolution (DE) algorithm is used to solve the complexity of the NIGPM generated for different goal priorities. The experimental results presented in this paper show their effectiveness in solving the admission capacity for higher education in terms of final solution quality and robustness. PMID:26819583
Mitigating Handoff Call Dropping in Wireless Cellular Networks: A Call Admission Control Technique
Ekpenyong, Moses Effiong; Udoh, Victoria Idia; Bassey, Udoma James
2016-06-01
Handoff management has been an important but challenging issue in the field of wireless communication. It seeks to maintain seamless connectivity of mobile users changing their points of attachment from one base station to another. This paper derives a call admission control model and establishes an optimal step-size coefficient (k) that regulates the admission probability of handoff calls. An operational CDMA network carrier was investigated through the analysis of empirical data collected over a period of 1 month, to verify the performance of the network. Our findings revealed that approximately 23 % of calls in the existing system were lost, while 40 % of the calls (on the average) were successfully admitted. A simulation of the proposed model was then carried out under ideal network conditions to study the relationship between the various network parameters and validate our claim. Simulation results showed that increasing the step-size coefficient degrades the network performance. Even at optimum step-size (k), the network could still be compromised in the presence of severe network crises, but our model was able to recover from these problems and still functions normally.
Novel Stochastic Model for Call Admission Control in Broadband Wireless Multimedia Networks
LIUGan; ZHUGuangxi; RUANYoulin; HUZhenping; WUWeimin; WANGDesheng
2005-01-01
As the increasing demand of the capacity of cellular networks, the cell sizes have become smaller than ever, which increases the probability of handoff one may experience during a service. To ensure the calls， QoS and high channel utilization, an effective call admission control is needed urgently. The well-known Guard channel method (GCM) which works with static fashion cannotadapt to the changes in traffic pattern, whereas, SDCA mechanism proposed by S. Wu can overcome that shortcoming due to its dynamic nature. Unfortunately, it is only suitable for single-service. In this paper, we establish a novel stochastic model to study the actual system so as to avoid coping with the complex multiple dimensions stochastic problem. Two wonderful features of the model make it competent for this role. On one hand, it can turnthe multiple steps of state transition into single step ofstate transition, which is a necessary condition for ideal birth-death processes. On the other hand, it can providea simple method to compute the approximation of the call dropping probabilities for multiple services， which facilitate our estimation for the acceptance ratio vector subject to QoS requirement. As a result, we get a multi-services dynamic call admission scheme to adapt for multiple types of services in mobile wireless networks. Numerical results show that our scheme steadily satisfies the constraint on call dropping probability of multi-services while maintaining a high channel throughput.
Algorithm For Control Of Large Antenna
Hill, Robert E.
1990-01-01
Alternative position-error feedback modes provided. Modern control theory basis for computer algorithm used to control two-axis positioning of large antenna. Algorithm - incorporated into software of real-time control computer - enables rapid intertarget positioning as well as precise tracking (using one of two optional position-feedback modes) without need of human operator intervention. Control system for one axis of two-axis azimuth/elevation control system embodied mostly in software based on advanced control theory. System has linear properties of classical linear feedback controller. Performance described by bandwidth and linear error coefficients.
Large space structures control algorithm characterization
Fogel, E.
1983-01-01
Feedback control algorithms are developed for sensor/actuator pairs on large space systems. These algorithms have been sized in terms of (1) floating point operation (FLOP) demands; (2) storage for variables; and (3) input/output data flow. FLOP sizing (per control cycle) was done as a function of the number of control states and the number of sensor/actuator pairs. Storage for variables and I/O sizing was done for specific structure examples.
TFRC—IVS Flow Control Algorithm
HEKaijian; LINYaping; YANGAng
2003-01-01
This paper investigates the TCP (Trans-mission Control Protocol) friendliness of multicast video-conferencing systems. Through the analysis and simulation experiments it is shown that the slow response to network state changes and the fixed rate adjustment process lead to TCP unfriendliness in the bandwidth sharing. Therefore,this paper proposes a new TCP friendly flow control al-gorithm called TFRC-IVS flow control algorithm for the current best-effort Internet. TFRC-IVS (TCP-Friendly Rate Control--INRIA Videoconferencing System) algo-rithm utilizes TCP friendly control function derived from complex TCP model to calculate TCP friendly sending rate.Simulation results show that TFRC-IVS flow control algorithm improves the smoothness of transmission rates and converges quickly to the stable sending rate. In addi-tion, the TCP friendly control function in TFRC-IVS flow control algorithm ensures the TCP friendliness of video flows and fair bandwidth allocation with TCP flows, which the traditional static rate adjustment algorithm lacks.
AN Enhanced SINR-Based Call Admission Control in 3G Networks
Moses Ekpenyong
2011-11-01
Full Text Available This paper presents the signal-to-interference plus noise ratio (SINR-based call admission control (CAC as an effective technique that guarantees signal quality for admitted users. We propose a CAC model that admits users as long as the SINR exceeds a threshold (th SINR . To reduce blocking, we ensure that the threshold level is maintained at a lower bound (lb thSINR −, convenient to keep the blocking probability ( Pb below a maximum value ( Pb−max. We simulate the CAC model with the Java programming language and evaluate the performance of the model. Simulation results show that our CAC scheme produce the expected performance that improves the network quality.
A STUDY ON PROBE-BASED MULTICAST ADMISSION CONTROL AND ENHANCEMENT
Le Chunhui; He Jianhua; Yang Zongkai; Liu Wei
2006-01-01
To provide scalable and simple Quality of Service(QoS) mechanism for multicast services,Probe-Based Multicast Admission Control (PBMAC) scheme was proposed. In this paper, PBMAC is studied and a so-called subsequent request problem is found in PBMAC, which degrades system performance significantly when the network traffic is heavily loaded. Based on the analysis on subsequent request problem, an Enhance PBMAC (EPBMAC) scheme is proposed, in which complementary probing is devised to solve the problem. Using a new metric of normalized requested equivalent link capacity, the performance of PBMAC and EPBMAC is analyzed and evaluated. Two implementations are proposed for incremental deployment. The paper finally introduces evaluation with packet-based simulations. Both analytical and simulation results show the significant improvement in performance.
Control algorithms for autonomous robot navigation
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
Control algorithms for autonomous robot navigation
Jorgensen, C.C.
1985-09-20
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.
Congestion Control Algorithm for Resilient Packet Ring
孔红伟; 葛宁; 阮方; 冯重熙
2003-01-01
A congestion control algorithm is proposed for resilient packet ring (RPR) in this paper. In thisalgorithm, nonlinear explicit rate feedback control is used to ensure fast convergence and smooth equilibriumbehavior. The algorithm combines explicit rate control with a deficit round robin (DRR) scheduler, which notonly ensures fairness, but also avoids the implementation difficulties of explicit rate control algorithms. Thealgorithm has good features of fairness, fast convergence, smooth equilibrium, Iow queue depth, and easyimplementation. It is insensitive to the loss of congestion control packets and can adapt to a wide range of linkrates and network scales. It has solved the unbalanced traffic problem of spatial reuse protocol (SRP). Thealgorithm can be implemented on the multi-access control layer of RPR nodes to ensure fair and efficient accessof the best-effort traffic.
Study on the Class-Based Admission Control Scheme for DiffServ in MPLS Networks
李震宇; 张中兆
2003-01-01
Differentiated services (DiffServ) and MPLS are two major building blocks for providing multi-class services over IP networks. In order to respond to the need for relatively simple, coarse methods of providing different levels of service for Internet traffic, to support various types of applications and specific business requirements, the MPLS network infrastructure and the DiffServ traffic model will work together. Meanwhile, in today's environment of multiple service networks, it is necessary for the node in the networks to perform the control mechanism to guarantee various QoS. In this paper, we propose a class-based admission control scheme that is suitable for DiffServ in MPLS networks. This scheme can achieve twofold objects: reliable QoS provisioning and high resource utilization. We evaluate the proposed scheme by numerical analysis of its performance in terms of throughput, delay, and reject probability. By performing simulation, we can ensure that the proposed scheme can work efficiently to provide strict QoS guarantees.
Genetic algorithms in adaptive fuzzy control
Karr, C. Lucas; Harper, Tony R.
1992-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.
Hybrid Genetic Algorithms with Fuzzy Logic Controller
无
2001-01-01
In this paper, a new implementation of genetic algorithms (GAs) is developed for the machine scheduling problem, which is abundant among the modern manufacturing systems. The performance measure of early and tardy completion of jobs is very natural as one's aim, which is usually to minimize simultaneously both earliness and tardiness of all jobs. As the problem is NP-hard and no effective algorithms exist, we propose a hybrid genetic algorithms approach to deal with it. We adjust the crossover and mutation probabilities by fuzzy logic controller whereas the hybrid genetic algorithm does not require preliminary experiments to determine probabilities for genetic operators. The experimental results show the effectiveness of the GAs method proposed in the paper.``
Digital control algorithms for microgravity isolation systems
Sinha, A.; Wang, Y.-P.
1993-01-01
New digital control algorithms have been developed to achieve the desired transmissibility function for a microgravity isolation system. Two approaches have been presented for the controller design in the context of a single degree of freedom system for which an attractive electromagnet is used as the actuator. The relative displacement and the absolute acceleration of the mass have been used as feedback signals. The results from numerical studies are presented. It has been found that the resulting transmissibility is quite close to the desired function. Also, the maximum coil currents required by new algorithms are smaller than the maximum current demanded by the previously proposed lead/lag method.
A reliable algorithm for optimal control synthesis
Vansteenwyk, Brett; Ly, Uy-Loi
1992-01-01
In recent years, powerful design tools for linear time-invariant multivariable control systems have been developed based on direct parameter optimization. In this report, an algorithm for reliable optimal control synthesis using parameter optimization is presented. Specifically, a robust numerical algorithm is developed for the evaluation of the H(sup 2)-like cost functional and its gradients with respect to the controller design parameters. The method is specifically designed to handle defective degenerate systems and is based on the well-known Pade series approximation of the matrix exponential. Numerical test problems in control synthesis for simple mechanical systems and for a flexible structure with densely packed modes illustrate positively the reliability of this method when compared to a method based on diagonalization. Several types of cost functions have been considered: a cost function for robust control consisting of a linear combination of quadratic objectives for deterministic and random disturbances, and one representing an upper bound on the quadratic objective for worst case initial conditions. Finally, a framework for multivariable control synthesis has been developed combining the concept of closed-loop transfer recovery with numerical parameter optimization. The procedure enables designers to synthesize not only observer-based controllers but also controllers of arbitrary order and structure. Numerical design solutions rely heavily on the robust algorithm due to the high order of the synthesis model and the presence of near-overlapping modes. The design approach is successfully applied to the design of a high-bandwidth control system for a rotorcraft.
Shunfu Jin
2013-01-01
Full Text Available In cognitive radio networks, if all the secondary user (SU packets join the system without any restrictions, the average latency of the SU packets will be greater, especially when the traffic load of the system is higher. For this, we propose an adaptive admission control scheme with a system access probability for the SU packets in this paper. We suppose the system access probability is inversely proportional to the total number of packets in the system and introduce an Adaptive Factor to adjust the system access probability. Accordingly, we build a discrete-time preemptive queueing model with adjustable joining rate. In order to obtain the steady-state distribution of the queueing model exactly, we construct a two-dimensional Markov chain. Moreover, we derive the formulas for the blocking rate, the throughput, and the average latency of the SU packets. Afterwards, we provide numerical results to investigate the influence of the Adaptive Factor on different performance measures. We also give the individually optimal strategy and the socially optimal strategy from the standpoints of the SU packets. Finally, we provide a pricing mechanism to coordinate the two optimal strategies.
A BATCH ARRIVAL RETRIAL QUEUE WITH STARTING FAILURES, FEEDBACK AND ADMISSION CONTROL
Jinting WANG; Peng-Feng ZHOU
2010-01-01
This paper is concerned with the analysis of a feedback M[X]/G/1 retrial queue with starting failures and general retrial times.In a batch,each individual customer is subject to a control admission policy upon arrival.If the server is idle,one of the customers admitted to the system may start its service and the rest joins the retrial group,whereas all the admitted customers go to the retrial group when the server is unavailable upon arrival.An arriving customer(primary or retrial)must turn-on the server,which takes negligible time.If the server is started successfully(with a certain probability),the customer gets service immediately.Otherwise,the repair for the server commences immediately and the customer must leave for the orbit and make a retrial at a later time.It is assumed that the customers who find the server unavailable are queued in the orbit in accordance with an FCFS discipline and only the customer at the head of the queue is allowed for access to the server.The Markov chain underlying the considered queueing system is studied and the necessary and sufficient condition for the system to be stable is presented.Explicit formulae for the stationary distribution and some performance measures of the system in steady-state are obtained.Finally,some numerical examples are presented to illustrate the influence of the parameters on several performance characteristics.
R. S. Mohana
2013-01-01
Full Text Available Software as a Service (SaaS offers reliable access to software applications to the end users over the Internet without direct investment in infrastructure and software. SaaS providers utilize resources of internal data centres or rent resources from a public Infrastructure as a Service (IaaS provider in order to serve their customers. Internal hosting can ample cost of administration and maintenance whereas hiring from an IaaS provider can impact the service quality due to its variable performance. To surmount these drawbacks, we propose pioneering admission control and scheduling algorithms for SaaS providers to effectively utilize public Cloud resources to maximize profit by minimizing cost and improving customer satisfaction level. There is a drawback in this method is strength of the algorithms by handling errors in dynamic scenario of cloud environment, also there is a need of machine learning method to predict the strategies and produce the according resources. The admission control provided by trust model that is based on SLA uses different strategies to decide upon accepting user requests so that there is minimal performance impact, avoiding SLA penalties that are giving higher profit. Machine learning method aims at building a distributed system for cloud resource monitoring and prediction that includes learning-based methodologies for modelling and optimization of resource prediction models. The learning methods are Artificial Neural Network (ANN and Support Vector Machine (SVM are two typical machine learning strategies in the category of regression computation. These two methods can be employed for modelling resource state prediction. In addition, we conduct a widespread evaluation study to analyze which solution matches best in which scenario to maximize SaaS providerâs profit. Results obtained through our extensive simulation shows that our proposed algorithms provide significant improvement (up to 40% cost saving over
Demand response based on admission control in smart grid%基于接纳控制的智能电网需求响应
马锴; 姚婷; 关新平
2015-01-01
采用效用函数刻画用户的用电满意度，将需求响应问题建模为一类凸优化问题。针对电力供应商的供电量不能满足用户最小用电需求的问题，结合分布式用电量调度和实时定价，设计两类接纳控制算法。仿真结果表明，通过接纳控制，满足了购电用户的最小用电需求，保证了用户的用电质量，能够实现电网的供需平衡。%Utility functions are used to denote the satisfaction of consumers and formulate demand response as a convex optimization problem. For the case that the power supply can not meet the minimum power consumption of the consumers, two admission control algorithms are designed, combining with distributed power consumption scheduling and real-time pricing. Simulation results show that the admission control makes the consumers meet the minimum power consumption, ensure the power quality of the consumers, and balance the supply and the demand in smart grid.
Pinning impulsive control algorithms for complex network
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.
Fuzzy controller design by parallel genetic algorithms
Mondelli, G.; Castellano, G.; Attolico, Giovanni; Distante, Arcangelo
1998-03-01
Designing a fuzzy system involves defining membership functions and constructing rules. Carrying out these two steps manually often results in a poorly performing system. Genetic Algorithms (GAs) has proved to be a useful tool for designing optimal fuzzy controller. In order to increase the efficiency and effectiveness of their application, parallel GAs (PAGs), evolving synchronously several populations with different balances between exploration and exploitation, have been implemented using a SIMD machine (APE100/Quadrics). The parameters to be identified are coded in such a way that the algorithm implicitly provides a compact fuzzy controller, by finding only necessary rules and removing useless inputs from them. Early results, working on a fuzzy controller implementing the wall-following task for a real vehicle as a test case, provided better fitness values in less generations with respect to previous experiments made using a sequential implementation of GAs.
Figuring Control in the Algorithmic Era
Markham, Annette; Bossen, Claus
of control retrospectively, and illustrate the powerful paradoxes operating in and through everyday actions of digital living. This paper is part of an ongoing ethnographic and phenomenological study of algorithmic life. The cases we offer in this paper take the shape of dialogues between various...... actual loss of control, and consequences of maintaining an ambiguous stance toward the notion and operation of control within techno-cultural contexts. We believe this is a useful analytical move toward thinking about what is and what could be otherwise....
Telephony Over IP: A QoS Measurement-Based End to End Control Algorithm
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.
Simulation research on control algorithm of differential pressure casting process
Chai Yan; Jie Wanqi; Yang Bo
2009-01-01
To improve the precision of the filling pressure curve of differential pressure casting controlled with PID controller,the model of differential pressure casting process is established and two pressure-difference control systems using PID algorithm and Dahlin algorithm are separately designed in MATLAB. The scheduled pressure curves controlled with PID algorithm and Dahlin algorithm,respectively,are comparatively simulated in MATLAB.The simulated pressure curves obtained show that the control precision with Dahlin algorithm is higher than that with PID algorithm in the differential pressure casting process,and it was further verified by production practice.
Azuhata, Takeo; Kinoshita, Kosaku; Kawano, Daisuke; Komatsu, Tomonori; Sakurai, Atsushi; Chiba, Yasutaka; Tanjho, Katsuhisa
2014-01-01
Introduction We developed a protocol to initiate surgical source control immediately after admission (early source control) and perform initial resuscitation using early goal-directed therapy (EGDT) for gastrointestinal (GI) perforation with associated septic shock. This study evaluated the relationship between the time from admission to initiation of surgery and the outcome of the protocol. Methods This examination is a prospective observational study and involved 154 patients of GI perforat...
Yuret, Deniz
2012-01-01
Lexical substitutes have found use in the context of word sense disambiguation, unsupervised part-of-speech induction, paraphrasing, machine translation, and text simplification. Using a statistical language model to find the most likely substitutes in a given context is a successful approach, but the cost of a naive algorithm is proportional to the vocabulary size. This paper presents the Fastsubs algorithm which can efficiently and correctly identify the most likely lexical substitutes for a given context based on a statistical language model without going through most of the vocabulary. The efficiency of Fastsubs makes large scale experiments based on lexical substitutes feasible. For example, it is possible to compute the top 10 substitutes for each one of the 1,173,766 tokens in Penn Treebank in about 6 hours on a typical workstation. The same task would take about 6 days with the naive algorithm. An implementation of the algorithm and a dataset with the top 100 substitutes of each token in the WSJ secti...
Redmond, J. [Sandia National Labs., Albuquerque, NM (United States); Parker, G. [State Univ. of New York, Buffalo, NY (United States)
1993-07-01
This paper examines the role of the control objective and the control time in determining fuel-optimal actuator placement for structural vibration suppression. A general theory is developed that can be easily extended to include alternative performance metrics such as energy and time-optimal control. The performance metric defines a convex admissible control set which leads to a max-min optimization problem expressing optimal location as a function of initial conditions and control time. A solution procedure based on a nested Genetic Algorithm is presented and applied to an example problem. Results indicate that the optimal locations vary widely as a function of control time and initial conditions.
Genetic Algorithm based Decentralized PI Type Controller: Load Frequency Control
Dwivedi, Atul; Ray, Goshaidas; Sharma, Arun Kumar
2016-05-01
This work presents a design of decentralized PI type Linear Quadratic (LQ) controller based on genetic algorithm (GA). The proposed design technique allows considerable flexibility in defining the control objectives and it does not consider any knowledge of the system matrices and moreover it avoids the solution of algebraic Riccati equation. To illustrate the results of this work, a load-frequency control problem is considered. Simulation results reveal that the proposed scheme based on GA is an alternative and attractive approach to solve load-frequency control problem from both performance and design point of views.
Performance evaluation of sensor allocation algorithm based on covariance control
无
2005-01-01
The covariance control capability of sensor allocation algorithms based on covariance control strategy is an important index to evaluate the performance of these algorithms. Owing to lack of standard performance metric indices to evaluate covariance control capability, sensor allocation ratio, etc, there are no guides to follow in the design procedure of sensor allocation algorithm in practical applications. To meet these demands, three quantified performance metric indices are presented, which are average covariance misadjustment quantity (ACMQ), average sensor allocation ratio (ASAR) and matrix metric influence factor (MMIF), where ACMQ, ASAR and MMIF quantify the covariance control capability, the usage of sensor resources and the robustness of sensor allocation algorithm, respectively. Meanwhile, a covariance adaptive sensor allocation algorithm based on a new objective function is proposed to improve the covariance control capability of the algorithm based on information gain. The experiment results show that the proposed algorithm have the advantage over the preceding sensor allocation algorithm in covariance control capability and robustness.
Two-Level Cross-Talked Admission Control Mechanism for QoS Guarantee in 802.11e EDCA
NIU Zhisheng; LIU Jing
2008-01-01
This paper describes a two-level cross-talked admission control mechanism that guarantees qual-ity of service (QoS) requirements for multimedia applications over wireless local area networks (WLANs). An enhanced distributed channel access analytical model is used to compute the maximum number of admitted users according to the QoS requirements and the packet arrival characters. Then, some channel resources are reserved for handoff calls based on the maximum number of admitted users and the call-level traffic model. The channel utilization ratio is also measured to reflect the current system traffic load. The maximum number of admitted users and the channel utilization ratio are used for admission control for applications with QoS requirements in the call level and for rate control of best effort applications in the packet level using the p-nonacknowledgement scheme. Thus, the QoS requirements are statistically guaranteed while the system is efficiently utilized. Simulations validate the effectiveness of this mechanism to guarantee the QoS and bandwidth utilization.
Optimization of PID Controllers Using Ant Colony and Genetic Algorithms
Ünal, Muhammet; Topuz, Vedat; Erdal, Hasan
2013-01-01
Artificial neural networks, genetic algorithms and the ant colony optimization algorithm have become a highly effective tool for solving hard optimization problems. As their popularity has increased, applications of these algorithms have grown in more than equal measure. While many of the books available on these subjects only provide a cursory discussion of theory, the present book gives special emphasis to the theoretical background that is behind these algorithms and their applications. Moreover, this book introduces a novel real time control algorithm, that uses genetic algorithm and ant colony optimization algorithms for optimizing PID controller parameters. In general, the present book represents a solid survey on artificial neural networks, genetic algorithms and the ant colony optimization algorithm and introduces novel practical elements related to the application of these methods to process system control.
AAO Starbugs: software control and associated algorithms
Lorente, Nuria P F; Shortridge, Keith; Farrell, Tony J; Smedley, Scott; Hong, Sungwook E; Bacigalupo, Carlos; Goodwin, Michael; Kuehn, Kyler; Satorre, Christophe
2016-01-01
The Australian Astronomical Observatory's TAIPAN instrument deploys 150 Starbug robots to position optical fibres to accuracies of 0.3 arcsec, on a 32 cm glass field plate on the focal plane of the 1.2 m UK-Schmidt telescope. This paper describes the software system developed to control and monitor the Starbugs, with particular emphasis on the automated path-finding algorithms, and the metrology software which keeps track of the position and motion of individual Starbugs as they independently move in a crowded field. The software employs a tiered approach to find a collision-free path for every Starbug, from its current position to its target location. This consists of three path-finding stages of increasing complexity and computational cost. For each Starbug a path is attempted using a simple method. If unsuccessful, subsequently more complex (and expensive) methods are tried until a valid path is found or the target is flagged as unreachable.
Clonal Selection Algorithm Based Iterative Learning Control with Random Disturbance
Yuanyuan Ju
2013-01-01
Full Text Available Clonal selection algorithm is improved and proposed as a method to solve optimization problems in iterative learning control. And a clonal selection algorithm based optimal iterative learning control algorithm with random disturbance is proposed. In the algorithm, at the same time, the size of the search space is decreased and the convergence speed of the algorithm is increased. In addition a model modifying device is used in the algorithm to cope with the uncertainty in the plant model. In addition a model is used in the algorithm cope with the uncertainty in the plant model. Simulations show that the convergence speed is satisfactory regardless of whether or not the plant model is precise nonlinear plants. The simulation test verify the controlled system with random disturbance can reached to stability by using improved iterative learning control law but not the traditional control law.
An experimental study on load-peak shaving in smart homes by means of online admission control
Costanzo, Giuseppe Tommaso; Kosek, Anna Magdalena; Zhu, Guchuan;
2012-01-01
This paper presents the design, implementation, and experimental results of an architecture for autonomous demand-side load management (ADSM) system for Smart Buildings in view of influencing the energy demand in the Smart Grid. In such an architecture, the management system has a layered structure...... and appliances' operation is modeled as a finite state machine, which enables an efficient load control using scheduling techniques borrowed from real-time computing systems. In this study the Admission Control, which is the bottom layer of the presented architecture interacting in real-time with...... physical equipments, is addressed and the real-time power consumption management in a residential dwelling is implemented and tested in a real office building. The experimental results provide a proof of concept for the proposed architecture and demonstrate the applicability of the on-line scheduling...
Stabilizing the Richardson eigenvector algorithm by controlling chaos
By viewing the operations of the Richardson purification algorithm as a discrete time dynamical process, we propose a method to overcome the instability of this eigenvector algorithm by controlling chaos. We present theoretical analysis and numerical results on the behavior and performance of the stabilized algorithm. copyright 1997 American Institute of Physics
LEARNING ALGORITHM OF STAGE CONTROL NBP NETWORK
Yan Lixiang; Qin Zheng
2003-01-01
This letter analyzes the reasons why the known Neural Back Promulgation (NBP)network learning algorithm has slower speed and greater sample error. Based on the analysis and experiment, the training group descending Enhanced Combination Algorithm (ECA) is proposed.The analysis of the generalized property and sample error shows that the ECA can heighten the study speed and reduce individual error.
Maintenance of Process Control Algorithms based on Dynamic Program Slicing
Hansen, Ole Fink; Andersen, Nils Axel; Ravn, Ole
2010-01-01
behavior of a control algorithm, enables maintenance personnel to focus on only relevant parts of the algorithm and semi-automatically locate the part of the algorithm that is responsible for the reduced performance. The solution is tuning-free and can be applied to installed and running systems without......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...... particularly difficult to locate causes of performance loss, while readjusting the algorithm once the cause of performance loss is actually realized and found is relatively simple. In this paper we present a software-engineering approach to the maintenance problem, which provides tools for exploring the...
DEVELOPMENT OF NEURO FUZZY CONTROLLER ALGORITHM FOR AIR CONDITIONING SYSTEM
AMRIT KAUR; ARSHDEEP KAUR
2012-01-01
The paper presents the neuro-fuzzy controller algorithm for air conditioning system. Neuro-fuzzy control combines the learning capabilities of neural networks and control capabilities of fuzzy logic control. The neurofuzzy controller for air conditioning system takes two inputs from temperature and humidity sensors and controls the compressor speed. The experimental results of the developed system are also shown.
DEVELOPMENT OF NEURO FUZZY CONTROLLER ALGORITHM FOR AIR CONDITIONING SYSTEM
AMRIT KAUR
2012-04-01
Full Text Available The paper presents the neuro-fuzzy controller algorithm for air conditioning system. Neuro-fuzzy control combines the learning capabilities of neural networks and control capabilities of fuzzy logic control. The neurofuzzy controller for air conditioning system takes two inputs from temperature and humidity sensors and controls the compressor speed. The experimental results of the developed system are also shown.
Advanced CHP Control Algorithms: Scope Specification
Katipamula, Srinivas; Brambley, Michael R.
2006-04-28
The primary objective of this multiyear project is to develop algorithms for combined heat and power systems to ensure optimal performance, increase reliability, and lead to the goal of clean, efficient, reliable and affordable next generation energy systems.
Steven Hawken
Full Text Available OBJECTIVE: We investigated the association between a child's birth order and emergency room (ER visits and hospital admissions following 2-,4-,6- and 12-month pediatric vaccinations. METHODS: We included all children born in Ontario between April 1(st, 2006 and March 31(st, 2009 who received a qualifying vaccination. We identified vaccinations, ER visits and admissions using health administrative data housed at the Institute for Clinical Evaluative Sciences. We used the self-controlled case series design to compare the relative incidence (RI of events among 1(st-born and later-born children using relative incidence ratios (RIR. RESULTS: For the 2-month vaccination, the RIR for 1(st-borns versus later-born children was 1.37 (95% CI: 1.19-1.57, which translates to 112 additional events/100,000 vaccinated. For the 4-month vaccination, the RIR for 1(st-borns vs. later-borns was 1.70 (95% CI: 1.45-1.99, representing 157 additional events/100,000 vaccinated. At 6 months, the RIR for 1(st vs. later-borns was 1.27 (95% CI: 1.09-1.48, or 77 excess events/100,000 vaccinated. At the 12-month vaccination, the RIR was 1.11 (95% CI: 1.02-1.21, or 249 excess events/100,000 vaccinated. CONCLUSIONS: Birth order is associated with increased incidence of ER visits and hospitalizations following vaccination in infancy. 1(st-born children had significantly higher relative incidence of events compared to later-born children.
Fuzzy Control of Chaotic System with Genetic Algorithm
FANG Jian-an; GUO Zhao-xia; SHAO Shi-huang
2002-01-01
A novel approach to control the unpredictable behavior of chaotic systems is presented. The control algorithm is based on fuzzy logic control technique combined with genetic algorithm. The use of fuzzy logic allows for the implementation of human "rule-of-thumb" approach to decision making by employing linguistic variables. An improved Genetic Algorithm (GA) is used to learn to optimally select the fuzzy membership functions of the linguistic labels in the condition portion of each rule,and to automatically generate fuzzy control actions under each condition. Simulation results show that such an approach for the control of chaotic systems is both effective and robust.
Power balance control using evolutionary algorithm
This paper described a nonlinear optimization problem to enable independent system operators (ISOs) to make least-cost decisions for the activation of ancillary services. A self-organizing migration algorithm (SOMA) based on the competitive-cooperative behavior of intelligent creatures solving a common problem was tested on 2 scenarios based on real values obtained from a transmission system operator (TSO) in the Czech Republic. The 6 hour datasets were used to demonstrate the prediction of error between production and consumption. The characteristics and capacity of the ancillary services were used as system and operating constraints for the optimization. History values from the datasets were then simulated. The SOMA algorithm then searched for solutions to minimize the cost function. Scenarios for a short and long outage of a large generating unit were used to demonstrate the algorithm's ability to balance power in the system. 4 refs., 1 tab., 3 figs.
Model-Free Adaptive Control Algorithm with Data Dropout Compensation
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.
Topology control based on quantum genetic algorithm in sensor networks
SUN Lijuan; GUO Jian; LU Kai; WANG Ruchuan
2007-01-01
Nowadays,two trends appear in the application of sensor networks in which both multi-service and quality of service (QoS)are supported.In terms of the goal of low energy consumption and high connectivity,the control on topology is crucial.The algorithm of topology control based on quantum genetic algorithm in sensor networks is proposed.An advantage of the quantum genetic algorithm over the conventional genetic algorithm is demonstrated in simulation experiments.The goals of high connectivity and low consumption of energy are reached.
Genetic Algorithm Based Proportional Integral Controller Design for Induction Motor
Mohanasundaram Kuppusamy
2011-01-01
Full Text Available Problem statement: This study has expounded the application of evolutionary computation method namely Genetic Algorithm (GA for estimation of feedback controller parameters for induction motor. GA offers certain advantages such as simple computational steps, derivative free optimization, reduced number of iterations and assured near global optima. The development of the method is well documented and computed and measured results are presented. Approach: The design of PI controller parameter for three phase induction motor drives was done using Genetic Algorithm. The objective function of motor current reduction, using PI controller, at starting is formulated as an optimization problem and solved with Genetic Algorithm. Results: The results showed the selected values of PI controller parameter using genetic algorithm approach, with objective of induction motor starting current reduction. Conclusions/Recommendation: The results proved the robustness and easy implementation of genetic algorithm selection of PI parameters for induction motor starting.
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-...
Admissibility of Linear Systems in Banach Spaces
GUO Fa-ming
2005-01-01
In this paper, infinite-time p-admissibility of unbounded operators is introduced and the Co-semigroup characterization of the infinite-time p-admissibility of unbounded observation operators is given. Moreover, the analogous result for the infinite-time p-admissibility of unbounded control operators is presented.
Multi-Stage Admission Control for Load Balancing in Next Generation Systems
Mihovska, Albena D.; Anggorojati, Bayu; Luo, Jijun;
2008-01-01
user to the network, i.e., the ranking of the intermediate decisions is dynamic. The decision is controlled by passing a token between the base station (BS) and the gateway (GW), thereby considering the load status of the BS and the backhaul network. A token is assigned to the entity with the highest...
Enhanced signaling scheme with admission control in the hybrid optical wireless (HOW) networks
Yan, Ying; Yu, Hao; Wessing, Henrik;
2009-01-01
The hybrid optical wireless (HOW) network has been viewed as a promising solution to meet the increasing user bandwidth and mobility demands. Due to the basic differences in the optical and wireless technologies, a challenging problem lies in the Media Access Control (MAC) protocol design so that...
Maybritt Jill Alpes
2015-09-01
Full Text Available This article analyzes what can happen to forced returnees upon arrival in their country of nationality. Subjective configurations of state agents in the Global South have created return risks, which in turn transform subjectivities of post-colonial citizens. The article contributes to this Special Issue by tracing repercussions of the externalization and internalization of border controls. In the case of Cameroon, these connections have resulted in the criminalization of emigration. Aspiring migrants are prosecuted if their departure projects fail to respect the entry requirements of countries in the Global North. The article is based on research conducted in Douala, Cameroon, in the form of discussions with control agents at the international airport, investigations at a prison, a review of related case law, police registers and interviews with Cameroonians returnees (November 2013–January 2014. Border controls and connected anti-fraud programs suppress family-based forms of solidarity and allow only for subjectivities rooted in state-managed forms of national identity. The article illustrates how efforts to combat fraud fuel corruption in returnees’ social networks, whereby, instead of receiving remittances, families in emigration countries have to mobilize financial resources in order to liberate returnees from police stations or prison complexes. Migration related detention of nationals in the Global South highlights the growing significance of exit controls in migration management.
Genetic Algorithm Tuned Fuzzy Logic Controller for Rotary Inverted Pendulum
Tzu-Chun Kuo; Ying-Jeh Huang; Ping-Chou Wu
2013-01-01
In this study, a Genetic Algorithm (GA) is proposed to search for the optimal input membership functions of the fuzzy logic controller. With the optimal membership function, the fuzzy logic controller can efficiently control a rotary inverted pendulum. The advantage of the proposed method is tuning the parameters of membership functions automatically rather than tuning them manually. In genetic algorithm, these parameters are converted to a chromosome which is encoded into a binary string. Be...
Algorithm improvement for phase control of subharmonic buncher
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)
Control Logic Algorithm for Medium Scale Wind Turbines
Osama Abdel Hakeem Abdel Sattar
2012-01-01
Full Text Available Recently, sustainable attention has been drawn to renewable energy sources. Wind energy systems as renewable source of energy have been extensively studied because of its benefits as an environmentally friendly clean energy, inexhaustible, safe and a low-cost for long term. Because of its unpredictable availability, power management control algorithms are essential to extract as much power as possible from the wind during its availability durations. This paper is motivated for proposing the main control algorithm for wind turbines each incorporating two generators. The proposed main algorithm contains several sub algorithm models (strategies for power control, pitch control, status checking, starting, grid connection, normal and emergency shutdown that are studied, designed and also, tested under operation. The testing phase shows that in the high wind speed range, the pitch control seems the most relevant to release a power margin. While in the low wind speed range, the increase of the rotation speed is more convenient.
NOVEL POWER CONTROL GAME VIA PRICING ALGORITHM FOR COGNITIVE RADIOS
无
2008-01-01
To compensate the service providers who have paid billions of dollars to use spectrum and to satisfy secondary users’requirements in cognitive radios,a Non-cooperative Power Control Game and Pricing algorithm (NPGP) is proposed. Simulation results show that the proposed algorithm can regulate the secondary users’transmitter powers,optimally allocate radio resource and increase the total throughput effectively.
Performance of Power Control Algorithm for DSCDMA on Reverse Link
Chandra Prakash
2013-09-01
Full Text Available In this paper, the performance of smart step closed loop power control (SSPC algorithm and base station assignment method based on minimizing the transmitter power (BSA-MTP technique for direct sequence-code division multiple access (DS-CDMA receiver in a 2D urban environment has been compared. The simulation results indicate that the SSPC algorithm and the BSA-MTP technique can improve the network bit error rate in comparison with other conventional methods. Further, the convergence speed of the SSPC algorithm is faster than that of conventional algorithms
Pinnock, Hilary; Hanley, Janet; McCloughan, Lucy; Todd, Allison; Krishan, Ashma; Lewis, Stephanie; Stoddart, Andrew; van der Pol, Marjon; MacNee, William; Sheikh, Aziz; Pagliari, Claudia; McKinstry, Brian
2013-01-01
Objective: To test the effectiveness of telemonitoring integrated into existing clinical services such that intervention and control groups have access to the same clinical care. Design: Researcher blind, multicentre, randomised controlled trial. Setting: UK primary care (Lothian, Scotland). Participants: Adults with at least one admission for chronic obstructive pulmonary disease (COPD) in the year before randomisation. We excluded people who had other significant lung disease, who were unab...
Pinnock, Hilary; Hanley, Janet; McCloughan, Lucy; Todd, Allison; Krishan, Ashma; Lewis, Stephanie; Stoddart, Andrew; van der Pol, Marjon; MacNee, William; Sheikh, Aziz; Pagliari, Claudia; McKinstry, Brian
2013-01-01
Objective To test the effectiveness of telemonitoring integrated into existing clinical services such that intervention and control groups have access to the same clinical care. Design Researcher blind, multicentre, randomised controlled trial. Setting UK primary care (Lothian, Scotland). Participants Adults with at least one admission for chronic obstructive pulmonary disease (COPD) in the year before randomisation. We excluded people who had other significant lung disease, who were unable t...
RSOFCPN: CONTROL SYSTEM STRUCTURE AND ALGORITHM DESIGN
无
2000-01-01
A stable control scheme for a class of unknown nonlinear systems was presented. The control architecture is composed of two parts, the fuzzy sliding mode controller (FSMC) is applied to drive the state to a designed switching hyperplane, and a reinforcement self-organizing fuzzy CPN (RSOFCPN) as a feedforward compensator is used to reduce the influence of system uncertainties. The simulation results demonstrate the effectiveness of the proposed control scheme.
DSP IMPLEMENTATION OF A -CONTROL ALGORITHM FOR A FORWARDER CRANE
Thati, Naga Praveen Parchuru and Jagadeesh
2010-01-01
The thesis task is to implement the algorithm for the automatic extension link into a proper Dasa computer system in order to control a forwarder crane. The implemented code should be tested at the laboratory crane at Linneus University, Vaxjo.
Robust reactor power control system design by genetic algorithm
The H∞ 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
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.
Robust reactor power control system design by genetic algorithm
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)
Decentralized Control of Dynamic Routing with a Neural Network Algorithm
无
2000-01-01
A state-dependent routing algorithm based on the neural network model, which takes advantage of other dynamic routing algorithm for circuit-switched network, is given in [1]. But, the Algorithm in [1] is a centralized control model with complex O (N7), therefore, is difficult to realize by hardware. A simplified algorithm is put forward in this paper, in which routing can be controlled decentralizedly, and its complexity is reduced to O (10N3). Computer simulations are made in a fully connected test network with eight nodes. The results show that the centralized control model has very effective performance that can match RTNR, and the centralized control model is not as good as the centralized one but better than DAR-1.
Ann L Montgomery
Full Text Available BACKGROUND: Research in areas of low skilled attendant coverage found that maternal mortality is paradoxically higher in women who seek obstetric care. We estimated the effect of health-facility admission on maternal survival, and how this effect varies with skilled attendant coverage across India. METHODS/FINDINGS: Using unmatched population-based case-control analysis of national datasets, we compared the effect of health-facility admission at any time (antenatal, intrapartum, postpartum on maternal deaths (cases to women reporting pregnancies (controls. Probability of maternal death decreased with increasing skilled attendant coverage, among both women who were and were not admitted to a health-facility, however, the risk of death among women who were admitted was higher (at 50% coverage, OR = 2.32, 95% confidence interval 1.85-2.92 than among those women who were not; while at higher levels of coverage, the effect of health-facility admission was attenuated. In a secondary analysis, the probability of maternal death decreased with increasing coverage among both women admitted for delivery or delivered at home but there was no effect of admission for delivery on mortality risk (50% coverage, OR = 1.0, 0.80-1.25, suggesting that poor quality of obstetric care may have attenuated the benefits of facility-based care. Subpopulation analysis of obstetric hemorrhage cases and report of 'excessive bleeding' in controls showed that the probability of maternal death decreased with increasing skilled attendant coverage; but the effect of health-facility admission was attenuated (at 50% coverage, OR = 1.47, 0.95-1.79, suggesting that some of the effect in the main model can be explained by women arriving at facility with complications underway. Finally, highest risk associated with health-facility admission was clustered in women with education ≤ 8 years. CONCLUSIONS: The effect of health-facility admission did vary by skilled attendant coverage, and
Control algorithms for quasi-steady-state reactor operation
Specialized algorithms for digitally controlling the quasi-steady-state operation of reactors can be derived from the well-known neutron and energy balance equations for reactors. Utilizing the appropriate assumptions, these equations can be reduced to yield the classical proportional-integral-derivative feedback control approach. This method may be applied to single- or multiple-region reactors to control fuel temperature or neutron flux by manipulating system reactivity, specifically control rod reactivity. This paper discusses the development of single- and multiple-region flux and temperature control as well as numerical and experimental testing of these algorithms
Towards Automatic Controller Design using Multi-Objective Evolutionary Algorithms
Pedersen, Gerulf
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, as the......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 of...... foundation for achieving the desired goal. While working with the algorithm, some issues arose which limited the use of the algorithm for unknown problems. These issues included the relative scale of the used fitness functions and the distribution of solutions on the optimal Pareto front. Some work has...
A Decomposition Algorithm for Optimal Control of Distributed Energy System
Sokoler, Leo Emil; Edlund, Kristian; Standardi, Laura;
2013-01-01
In economic model predictive control of distributed energy systems, the constrained optimal control problem can be expressed as a linear program with a block-angular structure. In this paper, we present an efficient Dantzig-Wolfe decomposition algorithm specifically tailored to problems of this t...... type. Simulations show that a MATLAB implementation of the algorithm is significantly faster than several state-of-the-art linear programming solvers and that it scales in a favorable way....
Simulation of signalized intersection functioning with fuzzy control algorithm
Zinoviy STOTSKO
2013-01-01
Full Text Available In the course of research the fuzzy algorithm for traffic control at signalized intersection has been developed. Based on the results of simulating of intersection functioning during an hour and a day it has been established that using of developed fuzzy algorithm enables to reduce average and maximal queue lengths of vehicles before the intersection owing to adaptation of control system parameters to traffic flow volumes.
Secondary Coordinated Control of Islanded Microgrids Based on Consensus Algorithms
Wu, Dan; Dragicevic, Tomislav; Vasquez, Juan Carlos;
2014-01-01
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...... in an islanded microgrid system is tested in different scenarios by means of hardware-in-the-loop results....
Scheduling start time in CDMA burst admission
Zhuge, L; Li, VOK
2002-01-01
Burst transmission protocols have been proposed in the next generation CDMA cellular systems to support short-time high-speed data communications. The existing burst admission algorithm considers only the current interference condition in the system. The burst transmission request will be rejected if the interference in the system will exceed the acceptable level with the burst admitted. In this paper we propose a new burst admission algorithm where a currently-unacceptable burst request can ...
Design of the teleoperation algorithm to control the humanoid robot
Shelomentcev, Egor Evgenyevich; Alexandrova, Tatyana Viktorovna
2015-01-01
This paper presents a concept design of work algorithm for teleoperation control system of humanoid robot. Humanoid robot control system needs to stabilize the robot in a vertical position in order to prevent the robot from falling. The process of design of the control system includes the design of position filter to detect the unstable positions. The application of such a control system enables to control the humanoid robot using motion capture technology.
Genetic Algorithm based PID controller for Frequency Regulation Ancillary services
Sandeep Bhongade
2010-12-01
Full Text Available In this paper, the parameters of Proportional, Integral and Derivative (PID controller for Automatic Generation Control (AGC suitable in restructured power system is tuned according to Generic Algorithms (GAs based performance indices. The key idea of the proposed method is to use the fitness function based on Area Control Error (ACE. The functioning of the proposed Genetic Algorithm based PID (GAPID controller has been demonstrated on a 75-bus Indian power system network and the results have been compared with those obtained by using Least Square Minimization method.
Reactor controller design using genetic algorithms with simulated annealing
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
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.
Adaptive Control Algorithms, Analysis and Applications
Landau, Ioan; Lozano, Rogelio; M'Saad, Mohammed; Karimi, Alireza
2011-01-01
Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the ...
Algorithm for calculating torque base in vehicle traction control system
Li, Hongzhi; Li, Liang; Song, Jian; Wu, Kaihui; Qiao, Yanjuan; Liu, Xingchun; Xia, Yongguang
2012-11-01
Existing research on the traction control system(TCS) mainly focuses on control methods, such as the PID control, fuzzy logic control, etc, aiming at achieving an ideal slip rate of the drive wheel over long control periods. The initial output of the TCS (referred to as the torque base in this paper), which has a great impact on the driving performance of the vehicle in early cycles, remains to be investigated. In order to improve the control performance of the TCS in the first several cycles, an algorithm is proposed to determine the torque base. First, torque bases are calculated by two different methods, one based on states judgment and the other based on the vehicle dynamics. The confidence level of the torque base calculated based on the vehicle dynamics is also obtained. The final torque base is then determined based on the two torque bases and the confidence level. Hardware-in-the-loop(HIL) simulation and vehicle tests emulating sudden start on low friction roads have been conducted to verify the proposed algorithm. The control performance of a PID-controlled TCS with and without the proposed torque base algorithm is compared, showing that the proposed algorithm improves the performance of the TCS over the first several cycles and enhances about 5% vehicle speed by contrast. The proposed research provides a more proper initial value for TCS control, and improves the performance of the first several control cycles of the TCS.
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.
Bouchti, Abdelali El; Kafhali, Said El
2012-01-01
In this paper, we consider a single-cell IEEE 802.16 environment in which the base station allocates subchannels to the subscriber stations in its coverage area. The subchannels allocated to a subscriber station are shared by multiple connections at that subscriber station. To ensure the Quality of Service (QoS) performances, two Connection Admission Control (CAC) mechanisms, namely, threshold-based and queue-aware CAC mechanisms are considered at a subscriber station. A queuing analytical framework for these admission control mechanisms is presented considering Orthogonal Frequency Division Multiple Access (OFDMA) based transmission at the physical layer. Then, based on the queuing model, both the connection-level and the packet-level performances are studied and compared with their analogues in the case without CAC. The connection arrival is modeled by a Poisson process and the packet arrival for a connection by Batch Markov Arrival Process (BMAP). We determine analytically and numerically different QoS per...
Optimized Reconfigurable Control Design for Aircraft using Genetic Algorithm
Arsalan H. Khan
2013-12-01
Full Text Available In this study, we propose a Genetic Algorithm (GA based modular reconfigurable control scheme for an over-actuated non-linear aircraft model. The reconfiguration of the flight controller is achieved for the case of control surface faults/failures using a separate control distribution algorithm without modifying the base-line control law. The baseline Multi-Input Multi-Output (MIMO Linear Quadratic Regulator (LQR is optimized using GA to produce desired moment commands. Then, a GA based weighted pseudo-inverse method is used for effective distribution of commands between redundant control surfaces. Control surface effectiveness levels are used to redistribute the control commands to healthy actuators when a fault or failure occurs. Simulation results using ADMIRE aircraft model show the satisfactory performance in accommodating different faults, which confirm the efficiency of optimized reconfigurable design strategy.
Ultramaneuverable steering control algorithms for terrain transitions
Torrie, Mel W.; Koch, Ralf; Bahl, Vikas; Cripps, Don
1999-07-01
The Center for Self-Organizing and Intelligent Systems has built several vehicles with ultra-maneuverable steering capability. Each drive wheel on the vehicle can be independently set at any angle with respect to the vehicle body and the vehicles can rotate or translate in any direction. The vehicles are expected to operate on a wide range of terrain surfaces and problems arise in effectively controlling changes in wheel steering angles as the vehicle transitions from one extreme running surface to another. Controllers developed for smooth surfaces may not perform well on rough or 'sticky' surfaces and vice versa. The approach presented involves the development of a model of the steering motor with the static and viscous friction of the steering motor load included. The model parameters are then identified through a series of environmental tests using a vehicle wheel assembly and the model thus obtained is used for control law development. Four different robust controllers were developed and evaluated through simulation and vehicle testing. The findings of this development will be presented.
MPPT algorithm for voltage controlled PV inverters
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 to...
On flexible CAD of adaptive control and identification algorithms
Christensen, Anders; Ravn, Ole
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 a t...
Remote System for Development, Implementation and Testing of Control Algorithms
Milan Matijevic
2007-02-01
Full Text Available Education in the field of automatic control requires adequate practice on real systems for better and full understanding of the control theory. Experimenting on real models developed exclusively for the purpose of education and gaining necessary experience is the most adequate and traditionally it requires physical presence in laboratories where the equipment is installed. Remote access to laboratories for control systems is a necessary precondition and support for implementation of the e learning in the area of control engineering. The main feature of the developed system is support for the development, implementation and testing of user defined control algorithms with remote controller laboratory. User can define control algorithm in some conventional programming language and test it using this remote system.
Oudin, Anna; Stroh, Emilie; Strömberg, Ulf; Jakobsson, Kristina; Björk, Jonas
2009-01-01
Background Long-term exposure to air pollution is a hypothesized risk factor for ischemic stroke. In a large case-control study with a complete study base, we investigated whether hospital admissions for ischemic stroke were associated with residential concentrations of outdoor NOx, as a proxy for exposure to air pollution, in the region of Scania, Southern Sweden. Methods We used a two-phase case-control study design, including as first-phase controls all individuals born between 1923 and 19...
Discrete-time minimal control synthesis adaptive algorithm
di Bernardo, M.; di Gennaro, F.; Olm, J. M.; Santini, S.
2010-12-01
This article proposes a discrete-time Minimal Control Synthesis (MCS) algorithm for a class of single-input single-output discrete-time systems written in controllable canonical form. As it happens with the continuous-time MCS strategy, the algorithm arises from the family of hyperstability-based discrete-time model reference adaptive controllers introduced in (Landau, Y. (1979), Adaptive Control: The Model Reference Approach, New York: Marcel Dekker, Inc.) and is able to ensure tracking of the states of a given reference model with minimal knowledge about the plant. The control design shows robustness to parameter uncertainties, slow parameter variation and matched disturbances. Furthermore, it is proved that the proposed discrete-time MCS algorithm can be used to control discretised continuous-time plants with the same performance features. Contrary to previous discrete-time implementations of the continuous-time MCS algorithm, here a formal proof of asymptotic stability is given for generic n-dimensional plants in controllable canonical form. The theoretical approach is validated by means of simulation results.
Zhang, Xianxia; Wang, Jian; Qin, Tinggao
2003-09-01
Intelligent control algorithms are introduced into the control system of temperature and humidity. A multi-mode control algorithm of PI-Single Neuron is proposed for single loop control of temperature and humidity. In order to remove the coupling between temperature and humidity, a new decoupling method is presented, which is called fuzzy decoupling. The decoupling is achieved by using a fuzzy controller that dynamically modifies the static decoupling coefficient. Taking the control algorithm of PI-Single Neuron as the single loop control of temperature and humidity, the paper provides the simulated output response curves with no decoupling control, static decoupling control and fuzzy decoupling control. Those control algorithms are easily implemented in singlechip-based hardware systems.
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.
TCP-ATCA: Improved Transmission Control Algorithm in Satellite Network
Liu Feng; Liu Hengna; Zhao Han
2008-01-01
An adaptive transmission control algorithm based on TCP (TCP-ATCA) is proposed to reduce the effects of long propagation de- lay and high link error rate of the satellite network on the performances. The flow control and the error recovery are differentiated by combined dynamic random early detection-explicit congestion notification (DRED-ECN) algorithm, and, moreover, the pertaining con- gestion control methods are used in TCP-ATCA to improve the throughput. By introducing the entire recovery algorithm, the unneces- sary congestion window decrease is reduced, and the throughput and fairness are improved. Simulation results show that, compared with TCP-Reno, TCP-ATCA provides a better throughput performance when the link capacity is higher (≥ 600 packet/s), and roughly the same when it is lower. At the same time, TCP-ATCA also increases fairness and reduces transmission delay.
Adaptive process control using fuzzy logic and genetic algorithms
Karr, C. L.
1993-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.
Adaptive Process Control with Fuzzy Logic and Genetic Algorithms
Karr, C. L.
1993-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision-making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.
The development of the system leads to the following: automated registering of the staff in the personnel database; real time reading of the personal dosimeters; real time reading of the collective dose; the control over the working people (especially external) concerning the dose limits or restrictions are performed in real time
A Traffic Prediction Algorithm for Street Lighting Control Efficiency
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.
Comparative analysis of algorithms for lunar landing control
Zhukov, B. I.; Likhachev, V. N.; Sazonov, V. V.; Sikharulidze, Yu. G.; Tuchin, A. G.; Tuchin, D. A.; Fedotov, V. P.; Yaroshevskii, V. S.
2015-11-01
For the descent from the pericenter of a prelanding circumlunar orbit a comparison of three algorithms for the control of lander motion is performed. These algorithms use various combinations of terminal and programmed control in a trajectory including three parts: main braking, precision braking, and descent with constant velocity. In the first approximation, autonomous navigational measurements are taken into account and an estimate of the disturbances generated by movement of the fuel in the tanks was obtained. Estimates of the accuracy for landing placement, fuel consumption, and performance of the conditions for safe lunar landing are obtained.
Review of control algorithms for offshore wind turbines
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.
Design of PID-type controllers using multiobjective genetic algorithms.
Herreros, Alberto; Baeyens, Enrique; Perán, José R
2002-10-01
The design of a PID controller is a multiobjective problem. A plant and a set of specifications to be satisfied are given. The designer has to adjust the parameters of the PID controller such that the feedback interconnection of the plant and the controller satisfies the specifications. These specifications are usually competitive and any acceptable solution requires a tradeoff among them. An approach for adjusting the parameters of a PID controller based on multiobjective optimization and genetic algorithms is presented in this paper. The MRCD (multiobjective robust control design) genetic algorithm has been employed. The approach can be easily generalized to design multivariable coupled and decentralized PID loops and has been successfully validated for a large number of experimental cases. PMID:12398277
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)
Wind turbine pitch control using ICPSO-PID algorithm
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......, a pitch controller was designed based on power and wind speed and by considering the inertia and delay characteristics of a pitch-control system to achieve a constant power output when a wind speed was beyond the rated one. A novel ICPSO-PID control algorithm was proposed based on a combination of...... 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...
Optimizing the controllability of arbitrary networks with genetic algorithm
Li, Xin-Feng; Lu, Zhe-Ming
2016-04-01
Recently, as the controllability of complex networks attracts much attention, how to optimize networks' controllability has become a common and urgent problem. In this paper, we develop an efficient genetic algorithm oriented optimization tool to optimize the controllability of arbitrary networks consisting of both state nodes and control nodes under Popov-Belevitch-Hautus rank condition. The experimental results on a number of benchmark networks show the effectiveness of this method and the evolution of network topology is captured. Furthermore, we explore how network structure affects its controllability and find that the sparser a network is, the more control nodes are needed to control it and the larger the differences between node degrees, the more control nodes are needed to achieve the full control. Our framework provides an alternative to controllability optimization and can be applied to arbitrary networks without any limitations.
Performance evaluation of two CAC algorithms in ATM networks
Chaves, Niudomar Siqueira de Araújo; Motoyama, Shusaburo
2000-01-01
This paper presents a performance study of two CAC (Connection Admission Control) algorithms. Both algorithms are based on effective bandwidth concept. The results were obtained through simulation. The analysis showed that the required QoS is achieved by the two algorithms, however, they overestimate the necessary bandwidth resulting in lower network resource utilization
Control algorithm implementation for a redundant degree of freedom manipulator
Cohan, Steve
1991-01-01
This project's purpose is to develop and implement control algorithms for a kinematically redundant robotic manipulator. The manipulator is being developed concurrently by Odetics Inc., under internal research and development funding. This SBIR contract supports algorithm conception, development, and simulation, as well as software implementation and integration with the manipulator hardware. The Odetics Dexterous Manipulator is a lightweight, high strength, modular manipulator being developed for space and commercial applications. It has seven fully active degrees of freedom, is electrically powered, and is fully operational in 1 G. The manipulator consists of five self-contained modules. These modules join via simple quick-disconnect couplings and self-mating connectors which allow rapid assembly/disassembly for reconfiguration, transport, or servicing. Each joint incorporates a unique drive train design which provides zero backlash operation, is insensitive to wear, and is single fault tolerant to motor or servo amplifier failure. The sensing system is also designed to be single fault tolerant. Although the initial prototype is not space qualified, the design is well-suited to meeting space qualification requirements. The control algorithm design approach is to develop a hierarchical system with well defined access and interfaces at each level. The high level endpoint/configuration control algorithm transforms manipulator endpoint position/orientation commands to joint angle commands, providing task space motion. At the same time, the kinematic redundancy is resolved by controlling the configuration (pose) of the manipulator, using several different optimizing criteria. The center level of the hierarchy servos the joints to their commanded trajectories using both linear feedback and model-based nonlinear control techniques. The lowest control level uses sensed joint torque to close torque servo loops, with the goal of improving the manipulator dynamic behavior
Implantation of algorithms of diffuse control in DSPS
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 study of complex control algorithm for regenerative furnace temperature
Lusheng GE
2004-01-01
Altemative switch combustion mode of air and gas is adopted on the two sides of the regenerative furnace, its temperature is in uncontrolled state in the switching process and the switch period is generally 3 ～ 5 min. Thus, the conventional bi-cross limited combustion control method is no longer applicable to the object. This paper makes use of neutral network algorithm to adjust the static operating point. On this basis, fuzzy control strategy is used for the furnace temperature control. The actual application result shows that the control strategy is effective to solve the problem of the combustion control for regenerative furnace.
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
Application of epidemic algorithms for smart grids control
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
Fully efficient time-parallelized quantum optimal control algorithm
Riahi, M. K.; Salomon, J.; Glaser, S. J.; Sugny, D.
2016-04-01
We present a time-parallelization method that enables one to accelerate the computation of quantum optimal control algorithms. We show that this approach is approximately fully efficient when based on a gradient method as optimization solver: the computational time is approximately divided by the number of available processors. The control of spin systems, molecular orientation, and Bose-Einstein condensates are used as illustrative examples to highlight the wide range of applications of this numerical scheme.
A Comparative Study of SIP Overload Control Algorithms
Hong, Yang; Huang, Changcheng; Yan, James
2012-01-01
Recent collapses of SIP servers in the carrier networks indicates two potential problems of SIP: (1) the current SIP design does not easily scale up to large network sizes, and (2) the built-in SIP overload control mechanism cannot handle overload conditions effectively. In order to help carriers prevent widespread SIP network failure effectively, this chapter presents a systematic investigation of current state-of-the-art overload control algorithms. To achieve this goal, this chapter first ...
Controller Design for Rotary Inverted Pendulum System Using Evolutionary Algorithms
Saleh Mobayen; Iraj Hassanzadeh
2011-01-01
This paper presents evolutionary approaches for designing rotational inverted pendulum (RIP) controller including genetic algorithms (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) methods. The goal is to balance the pendulum in the inverted position. Simulation and experimental results demonstrate the robustness and effectiveness of the proposed controllers with regard to parameter variations, noise effects, and load disturbances. The proposed methods can be consid...
Effective Algorithms for Parametrizing Linear Control Systems over Ore Algebras
Chyzak, Frédéric; Quadrat, Alban; Robertz, Daniel
2004-01-01
In this paper, we study linear control systems over Ore algebras. Within this mathematical framework, we can simultaneously deal with different classes of linear control systems such as time-varying systems of ordinary differential equations (ODEs), differential time-delay systems, underdetermined systems of partial differential equations (PDEs), multidimensional discrete systems, multidimensional convolutional codes etc. We give effective algorithms which check whether or not a linear contro...
Circumference and COD control algorithm of NewSUBARU
We renewed a closed orbit correction program for NewSUBARU. We use a new horizontal orbit correction algorithm with a circumference control. A response matrix in the program is calculated using the correct equation of the response in an electron storage ring. It made the correction process faster and more stable. It also eliminated an interference with the control program of RF frequency. (author)
Speed Control of PMSM Drives by Generalized Predictive Algorithms
Belda, Květoslav; Vošmik, D.
Montral : IEEE Industrial Electronics Society, 2012, s. 2002-2007. ISBN 978-1-4673-2419-9. [38th Annual Conference of the IEEE Industrial Electronics Society. Montreal (CA), 25.10.2012-28.10.2012] R&D Projects: GA ČR(CZ) GAP102/11/0437 Institutional support: RVO:67985556 Keywords : Generalized Predictive Control * PMSM Drives * Speed Control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2012/AS/belda-speed control of pmsm drives by generalized predictive algorithms.pdf
Managing control algorithms with an object-oriented database
Bickley, M.; Watson, W.
1995-12-31
The Continuous Electron Beam Accelerator Facility (CEBAF) uses the Experimental Physics and Industrial Control System (EPICS) for accelerator control. In EPICS, the atomic element of a control algorithm is a record. Records are grouped together to form generic applications, for example to control a single magnet. The generic applications are then instantiated for each specific item of machine hardware. Instantiated applications are executed on one of the 30 data acquisition and control computers that are used in the control system. There are roughly 125,000 unique, instantiated records at CEBAF, each associated with a specific piece of hardware. Management of these records in a database simplifies the task of application developers by allowing them to concentrate on algorithmic development instead of instantiation details. In addition, it decouples algorithmic development from the specification of operational parameters, allowing responsibility for those parameters to pass to machine operations staff. CEBAF needed an environment to provide support for development of EPICS database management tools. An object- oriented database (OODB) was chosen for two reasons: higher performance and the ability to smoothly manage objects of different types. 3 refs., 1 fig.
Managing control algorithms with an object-oriented database
Bickley, M; Watson, W
1995-01-01
The Continuous Electron Beam Accelerator Facility (CEBAF) uses the Experimental Physics and Industrial Control System (EPICS) for accelerator control. In EPICS, the atomic element of a control algorithm is a record. Records are grouped together to form generic applications, for example to control a single magnet. The generic applications are then instantiated for each specific item of machine hardware. Instantiated applications are executed on one of the 30 data acquisition and control computers that are used in the control system. There are roughly 125,000 unique, instantiated records at CEBAF, each associated with a specific piece of hardware. Management of these records in a database simplifies the task of application developers by allowing them to concentrate on algorithmic development instead of instantiation details. In addition, it decouples algorithmic development from the specification of operational parameters, allowing responsibility for those parameters to pass to machine operations staff. CEBAF needed an environment to provide support for development of EPICS database management tools. An object- oriented database (OODB) was chosen for two reasons: higher performance and the ability to smoothly manage objects of different types. 3 refs., 1 fig.
Managing control algorithms with an object-oriented database
The Continuous Electron Beam Accelerator Facility (CEBAF) uses the Experimental Physics and Industrial Control System (EPICS) for accelerator control. In EPICS, the atomic element of a control algorithm is a record. Records are grouped together to form generic applications, for example to control a single magnet. The generic applications are then instantiated for each specific item of machine hardware. Instantiated applications are executed on one of the 30 data acquisition and control computers that are used in the control system. There are roughly 125,000 unique, instantiated records at CEBAF, each associated with a specific piece of hardware. Management of these records in a database simplifies the task of application developers by allowing them to concentrate on algorithmic development instead of instantiation details. In addition, it decouples algorithmic development from the specification of operational parameters, allowing responsibility for those parameters to pass to machine operations staff. CEBAF needed an environment to provide support for development of EPICS database management tools. An object- oriented database (OODB) was chosen for two reasons: higher performance and the ability to smoothly manage objects of different types. 3 refs., 1 fig
Genetic Algorithm Tuned Fuzzy Logic Controller for Rotary Inverted Pendulum
Tzu-Chun Kuo
2013-06-01
Full Text Available In this study, a Genetic Algorithm (GA is proposed to search for the optimal input membership functions of the fuzzy logic controller. With the optimal membership function, the fuzzy logic controller can efficiently control a rotary inverted pendulum. The advantage of the proposed method is tuning the parameters of membership functions automatically rather than tuning them manually. In genetic algorithm, these parameters are converted to a chromosome which is encoded into a binary string. Because the membership functions are symmetric to zero, the length of each chromosome could be reduced by half. The computation time will also be shorter with the shorter chromosomes. Moreover, the roulette wheel selection is chosen as reproduction operator and one-point crossover operator and random mutation operator are also used. After the genetic algorithm completes searching for optimal parameters, the optimal membership function will be introduced to the fuzzy logic controller. Finally, simulation results show that the proposed GA-tuned fuzzy logic controller is effective for the rotary inverted pendulum control system with robust stabilization capability.
Control of Complex Systems Using Bayesian Networks and Genetic Algorithm
Marwala, Tshilidzi
2007-01-01
A method based on Bayesian neural networks and genetic algorithm is proposed to control the fermentation process. The relationship between input and output variables is modelled using Bayesian neural network that is trained using hybrid Monte Carlo method. A feedback loop based on genetic algorithm is used to change input variables so that the output variables are as close to the desired target as possible without the loss of confidence level on the prediction that the neural network gives. The proposed procedure is found to reduce the distance between the desired target and measured outputs significantly.
Algorithms and Methods for High-Performance Model Predictive Control
Frison, Gianluca
The goal of this thesis is to investigate algorithms and methods to reduce the solution time of solvers for Model Predictive Control (MPC). The thesis is accompanied with an open-source toolbox for High-Performance implementation of solvers for MPC (HPMPC), that contains the source code of all...... 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....
Control of the lighting system using a genetic algorithm
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.
Recursive estimation algorithms for power controls of wireless communication networks
Gang George YIN; Chin-An TAN; Le Yi WANG; Chengzhong XU
2008-01-01
Power control problems for wireless communication networks are investigated in direct-sequence codedivision multiple-access(DS/CDMA)channels.It is shown that the underlying problem can be formulated as a constrained optimization problem in a stochastic framework.For effective solutions to this optimization problem in real time,recursive algorithms of stochastic approximation type are developed that can solve the problem with unknown system components.Under broad conditions,convergence of the algorithms is established by using weak convergence methods.
Distributed autonomous systems: resource management, planning, and control algorithms
Smith, James F., III; Nguyen, ThanhVu H.
2005-05-01
Distributed autonomous systems, i.e., systems that have separated distributed components, each of which, exhibit some degree of autonomy are increasingly providing solutions to naval and other DoD problems. Recently developed control, planning and resource allocation algorithms for two types of distributed autonomous systems will be discussed. The first distributed autonomous system (DAS) to be discussed consists of a collection of unmanned aerial vehicles (UAVs) that are under fuzzy logic control. The UAVs fly and conduct meteorological sampling in a coordinated fashion determined by their fuzzy logic controllers to determine the atmospheric index of refraction. Once in flight no human intervention is required. A fuzzy planning algorithm determines the optimal trajectory, sampling rate and pattern for the UAVs and an interferometer platform while taking into account risk, reliability, priority for sampling in certain regions, fuel limitations, mission cost, and related uncertainties. The real-time fuzzy control algorithm running on each UAV will give the UAV limited autonomy allowing it to change course immediately without consulting with any commander, request other UAVs to help it, alter its sampling pattern and rate when observing interesting phenomena, or to terminate the mission and return to base. The algorithms developed will be compared to a resource manager (RM) developed for another DAS problem related to electronic attack (EA). This RM is based on fuzzy logic and optimized by evolutionary algorithms. It allows a group of dissimilar platforms to use EA resources distributed throughout the group. For both DAS types significant theoretical and simulation results will be presented.
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.
Attitude-Control Algorithm for Minimizing Maneuver Execution Errors
Acikmese, Behcet
2008-01-01
A G-RAC attitude-control algorithm is used to minimize maneuver execution error in a spacecraft with a flexible appendage when said spacecraft must induce translational momentum by firing (in open loop) large thrusters along a desired direction for a given period of time. The controller is dynamic with two integrators and requires measurement of only the angular position and velocity of the spacecraft. The global stability of the closed-loop system is guaranteed without having access to the states describing the dynamics of the appendage and with severe saturation in the available torque. Spacecraft apply open-loop thruster firings to induce a desired translational momentum with an extended appendage. This control algorithm will assist this maneuver by stabilizing the attitude dynamics around a desired orientation, and consequently minimize the maneuver execution errors.
Congestion control algorithm in large-delay uncertain networks
Fengjie YIN; Yuanwei JING; Yuanjiu GONG
2007-01-01
Based on Smith-fuzzy controller,a new active queue management(AQM)algorithm adaptable to the large-delay uncertain networks is presented.It can compensate the negative impact on the queue stability caused by the large delay,and it also maintains strong robustness under the condition of dynamic network fluid.Its stability is proven through Lyapunov method.Simulation results demonstrated that this method enables the queue length to converge at a preset value quickly and keeps the queue oscillation small.the simulation results also show that the scheme is very robust to disturbance under various network conditions and large delay and,in particular,the algorithm proposed outperforms the conventional PI control and fuzzy control when the network parameters and network delay change.
Backup Attitude Control Algorithms for the MAP Spacecraft
ODonnell, James R., Jr.; Andrews, Stephen F.; Ericsson-Jackson, Aprille J.; Flatley, Thomas W.; Ward, David K.; Bay, P. Michael
1999-01-01
The Microwave Anisotropy Probe (MAP) is a follow-on to the Differential Microwave Radiometer (DMR) instrument on the Cosmic Background Explorer (COBE) spacecraft. The MAP spacecraft will perform its mission, studying the early origins of the universe, in a Lissajous orbit around the Earth-Sun L(sub 2) Lagrange point. Due to limited mass, power, and financial resources, a traditional reliability concept involving fully redundant components was not feasible. This paper will discuss the redundancy philosophy used on MAP, describe the hardware redundancy selected (and why), and present backup modes and algorithms that were designed in lieu of additional attitude control hardware redundancy to improve the odds of mission success. Three of these modes have been implemented in the spacecraft flight software. The first onboard mode allows the MAP Kalman filter to be used with digital sun sensor (DSS) derived rates, in case of the failure of one of MAP's two two-axis inertial reference units. Similarly, the second onboard mode allows a star tracker only mode, using attitude and derived rate from one or both of MAP's star trackers for onboard attitude determination and control. The last backup mode onboard allows a sun-line angle offset to be commanded that will allow solar radiation pressure to be used for momentum management and orbit stationkeeping. In addition to the backup modes implemented on the spacecraft, two backup algorithms have been developed in the event of less likely contingencies. One of these is an algorithm for implementing an alternative scan pattern to MAP's nominal dual-spin science mode using only one or two reaction wheels and thrusters. Finally, an algorithm has been developed that uses thruster one shots while in science mode for momentum management. This algorithm has been developed in case system momentum builds up faster than anticipated, to allow adequate momentum management while minimizing interruptions to science. In this paper, each mode and
Algorithmic aspects of topology control problems for ad hoc networks
Liu, R. (Rui); Lloyd, E. L. (Errol L.); Marathe, M. V. (Madhav V.); Ramanathan, R. (Ram); Ravi, S. S.
2002-01-01
Topology control problems are concerned with the assignment of power values to nodes of an ad hoc network so that the power assignment leads to a graph topology satisfying some specified properties. This paper considers such problems under several optimization objectives, including minimizing the maximum power and minimizing the total power. A general approach leading to a polynomial algorithm is presented for minimizing maximum power for a class of graph properties, called monotone properties. The difficulty of generalizing the approach to properties that are not monoione is pointed out. Problems involving the minimization of total power are known to be NP-complete even for simple graph properties. A general approach that leads to an approximation algorithm for minimizing the total power for some monotone properties is presented. Using this approach, a new approximation algorithm for the problem of minimizing the total power for obtaining a 2-node-connected graph is obtained. It is shown that this algorithm provides a constant performance guarantee. Experimental results from an implementation of the approximation algorithm are also presented.
DR.C.SRINIVASA RAO
2013-01-01
Full Text Available This paper presents the implementation of load frequency control (LFC of hydrothermal system under restructured scenario employing fuzzy controlled genetic algorithm (FCGA. The concept of artificial intelligent techniques greatly helps in overcoming the disadvantages posed by the conventional controllers. Open transmission access and the evolving of more socialized companies for generation, transmission and distribution affects the formulation of LFC problem. So the traditional LFC system is modified to take into account the effect of bilateral contracts on the dynamics. Fuzzy logic is a powerful tool for dealing with imprecision and uncertainty while Genetic Algorithm is a potential tool for global optimization. A combinedtechnique involving both these techniques called as fuzzy controlled genetic algorithm has been developed to remove the limitations of these techniques and also improve the dynamic performance of the system over the existing conventional techniques. Simulation results show that the system employing fuzzy controlled genetic algorithm has better dynamic performance over the system with traditional integral controller.
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.
Robust Optimal Controller Design for Multimachine Systems using Genetic Algorithms
Dr.R.Lakshmipathi
2010-04-01
Full Text Available Power System Oscillation Controllers (PSOC are added to Excitation systems to enhance the damping during Low frequency oscillations. This paper provides a systematic approach to damp the low frequency oscillations observed in Three Machine Nine Bus Multimachine Power Systems based on Genetic Algorithm(GA.The Optimal Controller design problem is formulated as an optimization criterion comprising of Timedomain based objective function to compute the optimal controller parameters. The main objective is to minimize the integral squared error involving rotor speed deviation and power angle deviations. To validate the effective damping action of the proposed controller, Non linear Time domain simulations has been carried out in this work under wide variations in the system loading conditions. Also a comparative study has been done to show the robustness of the Genetic based controller over the conventionally designed Lead Lag controller.
A neuro-fuzzy controlling algorithm for wind turbine
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)
UAV Flight Control System Based on an Intelligent BEL Algorithm
Huangzhong Pu
2013-02-01
Full Text Available A novel intelligent control strategy based on a brain emotional learning (BEL algorithm is investigated in the application of the attitude control of a small unmanned aerial vehicle (UAV in this study. The BEL model imitates the emotional learning process in the amygdala‐ orbitofrontal (A‐O system of mammalian brains. Here it is used to develop the flight control system of the UAV. The control laws of elevator, aileron and rudder manipulators adopt the forms of traditional flight control laws, and three BEL models are used in above three control loops, to on‐ line regulate the control gains of each controller. Obviously, a BEL intelligent control system is self‐learning and self‐adaptive, which is important for UAVs when flight conditions change, while traditional flight control systems remain unchanged after design. In simulation, the UAV is on a flat flight and suddenly a wind disturbs it making it depart from the equilibrium state. In order to make the UAV recover to the original equilibrium state, the BEL intelligent control system is adopted. The simulation results illustrate that the BEL‐based intelligent flight control system has characteristics of better adaptability and stronger robustness, when compared with the traditional flight control system.
Control of transition state spectra: a variational algorithm
We propose to control the characteristics of transition state spectra by designing the initial state of a photochemical reaction. The method proceeds by introducing parameters into the (nonstationary) initial state wave function. The parameters are determined variationally to optimize a desired feature of the spectrum. One important application of this procedure is to reduce the unstructured background in a photoabsorption spectrum. In the resulting spectra, the contrast ratio of the resonance peaks to the background is dramatically increased, allowing a spectral quantization procedure to be used to assign the peaks. The algorithm can also be used to resolve overlapping peaks and to enhance specific progressions. As a theoretical tool, the variational algorithm can be viewed as a method to analyze the resonance structure of a given potential surface. We speculate that control of spectra can also be achieved in the laboratory, and suggest one possible scheme to do so. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)
A Concurrency Control Algorithm in Multi-Version Multilevel DBMS
ZHANGMin; FENGDengguo
2005-01-01
The conventional transaction concurrency control theory and mechanisms are challenged in the context of a multilevel DBMS (Data base management system). Not only the correctness of transaction processing, namely the serializability of the transaction histories, but also the security properties should be followed. These requirements include diminishing the timing covert channels and preventing the starving problem in high-level transactions' unlimited waiting. In this paper we present a timestamp order based concurrency control algorithm that produce serializable histories by correctly combining all the 1SR histories generated by different level schedulers. We also provide an implementation scheduler algorithm based on snapshots. This approach is free from timing covert channels and transactions of different security levels have the same privilege to execute. In addition, this approach does not require the existence of a global trusted scheduler. Instead, it can be built on enhanced untrusted traditional multi-version schedulers, with the supplement of appropriate process towards read-down operations.
Control Logic Algorithm for Medium Scale Wind Turbines
Osama Abdel Hakeem Abdel Sattar; R. R. Darwish; Saad Mohamed Ali Eid; Elsayed Mostafa Saad
2012-01-01
Recently, sustainable attention has been drawn to renewable energy sources. Wind energy systems as renewable source of energy have been extensively studied because of its benefits as an environmentally friendly clean energy, inexhaustible, safe and a low-cost for long term. Because of its unpredictable availability, power management control algorithms are essential to extract as much power as possible from the wind during its availability durations. This paper is motivated for proposing the m...
TECA : A Topology and Energy Control Algorithm for Sensor Networks
Busse, Marcel; Haenselmann, Thomas; Effelsberg, Wolfgang
2005-01-01
A main challenge in the field of sensor networks is energy efficiency to prolong the sensor's operational lifetime. Due to low-cost hardware, nodes' placement or hardware design, recharging might be impossible. Since most energy is spent for radio communication, many approaches exist that put sensor nodes into sleep mode with the communication radio turned off. In this paper, we propose a new Topology and Energy Control Algorithm called TECA. We will show the performance of TECA by means of e...
A comparison of three self-tuning control algorithms developed for the Bristol-Babcock controller
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.
A comparison of three self-tuning control algorithms developed for the Bristol-Babcock controller
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.
A comparison of three self-tuning control algorithms developed for the Bristol-Babcock controller
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
New Iterative Learning Control Algorithms Based on Vector Plots Analysis1）
XIESheng-Li; TIANSen-Ping; XIEZhen-Dong
2004-01-01
Based on vector plots analysis, this paper researches the geometric frame of iterativelearning control method. New structure of iterative learning algorithms is obtained by analyzingthe vector plots of some general algorithms. The structure of the new algorithm is different fromthose of the present algorithms. It is of faster convergence speed and higher accuracy. Simulationspresented here illustrate the effectiveness and advantage of the new algorithm.
Comparison of Adaptive Antenna Arrays Controlled by Gradient Algorithms
Z. Raida
1994-09-01
Full Text Available The paper presents the Simple Kalman filter (SKF that has been designed for the control of digital adaptive antenna arrays. The SKF has been applied to the pilot signal system and the steering vector one. The above systems based on the SKF are compared with adaptive antenna arrays controlled by the classical LMS and the Variable Step Size (VSS LMS algorithms and by the pure Kalman filter. It is shown that the pure Kalman filter is the most convenient for the control of the adaptive arrays because it does not require any a priori information about noise statistics and excels in high rate of convergence and low misadjustment. Extremely high computational requirements are drawback of this filter. Hence, if low computational power of signal processors is at the disposal, the SKF is recommended to be used. Computational requirements of the SKF are of the same order as the classical LMS algorithm exhibits. On the other hand, all the important features of the pure Kalman filter are inherited by the SKF. The paper shows that presented Kalman filters can be regarded as special gradient algorithms. That is why they can be compared with the LMS family.
Tanya Gurieva
Full Text Available Nosocomial infection rates due to antibiotic-resistant bacteriae, e.g., methicillin-resistant Staphylococcus aureus (MRSA remain high in most countries. Screening for MRSA carriage followed by barrier precautions for documented carriers (so-called screen and isolate (S&I has been successful in some, but not all settings. Moreover, different strategies have been proposed, but comparative studies determining their relative effects and costs are not available. We, therefore, used a mathematical model to evaluate the effect and costs of different S&I strategies and to identify the critical parameters for this outcome. The dynamic stochastic simulation model consists of 3 hospitals with general wards and intensive care units (ICUs and incorporates readmission of carriers of MRSA. Patient flow between ICUs and wards was based on real observations. Baseline prevalence of MRSA was set at 20% in ICUs and hospital-wide at 5%; ranges of costs and infection rates were based on published data. Four S&I strategies were compared to a do-nothing scenario: S&I of previously documented carriers ("flagged" patients; S&I of flagged patients and ICU admissions; S&I of flagged and group of "frequent" patients; S&I of all hospital admissions (universal screening. Evaluated levels of efficacy of S&I were 10%, 25%, 50% and 100%. Our model predicts that S&I of flagged and S&I of flagged and ICU patients are the most cost-saving strategies with fastest return of investment. For low isolation efficacy universal screening and S&I of flagged and "frequent" patients may never become cost-saving. Universal screening is predicted to prevent hardly more infections than S&I of flagged and "frequent" patients, albeit at higher costs. Whether an intervention becomes cost-saving within 10 years critically depends on costs per infection in ICU, costs of screening and isolation efficacy.
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
EFFICIENT FAN-OUT RF VECTOR CONTROL ALGORITHM *
A new RF vector control algorithm for fan-out power distribution using reactive transmission line circuit parameters for maximum power efficiency is presented. This control with fan-out power distribution system is considered valuable for large scale SRF accelerator systems to reduce construction costs and save on operating costs. In a fan-out RF power distribution system, feeding multiple accelerating cavities with a single RF power generator can be accomplished by adjusting phase delays between the load cavities and reactive loads at the cavity inputs for independent control of cavity RF voltage vectors. In this approach, the RF control parameters for a set of specified cavity RF voltage vectors is determined for an entire fan-out system. The reactive loads and phase shifts can be realized using high power RF phase shifters.
Diversity Controlling Genetic Algorithm for Order Acceptance and Scheduling Problem
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.
Implementing Genetic Algorithms on Arduino Micro-Controllers
Alves, Nuno
2010-01-01
Since their conception in 1975, Genetic Algorithms have been an extremely popular approach to find exact or approximate solutions to optimization and search problems. Over the last years there has been an enhanced interest in the field with related techniques, such as grammatical evolution, being developed. Unfortunately, work on developing genetic optimizations for low-end embedded architectures hasn't embraced the same enthusiasm. This short paper tackles that situation by demonstrating how genetic algorithms can be implemented in Arduino Duemilanove, a 16 MHz open-source micro-controller, with limited computation power and storage resources. As part of this short paper, the libraries used in this implementation are released into the public domain under a GPL license.
A cooperative control algorithm for camera based observational systems.
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.
Hu, Helen
2012-01-01
Few people set out to become admissions counselors, say people in the profession. But the field is requiring skills that are more demanding and varied than ever. And at a time when universities are looking especially hard at the bottom line, people in admissions need to constantly learn new things and make themselves indispensable. Counselors…
A Digital Control Algorithm for Magnetic Suspension Systems
Britton, Thomas C.
1996-01-01
An ongoing program exists to investigate and develop magnetic suspension technologies and modelling techniques at NASA Langley Research Center. Presently, there is a laboratory-scale large air-gap suspension system capable of five degree-of-freedom (DOF) control that is operational and a six DOF system that is under development. Those systems levitate a cylindrical element containing a permanent magnet core above a planar array of electromagnets, which are used for levitation and control purposes. In order to evaluate various control approaches with those systems, the Generic Real-Time State-Space Controller (GRTSSC) software package was developed. That control software package allows the user to implement multiple control methods and allows for varied input/output commands. The development of the control algorithm is presented. The desired functionality of the software is discussed, including the ability to inject noise on sensor inputs and/or actuator outputs. Various limitations, common issues, and trade-offs are discussed including data format precision; the drawbacks of using either Direct Memory Access (DMA), interrupts, or program control techniques for data acquisition; and platform dependent concerns related to the portability of the software, such as memory addressing formats. Efforts to minimize overall controller loop-rate and a comparison of achievable controller sample rates are discussed. The implementation of a modular code structure is presented. The format for the controller input data file and the noise information file is presented. Controller input vector information is available for post-processing by mathematical analysis software such as MATLAB1.
Navigation Algorithm Using Fuzzy Control Method in Mobile Robotics
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.
An Active Learning Algorithm for Control of Epidural Electrostimulation.
Desautels, Thomas A; Choe, Jaehoon; Gad, Parag; Nandra, Mandheerej S; Roy, Roland R; Zhong, Hui; Tai, Yu-Chong; Edgerton, V Reggie; Burdick, Joel W
2015-10-01
Epidural electrostimulation has shown promise for spinal cord injury therapy. However, finding effective stimuli on the multi-electrode stimulating arrays employed requires a laborious manual search of a vast space for each patient. Widespread clinical application of these techniques would be greatly facilitated by an autonomous, algorithmic system which choses stimuli to simultaneously deliver effective therapy and explore this space. We propose a method based on GP-BUCB, a Gaussian process bandit algorithm. In n = 4 spinally transected rats, we implant epidural electrode arrays and examine the algorithm's performance in selecting bipolar stimuli to elicit specified muscle responses. These responses are compared with temporally interleaved intra-animal stimulus selections by a human expert. GP-BUCB successfully controlled the spinal electrostimulation preparation in 37 testing sessions, selecting 670 stimuli. These sessions included sustained autonomous operations (ten-session duration). Delivered performance with respect to the specified metric was as good as or better than that of the human expert. Despite receiving no information as to anatomically likely locations of effective stimuli, GP-BUCB also consistently discovered such a pattern. Further, GP-BUCB was able to extrapolate from previous sessions' results to make predictions about performance in new testing sessions, while remaining sufficiently flexible to capture temporal variability. These results provide validation for applying automated stimulus selection methods to the problem of spinal cord injury therapy. PMID:25974925
A simplified rate control algorithm for H.264/SVC
Zhang, Guang Y.; Abdelazim, Abdelrahman; Mein, Stephen J.; Varley, Martin R.; Ait-Boudaoud, Djamel
2011-06-01
The objective of scalable video coding is to enable the generation of a unique bitstream that can adapt to various bitrates, transmission channels and display capabilities. The scalability is categorised in terms of temporal, spatial, and quality. Effective Rate Control (RC) has important ramifications for coding efficiency, and also channel bandwidth and buffer constraints in real-time communication. The main target of RC is to reduce the disparity between the actual and target bit-rates. In order to meet the target bitrate, a predicted Mean of Absolute Difference (MAD) between frames is used in a rate-quantisation model to obtain the Quantisation Parameter (QP) for encoding the current frame. The encoding process exploits the interdependencies between video frames; therefore the MAD does not change abruptly unless the scene changes significantly. After the scene change, the MAD will maintain a stable slow increase or decrease. Based on this observation, we developed a simplified RC algorithm. The scheme is divided in two steps; firstly, we predict scene changes, secondly, in order to suppress the visual quality, we limit the change in QP value between two frames to an adaptive range. This limits the need to use the rate-quantisation model to those situations where the scene changes significantly. To assess the proposed algorithm, comprehensive experiments were conducted. The experimental results show that the proposed algorithm significantly reduces encoding time whilst maintaining similar rate distortion performance, compared to both the H.264/SVC reference software and recently reported work.
Efficient computer algebra algorithms for polynomial matrices in control design
Baras, J. S.; Macenany, D. C.; Munach, R.
1989-01-01
The theory of polynomial matrices plays a key role in the design and analysis of multi-input multi-output control and communications systems using frequency domain methods. Examples include coprime factorizations of transfer functions, cannonical realizations from matrix fraction descriptions, and the transfer function design of feedback compensators. Typically, such problems abstract in a natural way to the need to solve systems of Diophantine equations or systems of linear equations over polynomials. These and other problems involving polynomial matrices can in turn be reduced to polynomial matrix triangularization procedures, a result which is not surprising given the importance of matrix triangularization techniques in numerical linear algebra. Matrices with entries from a field and Gaussian elimination play a fundamental role in understanding the triangularization process. In the case of polynomial matrices, matrices with entries from a ring for which Gaussian elimination is not defined and triangularization is accomplished by what is quite properly called Euclidean elimination. Unfortunately, the numerical stability and sensitivity issues which accompany floating point approaches to Euclidean elimination are not very well understood. New algorithms are presented which circumvent entirely such numerical issues through the use of exact, symbolic methods in computer algebra. The use of such error-free algorithms guarantees that the results are accurate to within the precision of the model data--the best that can be hoped for. Care must be taken in the design of such algorithms due to the phenomenon of intermediate expressions swell.
Indeterminate EMU admissions: does repeating the admission help?
Zarkou, Srijana; Grade, Madeline; Hoerth, Matthew T; Noe, Katherine H; Sirven, Joseph I; Drazkowski, Joseph F
2011-04-01
Epilepsy monitoring unit (EMU) admissions during 2007-2009 at Mayo Clinic Hospital Arizona were reviewed. Of the 106 indeterminate admissions, 13 (12%) went on to have a second admission. During the second admission, 8 (62%) were diagnosed. Five patients went on to have a third or fourth admission, with none of them receiving a diagnosis. Nineteen (18%) patients had ambulatory EEG monitoring after an indeterminate admission, with only one (5%) receiving a diagnosis after ambulatory EEG monitoring. Even in patients who were initially indeterminate, medication management changed 37% of the time. Admission to the EMU was helpful for spell classification, with 80% of the patients receiving a diagnosis after the first admission. Based on this study, a second admission should be considered if no diagnosis is reached after the first admission. If no diagnosis is made after the second EMU admission, subsequent admissions are unlikely to produce a definitive diagnosis. PMID:21441070
Carmen Jan
Full Text Available OBJECTIVE: To evaluate the association of a nationwide comprehensive smoking ban (CSB and tobacco tax increase (TTI on the risk of acute myocardial infarctions (AMI in Panama for the period of 2006 - 2010 using hospital admissions data. METHODS: Data of AMI cases was gathered from public and private hospitals in the country for the period of January 1, 2006 to December 31, 2010. The number of AMI cases was calculated on a monthly basis. The risk of AMI was estimated for the pre-CSB period (January 2006 to April 2008 and was used as a reference point. Three post-intervention periods were examined: (1 post-CSB from May 2008 to April 2009 (12 months; (2 post-CSB from May 2009 to November 2009 (7 months; and (3 post-TTI from December 2009 to December 2010 (13 months. Relative risks (RR of AMI were estimated for each post intervention periods by using a Poisson regression model. Mortality registries for the country attributed to myocardial infarction (MI were obtained from January 2001 to December 2012. The annual percentage change (APC of the number of deaths from MI was calculated using Joinpoint regression analysis. RESULTS: A total sample size of 2191 AMI cases was selected (monthly mean number of cases 36.52 ± 8.24 SD. Using the pre-CSB as a reference point (RR = 1.00, the relative risk of AMI during the first CSB period, the second CSB period and post-TTI were 0.982, 1.049, and 0.985, respectively. The APC of deaths from MI from January 2001 to April 2008 was 0.5%. From January 2001 to June 2010 the APC trend was 0.47% and from July 2010 to December 2012 the APC was -0.3%. CONCLUSIONS: The implementation of a CSB and TTI in Panama were associated with a decrease in tobacco consumption and a reduction of the RR of AMI.
The product composition control system at Savannah River: Statistical process control algorithm
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
Naeim Farouk
2012-11-01
Full Text Available The degree of speed control of ship machinery effects on the economics and optimization of the machinery configuration and operation. All marine vessel ranging need some sort of speed control system to control and govern the speed of the marine diesel engines. The main focus of this study is to apply and comparative between two specific soft-computing techniques. Fuzzy logic controller and genetic algorithm to design and tuning of PID controller for applied on speed control system of marine diesel engine to get an output with better dynamic and static performance. Simulation results show that the response of system when using genetic algorithm is better and faster than when using fuzzy tuning PID controller.
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
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
Motion Control Algorithms for a Free-swimming Biomimetic Robot Fish
YUJun-Zhi; CHENEr-Kui; WANGShuo; TANMin
2005-01-01
A practical motion control strategy for a radio-controlled, 4-1ink and free-swimming biomimetic robot fish is presented. Based on control performance of the fish the fish's motion control task is decomposed into on-line speed control and orientation control. The speed control algorithm is implemented by using piecewise control, and orientation control is realized by fuzzy logic. Combining with step control and fuzzy control, a point-to-point (PTP) control algorithm is proposed and applied to the closed-loop experimental system that uses a vision-based position sensing subsystem to provide feedback. Experiments confirm the reliability and effectiveness of the presented algorithms.
Algorithms to Solve Stochastic H2/H∞ Control with State-Dependent Noise
Ming Gao
2014-01-01
Full Text Available This paper is concerned with the algorithms which solve H2/H∞ control problems of stochastic systems with state-dependent noise. Firstly, the algorithms for the finite and infinite horizon H2/H∞ control of discrete-time stochastic systems are reviewed and studied. Secondly, two algorithms are proposed for the finite and infinite horizon H2/H∞ control of continuous-time stochastic systems, respectively. Finally, several numerical examples are presented to show the effectiveness of the algorithms.
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
Model algorithm control using neural networks for input delayed nonlinear control system
Yuanliang Zhang; Kil To Chong
2015-01-01
The performance of the model algorithm control method is partial y based on the accuracy of the system’s model. It is diffi-cult to obtain a good model of a nonlinear system, especial y when the nonlinearity is high. Neural networks have the ability to“learn”the characteristics of a system through nonlinear mapping to rep-resent nonlinear functions as wel as their inverse functions. This paper presents a model algorithm control method using neural net-works for nonlinear time delay systems. Two neural networks are used in the control scheme. One neural network is trained as the model of the nonlinear time delay system, and the other one pro-duces the control inputs. The neural networks are combined with the model algorithm control method to control the nonlinear time delay systems. Three examples are used to il ustrate the proposed control method. The simulation results show that the proposed control method has a good control performance for nonlinear time delay systems.
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.
Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms
Knudson, Matthew D.; Colby, Mitchell; Tumer, Kagan
2014-01-01
Dynamic flight environments in which objectives and environmental features change with respect to time pose a difficult problem with regards to planning optimal flight paths. Path planning methods are typically computationally expensive, and are often difficult to implement in real time if system objectives are changed. This computational problem is compounded when multiple agents are present in the system, as the state and action space grows exponentially. In this work, we use cooperative coevolutionary algorithms in order to develop policies which control agent motion in a dynamic multiagent unmanned aerial system environment such that goals and perceptions change, while ensuring safety constraints are not violated. Rather than replanning new paths when the environment changes, we develop a policy which can map the new environmental features to a trajectory for the agent while ensuring safe and reliable operation, while providing 92% of the theoretically optimal performance
RETRACTED ARTICLE: Dynamic voltage restorer controller using grade algorithm
S. Deepa
2015-12-01
Full Text Available This paper deals with the terminology and various issues about power quality problems. This problem occurs owing to voltage sag, swell, harmonics, and surges. The sustained overvoltage and undervoltage originated from power system may often damage/or disrupt computerized process. Voltage sags and harmonics disturb the power quality and this can be overcome by custom power device called dynamic voltage restorer (DVR. The DVR is normally installed between the source voltage and critical or sensitive load. The vital role of DVR depends on the efficiency of the control technique involved in switching circuit of the inverter. In this paper, Combination of improved grade algorithm with fuzzy membership function is used to decide the Proportional-Integral coefficients. The DVR works well both in balanced and unbalanced conditions of voltages. The simulation results show the efficiency of the proposed method.
Controlling Risk Exposure in Periodic Environments: A Genetic Algorithm Approach
Navarro, Emeterio
2007-01-01
In this paper, we compare the performance of different agent's investment strategies in an investment scenario with periodic returns and different types and levels of noise. We consider an investment model, where an agent decides the percentage of budget to risk at each time step. Afterwards, agent's investment is evaluated in the market via a return on investment (RoI), which we assume is a stochastic process with unknown periodicities and different levels of noise. To control the risk exposure, we investigate approaches based on: technical analysis (Moving Least Squares, MLS), and evolutionary computation (Genetic Algorithms, GA). In our comparison, we also consider two reference strategies for zero-knowledge and complete-knowledge behaviors, respectively. In our approach, the performance of a strategy corresponds to the average budget that can be obtained with this strategy over a certain number of time steps. To this end, we perform some computer experiments, where for each strategy the budget obtained af...
Comparative Analysis of Congestion Control Algorithms Using ns-2
Patel, Sanjeev; Garg, Arjun; Mehrotra, Prateek; Chhabra, Manish
2012-01-01
In order to curtail the escalating packet loss rates caused by an exponential increase in network traffic, active queue management techniques such as Random Early Detection (RED) have come into picture. Flow Random Early Drop (FRED) keeps state based on instantaneous queue occupancy of a given flow. FRED protects fragile flows by deterministically accepting flows from low bandwidth connections and fixes several shortcomings of RED by computing queue length during both arrival and departure of the packet. Stochastic Fair Queuing (SFQ) ensures fair access to network resources and prevents a busty flow from consuming more than its fair share. In case of (Random Exponential Marking) REM, the key idea is to decouple congestion measure from performance measure (loss, queue length or delay). Stabilized RED (SRED) is another approach of detecting nonresponsive flows. In this paper, we have shown a comparative analysis of throughput, delay and queue length for the various congestion control algorithms RED, SFQ and REM...
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
Dynamic Fuzzy Logic Control of Genetic Algorithm Probabilities
Huijuan Guo; Yi Feng; Fei Hao; Shengtong Zhong; Shuai Li
2014-01-01
Genetic Algorithms are traditionally used to solve combinatorial optimization problems. The implementation of Genetic Algorithms involves of using genetic operators (crossover, mutation, selection, etc.). Meanwhile, paramters (such as population size, probabilities of crossover and mutation) of Genetic Algorithm need to be chosen or tuned. In this paper, we propose a hybrid Fuzzy-Genetic Algorithm (FLGA) approach to solve the multiprocessor scheduling problem. Based on traditional Genetic Alg...
AUTOMATION OF PLC PROGRAMMING WHEN IMPLEMENTING ALGORITHMS OF GUARANTEEING CONTROL
M. V. Levinskyi
2015-05-01
Full Text Available During developing programs for programmable logic controllers (PLCs the concept of model-oriented design is increasingly used. In particular, usage of Simulink PLC Coder is giving the opportunity to get SCL program codefrom Simulink model which contains certain dynamic elements. Then, for example, this SCL code can be transformed to functional blocks of the Simatic S7-300 (VIPA 300 PLC. This significantly reduces the timerequired to develop code in the language of SCL and reduces requirements for specialists’ qualification when developing control systems. In this article we provide an example of PLC programming automation whenimplementing algorithms of guaranteeing control (AGC. For certain types of technological processes it is typical to contain monotonically increasing function of the effectiveness with fixed one-way restriction in regulations. Forexample, in the grinders, presses, extruders the load current of the drive is stabilized using the change of feed. Energy efficiency of these plants will increase with increasing of the set point (SP to the controller of the drive loadcurrent stabilization loop. However, an increase in SP increases the probability of triggering appropriate protection, for example, as a result of random changes in the properties of raw materials. Therefore, to avoid this accident, thepower of driving motors is often unreasonably overrated. And in this case they are used with currents equal to the half of rated.Systems of guaranteeing control (SGC are used to solve the contradiction between the need to improvethe efficiency and increasing probability of an accident.
Conrad, Finn; Zhou, Jianjun; Gabacik, Andrzej; Stecki, Jacek
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....
A predictive control algorithm for an active three-phase power filter
R.V. Vlasenko; Bialobrzeski, O. V.
2014-01-01
The paper deals with grid connection circuits for active filters, structures of active power filter control systems, and methods based on full capacity components determination. The existing structures of active power filter control and control algorithm adjustment for valve commutation loss reduction are analyzed. A predictive control algorithm for an active three-phase power filter is introduced.
Meysam Gheisarnezhad
2015-01-01
Full Text Available Fractional-order PID (FOPID controller is a generalization of standard PID controller using fractional calculus. Compared with the Standard PID controller, two adjustable variables “differential order” and “integral order” are added to the PID controller.Three tank system is a nonlinear multivariable process that is a good prototype of chemical industrial processes. Cuckoo Optimization Algorithm (COA, that was recently introduced has shown its good performance in optimization problems. In this study, Improved Cuckoo Optimization Algorithm (ICOA has been presented. The aim of the paper is to compare different controllers tuned with a Improved Cuckoo Optimization Algorithm (ICOA for Three Tank System. In order to compare the performance of the optimized FOPID controller with other controllers, Genetic Algorithm(GA, Particle swarm optimization (PSO, Cuckoo Optimization Algorithm (COA and Imperialist Competitive Algorithm (ICA.
Sukanta Nama
2016-04-01
Full Text Available Differential evolution (DE is an effective and powerful approach and it has been widely used in different environments. However, the performance of DE is sensitive to the choice of control parameters. Thus, to obtain optimal performance, time-consuming parameter tuning is necessary. Backtracking Search Optimization Algorithm (BSA is a new evolutionary algorithm (EA for solving real-valued numerical optimization problems. An ensemble algorithm called E-BSADE is proposed which incorporates concepts from DE and BSA. The performance of E-BSADE is evaluated on several benchmark functions and is compared with basic DE, BSA and conventional DE mutation strategy.
A Scheduling Algorithm Based on Communication Delay for Wireless Network Control System
Jun Wang
2012-09-01
Full Text Available In this study, a scheduling algorithm based on communication delay is proposed. This scheduling algorithm can tolerate delay of periodic communication tasks in wireless network control system. It resolves real-time problem of periodic communication tasks in wireless network control system and partly reduces overtime phenomenon of periodic communication tasks caused by delay in wireless network. At the same time, the nonlinear programming model is built for solving scheduling timetable based on the proposed scheduling algorithm. Finally, the performance of the proposed scheduling algorithm is evaluated by an application example. The statistics results show that it is more effective than traditional scheduling algorithms in wireless network control system.
Kalaivani
2013-09-01
Full Text Available This paper presents concurrent vibration control of a laboratory scaled vibration isolator platform with Active Force Control (AFC using Iterative Learning Algorithm (ILA. The work investigates the performance of the traditional Proportional Integral Derivative Controller (PIDC with and without AFC using ILA for vibration suppression. The physical single degree of freedom quarter car has been interfaced with a personal computer using a National Instruments data acquisition card NI USB 6008. The controllers are designed and simulated using LabVIEW simulation software. The results infer that the PIDC with AFC using ILA works superior than the PIDC.
Double Motor Coordinated Control Based on Hybrid Genetic Algorithm and CMAC
Cao, Shaozhong; Tu, Ji
A novel hybrid cerebellar model articulation controller (CMAC) and online adaptive genetic algorithm (GA) controller is introduced to control two Brushless DC motor (BLDCM) which applied in a biped robot. Genetic Algorithm simulates the random learning among the individuals of a group, and CMAC simulates the self-learning of an individual. To validate the ability and superiority of the novel algorithm, experiments have been done in MATLAB/SIMULINK. Analysis among GA, hybrid GA-CMAC and CMAC feed-forward control is also given. The results prove that the torque ripple of the coordinated control system is eliminated by using the hybrid GA-CMAC algorithm.
Admissible and Restrained Revision
Booth, R; 10.1613/jair.1874
2011-01-01
As partial justification of their framework for iterated belief revision Darwiche and Pearl convincingly argued against Boutiliers natural revision and provided a prototypical revision operator that fits into their scheme. We show that the Darwiche-Pearl arguments lead naturally to the acceptance of a smaller class of operators which we refer to as admissible. Admissible revision ensures that the penultimate input is not ignored completely, thereby eliminating natural revision, but includes the Darwiche-Pearl operator, Nayaks lexicographic revision operator, and a newly introduced operator called restrained revision. We demonstrate that restrained revision is the most conservative of admissible revision operators, effecting as few changes as possible, while lexicographic revision is the least conservative, and point out that restrained revision can also be viewed as a composite operator, consisting of natural revision preceded by an application of a "backwards revision" operator previously studied by Papini. ...
Dynamic Fuzzy Logic Control of GeneticAlgorithm Probabilities
Feng, Yi
2008-01-01
Genetic algorithms are commonly used to solve combinatorial optimizationproblems. The implementation evolves using genetic operators (crossover, mutation,selection, etc.). Anyway, genetic algorithms like some other methods have parameters(population size, probabilities of crossover and mutation) which need to be tune orchosen.In this paper, our project is based on an existing hybrid genetic algorithmworking on the multiprocessor scheduling problem. We propose a hybrid Fuzzy-Genetic Algorithm ...
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…
High order single step time delay compensation algorithm for structural active control
王焕定; 耿淑伟; 王伟
2002-01-01
The optimal instantaneous high order single step algorithm for active control is first discussed andthen, the n + 1 time step controlling force vector of the instantaneous optimal algorithm is derived from way of ntime state vector. An estimating algorithm, is developed from this to solve the problem of active control withtime delay compensation. The estimating algorithm based on this high order single step β method (HSM) foun-dation, is proven by simulation and experiment analysis, to be a valid solution to problem of active control withtime delay compensation.