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
Institute of Scientific and Technical Information of China (English)
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
Institute of Scientific and Technical Information of China (English)
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
Institute of Scientific and Technical Information of China (English)
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
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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...
Institute of Scientific and Technical Information of China (English)
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
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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
Institute of Scientific and Technical Information of China (English)
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
DEFF Research Database (Denmark)
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
Institute of Scientific and Technical Information of China (English)
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
Directory of Open Access Journals (Sweden)
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
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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
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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
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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
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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
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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
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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
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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
DEFF Research Database (Denmark)
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
Directory of Open Access Journals (Sweden)
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
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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
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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
Institute of Scientific and Technical Information of China (English)
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
Institute of Scientific and Technical Information of China (English)
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
International Nuclear Information System (INIS)
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
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
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
DEFF Research Database (Denmark)
Midtgaard, Jan; Van Horn, David
We give the first direct subcubic algorithm for performing control flow analysis of higher-order functional programs. Despite the long held belief that inclusion-based flow analysis could not surpass the ``cubic bottleneck, '' we apply known set compression techniques to obtain an algorithm...... that runs in time O(n^3/log n) on a unit cost random-access memory model machine. Moreover, we refine the initial flow analysis into two more precise analyses incorporating notions of reachability. We give subcubic algorithms for these more precise analyses and relate them to an existing analysis from...
SERVICE-AWARE BASED FUZZY ADMISSION CONTROL SCHEME IN MULTI-SERVICE NETWORKS
Institute of Scientific and Technical Information of China (English)
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
DEFF Research Database (Denmark)
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...
DEFF Research Database (Denmark)
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
Energy Technology Data Exchange (ETDEWEB)
Hsieh, Scott S., E-mail: sshsieh@stanford.edu [Department of Radiology, Stanford University, Stanford, California 94305 and Department of Electrical Engineering, Stanford University, Stanford, California 94305 (United States); Pelc, Norbert J. [Department of Radiology, Stanford University, Stanford California 94305 and Department of Bioengineering, Stanford University, Stanford, California 94305 (United States)
2014-06-15
Purpose: The authors describe algorithms to control dynamic attenuators in CT and compare their performance using simulated scans. Dynamic attenuators are prepatient beam shaping filters that modulate the distribution of x-ray fluence incident on the patient on a view-by-view basis. These attenuators can reduce dose while improving key image quality metrics such as peak or mean variance. In each view, the attenuator presents several degrees of freedom which may be individually adjusted. The total number of degrees of freedom across all views is very large, making many optimization techniques impractical. The authors develop a theory for optimally controlling these attenuators. Special attention is paid to a theoretically perfect attenuator which controls the fluence for each ray individually, but the authors also investigate and compare three other, practical attenuator designs which have been previously proposed: the piecewise-linear attenuator, the translating attenuator, and the double wedge attenuator. Methods: The authors pose and solve the optimization problems of minimizing the mean and peak variance subject to a fixed dose limit. For a perfect attenuator and mean variance minimization, this problem can be solved in simple, closed form. For other attenuator designs, the problem can be decomposed into separate problems for each view to greatly reduce the computational complexity. Peak variance minimization can be approximately solved using iterated, weighted mean variance (WMV) minimization. Also, the authors develop heuristics for the perfect and piecewise-linear attenuators which do not requirea priori knowledge of the patient anatomy. The authors compare these control algorithms on different types of dynamic attenuators using simulated raw data from forward projected DICOM files of a thorax and an abdomen. Results: The translating and double wedge attenuators reduce dose by an average of 30% relative to current techniques (bowtie filter with tube current
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
Directory of Open Access Journals (Sweden)
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
Institute of Scientific and Technical Information of China (English)
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
Directory of Open Access Journals (Sweden)
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
Institute of Scientific and Technical Information of China (English)
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
Directory of Open Access Journals (Sweden)
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
Directory of Open Access Journals (Sweden)
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.
Directory of Open Access Journals (Sweden)
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
Institute of Scientific and Technical Information of China (English)
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
Institute of Scientific and Technical Information of China (English)
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
Directory of Open Access Journals (Sweden)
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
Institute of Scientific and Technical Information of China (English)
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
International Nuclear Information System (INIS)
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
Energy Technology Data Exchange (ETDEWEB)
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
Institute of Scientific and Technical Information of China (English)
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
Institute of Scientific and Technical Information of China (English)
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
Institute of Scientific and Technical Information of China (English)
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.
Directory of Open Access Journals (Sweden)
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
Institute of Scientific and Technical Information of China (English)
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.
Directory of Open Access Journals (Sweden)
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
Institute of Scientific and Technical Information of China (English)
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
Energy Technology Data Exchange (ETDEWEB)
Sun, Wen [School of Information and Mathematics, Yangtze University, Jingzhou 434023 (China); Lü, Jinhu [Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190 (China); Chen, Shihua [College of Mathematics and Statistics, Wuhan University, Wuhan 430072 (China); Yu, Xinghuo [School of Electrical and Computer Engineering, RMIT University, Melbourne VIC 3001 (Australia)
2014-03-15
In this paper, we further investigate the synchronization of complex dynamical network via pinning control in which a selection of nodes are controlled at discrete times. Different from most existing work, the pinning control algorithms utilize only the impulsive signals at discrete time instants, which may greatly improve the communication channel efficiency and reduce control cost. Two classes of algorithms are designed, one for strongly connected complex network and another for non-strongly connected complex network. It is suggested that in the strongly connected network with suitable coupling strength, a single controller at any one of the network's nodes can always pin the network to its homogeneous solution. In the non-strongly connected case, the location and minimum number of nodes needed to pin the network are determined by the Frobenius normal form of the coupling matrix. In addition, the coupling matrix is not necessarily symmetric or irreducible. Illustrative examples are then given to validate the proposed pinning impulsive control algorithms.
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
DEFF Research Database (Denmark)
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
Directory of Open Access Journals (Sweden)
Luigi Alcuri
2004-12-01
Full Text Available This paper presents a method for admitting voice calls in Telephony over IP (ToIP scenarios. This method, called QoS-Weighted CAC, aims to guarantee Quality of Service to telephony applications. We use a measurement-based call admission control algorithm, which detects network congested links through a feedback on overall link utilization. This feedback is based on the measures of packet delivery latencies related to voice over IP connections at the edges of the transport network. In this way we introduce a close loop control method, which is able to auto-adapt the quality margin on the basis of network load and specific service level requirements. Moreover we evaluate the difference in performance achieved by different Queue management configurations to guarantee Quality of Service to telephony applications, in which our goal was to evaluate the weight of edge router queue configuration in complex and real-like telephony over IP scenario. We want to compare many well-know queue scheduling algorithms, such as SFQ, WRR, RR, WIRR, and Priority. This comparison aims to locate queue schedulers in a more general control scheme context where different elements such as DiffServ marking and Admission control algorithms contribute to the overall Quality of Service required by real-time voice conversations. By means of software simulations we want to compare this solution with other call admission methods already described in scientific literature in order to locate this proposed method in a more general control scheme context. On the basis of the results we try to evidence the possible advantages of this QoS-Weighted solution in comparison with other similar CAC solutions ( in particular Measured Sum, Bandwidth Equivalent with Hoeffding Bounds, and Simple Measure CAC, on the planes of complexity, stability, management, tune-ability to service level requirements, and compatibility with actual network implementation.
Simulation research on control algorithm of differential pressure casting process
Institute of Scientific and Technical Information of China (English)
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...
Energy Technology Data Exchange (ETDEWEB)
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
Institute of Scientific and Technical Information of China (English)
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
Institute of Scientific and Technical Information of China (English)
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
Directory of Open Access Journals (Sweden)
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
DEFF Research Database (Denmark)
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
International Nuclear Information System (INIS)
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
Institute of Scientific and Technical Information of China (English)
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
DEFF Research Database (Denmark)
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
Directory of Open Access Journals (Sweden)
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
Energy Technology Data Exchange (ETDEWEB)
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.
Directory of Open Access Journals (Sweden)
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
Institute of Scientific and Technical Information of China (English)
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
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
Xuhui Bu
2012-01-01
Full Text Available The convergence of model-free adaptive control (MFAC algorithm can be guaranteed when the system is subject to measurement data dropout. The system output convergent speed gets slower as dropout rate increases. This paper proposes a MFAC algorithm with data compensation. The missing data is first estimated using the dynamical linearization method, and then the estimated value is introduced to update control input. The convergence analysis of the proposed MFAC algorithm is given, and the effectiveness is also validated by simulations. It is shown that the proposed algorithm can compensate the effect of the data dropout, and the better output performance can be obtained.
Topology control based on quantum genetic algorithm in sensor networks
Institute of Scientific and Technical Information of China (English)
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
Directory of Open Access Journals (Sweden)
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
Institute of Scientific and Technical Information of China (English)
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
DEFF Research Database (Denmark)
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
DEFF Research Database (Denmark)
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...
Directory of Open Access Journals (Sweden)
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
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
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
Institute of Scientific and Technical Information of China (English)
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
Directory of Open Access Journals (Sweden)
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
Institute of Scientific and Technical Information of China (English)
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
International Nuclear Information System (INIS)
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
Energy Technology Data Exchange (ETDEWEB)
Lee, Yoon Joon; Cho, Kyung Ho; Kim, Sin [Cheju National University, Cheju (Korea, Republic of)
1997-12-31
The H{sub {infinity}} robust controller for the reactor power control system is designed by use of the mixed weight sensitivity. The system is configured into the typical two-port model with which the weight functions are augmented. Since the solution depends on the weighting functions and the problem is of nonconvex, the genetic algorithm is used to determine the weighting functions. The cost function applied in the genetic algorithm permits the direct control of the power tracking performances. In addition, the actual operating constraints such as rod velocity and acceleration can be treated as design parameters. Compared with the conventional approach, the controller designed by the genetic algorithm results in the better performances with the realistic constraints. Also, it is found that the genetic algorithm could be used as an effective tool in the robust design. 4 refs., 6 figs. (Author)
Decentralized Control of Dynamic Routing with a Neural Network Algorithm
Institute of Scientific and Technical Information of China (English)
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.
Directory of Open Access Journals (Sweden)
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
International Nuclear Information System (INIS)
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
DEFF Research Database (Denmark)
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
DEFF Research Database (Denmark)
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
Directory of Open Access Journals (Sweden)
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
DEFF Research Database (Denmark)
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
Directory of Open Access Journals (Sweden)
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
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
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
DEFF Research Database (Denmark)
Kerekes, Tamas; Teodorescu, Remus; Liserre, Marco;
2008-01-01
This paper presents a novel concept for an MPPT that can be used in case of a voltage controlled grid connected PV inverters. In case of single-phase systems, the 100 Hz ripple in the AC power is also present on the DC side. Depending on the DC link capacitor, this power fluctuation can be used to...
On flexible CAD of adaptive control and identification algorithms
DEFF Research Database (Denmark)
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
Directory of Open Access Journals (Sweden)
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
Institute of Scientific and Technical Information of China (English)
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.
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
POPA Valentin
2013-01-01
Full Text Available This paper presents the development of a traffic prediction algorithm that can be integrated in a street lighting monitoring and control system. The prediction algorithm must enable the reduction of energy costs and improve energy efficiency by decreasing the light intensity depending on the traffic level. The algorithm analyses and processes the information received at the command center based on the traffic level at different moments. The data is collected by means of the Doppler vehicle detection sensors integrated within the system. Thus, two methods are used for the implementation of the algorithm: a neural network and a k-NN (k-Nearest Neighbor prediction algorithm. For 500 training cycles, the mean square error of the neural network is 9.766 and for 500.000 training cycles the error amounts to 0.877. In case of the k-NN algorithm the error increases from 8.24 for k=5 to 12.27 for a number of 50 neighbors. In terms of a root means square error parameter, the use of a neural network ensures the highest performance level and can be integrated in a street lighting control system.
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
Energy Technology Data Exchange (ETDEWEB)
Spruce, C.J.; Markou, H.; Leithead, W.E.; Dominguez Ruiz, S.
2005-07-01
Innovative turbine control strategies could allow the improvements to cost and performance considered essential to reduce the cost of energy from offshore wind farms around the UK. This project reviewed and investigated the possibility for further development of a power control algorithm originally developed by NEG Micon Rotors Ltd for use with offshore wind turbines in the hope that more advanced algorithms would reduce the loads on, and hence the costs of, components such as the foundation/support structure, tower, blades and bedplate. Three models (simulation model, linearisation of the simulation model and control model) were produced in order to conduct the review. Application of these models produced the conclusion that the size of the latest generation of offshore wind turbines has now reached a level where performance is starting to be constrained by fundamental factors in the dynamics caused by the machine's physical size. It was also concluded that an ideal control strategy could achieve potential cost savings for the tower and support structure of 5-10% of the total cost of the turbine plus support structure. Further work to develop controllers to reduce loads in the tower and support structure is urged. The report considers non-linear simulation, the linear model, the control model, general operation of the controller, the drive train damping filter, torque control, pitch control and advanced algorithms, and makes detailed recommendations for future work.
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
International Nuclear Information System (INIS)
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
DEFF Research Database (Denmark)
Xu, Chang; Tian, Qiangqiang; Shen, Wen Zhong;
2013-01-01
For the traditional simplified first-order pitch-control system model, it is difficult to describe a real dynamic characteristic of a variable pitch action system, thus a complete high order mathematical model has to be developed for the pitch control of wind turbine generation (WTG). In the paper......, 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
International Nuclear Information System (INIS)
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
Institute of Scientific and Technical Information of China (English)
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.
International Nuclear Information System (INIS)
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
International Nuclear Information System (INIS)
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
International Nuclear Information System (INIS)
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
Czech Academy of Sciences Publication Activity Database
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
Energy Technology Data Exchange (ETDEWEB)
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
Energy Technology Data Exchange (ETDEWEB)
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
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
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
DEFF Research Database (Denmark)
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
Directory of Open Access Journals (Sweden)
Čongradac Velimir D.
2012-01-01
Full Text Available The manufacturing, distribution and use of electricity are of fundamental importance for the social life and they have the biggest influence on the environment associated with any human activity. The energy needed for building lighting makes up 20-40% of the total consumption. This paper displays the development of the mathematical model and genetic algorithm for the control of dimmable lighting on problems of regulating the level of internal lighting and increase of energetic efficiency using daylight. A series of experiments using the optimization algorithm on the realized model confirmed very high savings in electricity consumption.
Recursive estimation algorithms for power controls of wireless communication networks
Institute of Scientific and Technical Information of China (English)
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
Institute of Scientific and Technical Information of China (English)
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
Energy Technology Data Exchange (ETDEWEB)
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.
Directory of Open Access Journals (Sweden)
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
Directory of Open Access Journals (Sweden)
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
Energy Technology Data Exchange (ETDEWEB)
Li Lin [Tampere Univ. of Technology (Finland); Eriksson, J.T. [Tampere Univ. of Technology (Finland)
1995-12-31
The wind turbine control system is stochastic and nonlinear, offering a demanding field for different control methods. An improved and efficient controller will have great impact on the cost-effectiveness of the technology. In this article, a design method for a self-organizing fuzzy controller is discussed, which combines two popular computational intelligence techniques, neural networks and fuzzy logic. Based on acquisited dynamic parameters of the wind, it can effectively predict wind changes in speed and direction. Maximum power can always be extracted from the kinetic energy of the wind. Based on the stimulating experiments applying nonlinear dynamics to a `Variable Speed Fixed Angle` wind turbine, it is demonstrated that the proposed control model 3rd learning algorithm provide a predictable, stable and accurate performance. The robustness of the controller to system parameter variations and measurement disturbances is also discussed. (author)
UAV Flight Control System Based on an Intelligent BEL Algorithm
Directory of Open Access Journals (Sweden)
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
International Nuclear Information System (INIS)
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
Institute of Scientific and Technical Information of China (English)
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
Energy Technology Data Exchange (ETDEWEB)
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
Energy Technology Data Exchange (ETDEWEB)
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
International Nuclear Information System (INIS)
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）
Institute of Scientific and Technical Information of China (English)
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
Directory of Open Access Journals (Sweden)
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.
Directory of Open Access Journals (Sweden)
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.
International Nuclear Information System (INIS)
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 *
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
Cheng Chen
2014-01-01
Full Text Available Selection and scheduling are an important topic in production systems. To tackle the order acceptance and scheduling problem on a single machine with release dates, tardiness penalty, and sequence-dependent setup times, in this paper a diversity controlling genetic algorithm (DCGA is proposed, in which a diversified population is maintained during the whole search process through survival selection considering both the fitness and the diversity of individuals. To measure the similarity between individuals, a modified Hamming distance without considering the unaccepted orders in the chromosome is adopted. The proposed DCGA was validated on 1500 benchmark instances with up to 100 orders. Compared with the state-of-the-art algorithms, the experimental results show that DCGA improves the solution quality obtained significantly, in terms of the deviation from upper bound.
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.
Energy Technology Data Exchange (ETDEWEB)
Young, Joseph G.
2012-01-01
Over the last several years, there has been considerable growth in camera based observation systems for a variety of safety, scientific, and recreational applications. In order to improve the effectiveness of these systems, we frequently desire the ability to increase the number of observed objects, but solving this problem is not as simple as adding more cameras. Quite often, there are economic or physical restrictions that prevent us from adding additional cameras to the system. As a result, we require methods that coordinate the tracking of objects between multiple cameras in an optimal way. In order to accomplish this goal, we present a new cooperative control algorithm for a camera based observational system. Specifically, we present a receding horizon control where we model the underlying optimal control problem as a mixed integer linear program. The benefit of this design is that we can coordinate the actions between each camera while simultaneously respecting its kinematics. In addition, we further improve the quality of our solution by coupling our algorithm with a Kalman filter. Through this integration, we not only add a predictive component to our control, but we use the uncertainty estimates provided by the filter to encourage the system to periodically observe any outliers in the observed area. This combined approach allows us to intelligently observe the entire region of interest in an effective and thorough manner.
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
Directory of Open Access Journals (Sweden)
Cviklovič Vladimír
2016-03-01
Full Text Available The issue of navigation methods is being continuously developed globally. The aim of this article is to test the fuzzy control algorithm for track finding in mobile robotics. The concept of an autonomous mobile robot EN20 has been designed to test its behaviour. The odometry navigation method was used. The benefits of fuzzy control are in the evidence of mobile robot’s behaviour. These benefits are obtained when more physical variables on the base of more input variables are controlled at the same time. In our case, there are two input variables - heading angle and distance, and two output variables - the angular velocity of the left and right wheel. The autonomous mobile robot is moving with human logic.
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
Directory of Open Access Journals (Sweden)
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
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
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
International Nuclear Information System (INIS)
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
Institute of Scientific and Technical Information of China (English)
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
Directory of Open Access Journals (Sweden)
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.
International Nuclear Information System (INIS)
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
Institute of Scientific and Technical Information of China (English)
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.
Directory of Open Access Journals (Sweden)
Gang Qin
2015-01-01
Full Text Available The acceleration performance of EV, which affects a lot of performances of EV such as start-up, overtaking, driving safety, and ride comfort, has become increasingly popular in recent researches. An improved variable gain PID control algorithm to improve the acceleration performance is proposed in this paper. The results of simulation with Matlab/Simulink demonstrate the effectiveness of the proposed algorithm through the control performance of motor velocity, motor torque, and three-phase current of motor. Moreover, it is investigated that the proposed controller is valid by comparison with the other PID controllers. Furthermore, the AC induction motor experiment set is constructed to verify the effect of proposed controller.
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
Directory of Open Access Journals (Sweden)
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...
Energy Technology Data Exchange (ETDEWEB)
Perez C, B
2003-07-01
In this thesis work there are presented: a) The characteristics and main components used in an electronic system based on a Dsp guided to control applications of processes, b) The description of an algorithm of diffuse control whose objective is the regulation of neutron power in a model of the punctual kinetics of a nuclear research reactor type TRIGA, and c) The installation in language assembler and execution in real time of the control algorithm in the system based on a Dsp. With regard to the installation and execution of the algorithm, the reaches of the project have been delimited to the following: a) Readiness of the entrance values to the controller in specific registrations of the system Dsp, b) Conversion of the entrances to the numerical formats with those that one obtains the best acting in the control algorithm, c) Execution of the algorithm until the obtaining of the value of the controller's exit, and d) Placement of the result in specific registrations of the Dsp for their later reading for an external parallel interface. It is necessary to mention that the simulation of the punctual kinetics of a reactor type TRIGA in the Pc and its integration with the control system based on the one Dsp is had contemplated as continuation of this work and that one of those will constitute main activities in my project of master thesis. A brief description of the topics presented in this thesis is given next. In the chapter one it is presented a general description of the diffuse logic and some of their applications in the industry. The main characteristics of a Dsp are also presented that they make it different from a micro controller or a microprocessor of general purpose. In the chapter 2 details of the internal architecture of the Dsp TMS320CS0 of Texas Instruments that are not explained with detail in the manual of user of the same one. This chapter has as objective to understand the internal hardware of the Dsp that is used for to carry out the program
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
Directory of Open Access Journals (Sweden)
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.
DEFF Research Database (Denmark)
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.
Directory of Open Access Journals (Sweden)
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.
Directory of Open Access Journals (Sweden)
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
Directory of Open Access Journals (Sweden)
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.
Directory of Open Access Journals (Sweden)
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
Institute of Scientific and Technical Information of China (English)
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.
A parallel clustered dynamic programming algorithm for discrete time optimal control problems
International Nuclear Information System (INIS)
Optimal control of dynamical systems is a problem that arises in many areas of engineering and physical science. Due to the special structure of optimal control problems, currently there is no parallel algorithm that can solve optimal control problems efficiently on computers with a large number of processors. In this paper, we will introduce a new optimal control algorithm that permits massively parallel processing. The proposed algorithm, called Cluster Dynamic Programming, is a combination of two efficient serial algorithms, differential dynamic programming and a stagewise Newton's method. Parallel numerical results on an Intel iPSC/860 will be presented
Evolutionary algorithms for the optimal laser control of molecular orientation
International Nuclear Information System (INIS)
In terms of optimal control, laser-induced molecular orientation is an optimization problem involving a global minimum search on a multi-dimensional surface function of varying parameters characterizing the laser pulse (frequency, peak intensity, temporal shape). Genetic algorithms, aiming at the optimization of different possible targets, may temporarily be trapped in a local minimum, before reaching the global one. A careful study of such local (robust) minima provides a key for the thorough interpretation of the orientation dynamics, in terms of basic mechanisms. Two targets are retained: the first, simple, one searching for an angle between molecular and laser polarization axes as close as possible to zero (orientation) at a given time; the second, hybrid, one combining the efficiency of orientation with its duration. Their respective roles are illustrated referring to two molecular systems, HCN and LiF, taken at a rigid rotor approximation level. A sudden and asymmetric laser pulse (provided by a frequency ω superposed on its second harmonic 2ω leads to the kick mechanism. The result is a very fast (as compared to the rotational period) angular momentum transfer to the molecule, that turns out to be responsible for an efficient orientation after the laser pulse is turned off
Hybrid genetic algorithm approach for selective harmonic control
Energy Technology Data Exchange (ETDEWEB)
Dahidah, Mohamed S.A. [Faculty of Engineering, Multimedia University, 63100, Jalan Multimedia-Cyberjaya, Selangor (Malaysia); Agelidis, Vassilios G. [School of Electrical and Information Engineering, The University of Sydney, NSW (Australia); Rao, Machavaram V. [Faculty of Engineering and Technology, Multimedia University, 75450, Jalan Ayer Keroh Lama-Melaka (Malaysia)
2008-02-15
The paper presents an optimal solution for a selective harmonic elimination pulse width modulated (SHE-PWM) technique suitable for a high power inverter used in constant frequency utility applications. The main challenge of solving the associated non-linear equations, which are transcendental in nature and, therefore, have multiple solutions, is the convergence, and therefore, an initial point selected considerably close to the exact solution is required. The paper discusses an efficient hybrid real coded genetic algorithm (HRCGA) that reduces significantly the computational burden, resulting in fast convergence. An objective function describing a measure of the effectiveness of eliminating selected orders of harmonics while controlling the fundamental, namely a weighted total harmonic distortion (WTHD) is derived, and a comparison of different operating points is reported. It is observed that the method was able to find the optimal solution for a modulation index that is higher than unity. The theoretical considerations reported in this paper are verified through simulation and experimentally on a low power laboratory prototype. (author)
Hybrid genetic algorithm approach for selective harmonic control
International Nuclear Information System (INIS)
The paper presents an optimal solution for a selective harmonic elimination pulse width modulated (SHE-PWM) technique suitable for a high power inverter used in constant frequency utility applications. The main challenge of solving the associated non-linear equations, which are transcendental in nature and, therefore, have multiple solutions, is the convergence, and therefore, an initial point selected considerably close to the exact solution is required. The paper discusses an efficient hybrid real coded genetic algorithm (HRCGA) that reduces significantly the computational burden, resulting in fast convergence. An objective function describing a measure of the effectiveness of eliminating selected orders of harmonics while controlling the fundamental, namely a weighted total harmonic distortion (WTHD) is derived, and a comparison of different operating points is reported. It is observed that the method was able to find the optimal solution for a modulation index that is higher than unity. The theoretical considerations reported in this paper are verified through simulation and experimentally on a low power laboratory prototype
A Self-tuning Fuzzy Queue Management Algorithm for Congestion Control
Institute of Scientific and Technical Information of China (English)
Zhang Jingyuan(张敬辕); Xie Jianying
2004-01-01
This letter presents an effective self-tuning fuzzy queue management algorithm for congestion control. With the application of the algorithm, routers in IP network regulate its packet drop probability by a self-tuning fuzzy controller. The main advantage of the algorithm is that, with the parameter self-tuning mechanism, queue length can keep stable in a variety of network environments without the difficulty of parameter configuration. Simulations show that the algorithm is efficient, stable and outperforms the popular RED queue management algorithm significantly.
A topology control algorithm for preserving minimum-energy paths in wireless ad hoc networks
Institute of Scientific and Technical Information of China (English)
SHEN Zhong; CHANG Yilin; CUI Can; ZHANG Xin
2007-01-01
In this Paper,a distributed topology control algorithm is proposed.By adjusting the transmission power of each node,this algorithm constructs a wireless network topology with minimum-energy property,i.e.,it preserves a minimum-energy path between every pair of nodes.Moreover,the proposed algorithm can be used in both homogenous and heterogeneous wireless networks.and it can also work without an explicit propagation channel model or the position information of nodes.Simulation results show that the proposed algorithm has advantages over the topology control algorithm based on direct-transmission region in terms of average node degree and power efficiency.
A Congestion—point Orientd Congestion Control Algorithm for Resilient Packet Ring
Institute of Scientific and Technical Information of China (English)
KONGHongwei; EGNing; RUANFang; FENGChongxi
2003-01-01
In this paper,one congestion-point oriented congestion control algorithm for resilient packet ring is proposed.By using deflcit round robin scheduling algorithm and non-linear adjustment of control gain via the explicit feedbck information about the explicit rate and the virtual queueing delay,this algorithm can promise fairness,fast convergence,low memory requirement and smooth equilibrlum behavior.This algorithm also avoids the difflculty of estimating the number of active flows when calculating the explicit rate,thus decreases the implementation complexity greatly.This algorithm is not sensitive to the loss of congestion control packets and can adapt to a wide range of link rates and network scale.This congestion control algorithm can be implemented on the multi-access control layer of resilient packet ring.
ATEFI - A descentralized fix time algorithm for signal control
Directory of Open Access Journals (Sweden)
Edmar Nagayama
2009-03-01
Full Text Available This work proposes the presentation of a decentralized fixed time algorithm (ATEFI, with the purpose of finding optimized traffic light times. The results of the algorithm will be compared with commercial software called TRANSYT. The objective is to minimize the delay and the comparison of different strategies, trying to obtain a low cost solution for the urban traffic management problems.
Distributed control software of high-performance control-loop algorithm
Blanc, D
1999-01-01
The majority of industrial cooling and ventilation plants require the control of complex processes. All these processes are highly important for the operation of the machines. The stability and reliability of these processes are leading factors identifying the quality of the service provided. The control system architecture and software structure, as well, are required to have high dynamical performance and robust behaviour. The intelligent systems based on PID or RST controllers are used for their high level of stability and accuracy. The design and tuning of these complex controllers require the dynamic model of the plant to be known (generally obtained by identification) and the desired performance of the various control loops to be specified for achieving good performances. The concept of having a distributed control algorithm software provides full automation facilities with well-adapted functionality and good performances, giving methodology, means and tools to master the dynamic process optimization an...
Design of Sliding Mode Controller Enhanced by Fuzzy Logic Algorithm for Industrial Robot
Directory of Open Access Journals (Sweden)
Vijay Tiwari
2013-11-01
Full Text Available In this paper a sliding mode control enhanced by fuzzy logic algorithm method is proposed for the robust tracking control of industrial robot manipulator. The proposed controller ensures the advantage of fuzzy logic algorithm and sliding mode control. There are two parts of the proposed method: first the design of sliding mode control for robust stability and second the development of fuzzy logic algorithms to reduce chattering effectively. The stability of control is proven by Lyapunov stability method and the performance of tracking error is shown in a table by using RMS value.
Energy Technology Data Exchange (ETDEWEB)
Gayeski, N.; Armstrong, Peter; Alvira, M.; Gagne, J.; Katipamula, Srinivas
2011-11-30
KGS Buildings LLC (KGS) and Pacific Northwest National Laboratory (PNNL) have developed a simplified control algorithm and prototype low-lift chiller controller suitable for model-predictive control in a demonstration project of low-lift cooling. Low-lift cooling is a highly efficient cooling strategy conceived to enable low or net-zero energy buildings. A low-lift cooling system consists of a high efficiency low-lift chiller, radiant cooling, thermal storage, and model-predictive control to pre-cool thermal storage overnight on an optimal cooling rate trajectory. We call the properly integrated and controlled combination of these elements a low-lift cooling system (LLCS). This document is the final report for that project.
Model predictive control algorithms and their application to a continuous fermenter
Directory of Open Access Journals (Sweden)
R. G. SILVA
1999-06-01
Full Text Available In many continuous fermentation processes, the control objective is to maximize productivity per unit time. The optimum operational point in the steady state can be obtained by maximizing the productivity rate using feed substrate concentration as the independent variable with the equations of the static model as constraints. In the present study, three model-based control schemes have been developed and implemented for a continuous fermenter. The first method modifies the well-known dynamic matrix control (DMC algorithm by making it adaptive. The other two use nonlinear model predictive control algorithms (NMPC, nonlinear model predictive control for calculation of control actions. The NMPC1 algorithm, which uses orthogonal collocation in finite elements, acted similar to NMPC2, which uses equidistant collocation. These algorithms are compared with DMC. The results obtained show the good performance of nonlinear algorithms.
Directory of Open Access Journals (Sweden)
Riedel-Heller Steffi G
2008-05-01
Full Text Available Abstract Background Regarding demographic changes in Germany it can be assumed that the number of elderly and the resulting need for long term care is increasing in the near future. It is not only an individual's interest but also of public concern to avoid a nursing home admission. Current evidence indicates that preventive home visits can be an effective way to reduce the admission rate in this way making it possible for elderly people to stay longer at home than without home visits. As the effectiveness and cost-effectiveness of preventive home visits strongly depends on existing services in the social and health system existing international results cannot be merely transferred to Germany. Therefore it is necessary to investigate the effectiveness and cost-effectiveness of such an intervention in Germany by a randomized controlled trial. Methods The trial is designed as a prospective multi-center randomized controlled trial in the cities of Halle and Leipzig. The trial includes an intervention and a control group. The control group receives usual care. The intervention group receives three additional home visits by non-physician health professionals (1 geriatric assessment, (2 consultation, (3 booster session. The nursing home admission rate after 18 months will be defined as the primary outcome. An absolute risk reduction from a 20% in the control-group to a 7% admission rate in the intervention group including an assumed drop out rate of 30% resulted in a required sample size of N = 320 (n = 160 vs. n = 160. Parallel to the clinical outcome measurement the intervention will be evaluated economically. The economic evaluation will be performed from a society perspective. Discussion To the authors' knowledge for the first time a trial will investigate the effectiveness and cost-effectiveness of preventive home visits for people aged 80 and over in Germany using the design of a randomized controlled trial. Thus, the trial will contribute to
Newton algorithm for Hamiltonian characterization in quantum control
International Nuclear Information System (INIS)
We propose a Newton algorithm to characterize the Hamiltonian of a quantum system interacting with a given laser field. The algorithm is based on the assumption that the evolution operator of the system is perfectly known at a fixed time. The computational scheme uses the Crank–Nicholson approximation to explicitly determine the derivatives of the propagator with respect to the Hamiltonians of the system. In order to globalize this algorithm, we use a continuation method that improves its convergence properties. This technique is applied to a two-level quantum system and to a molecular one with a double-well potential. The numerical tests show that accurate estimates of the unknown parameters are obtained in some cases. We discuss the numerical limits of the algorithm in terms of the basin of convergence and the non-uniqueness of the solution. (paper)
Synthesis of sequential control algorithms for pneumatic drives controlled by monostable valves
Directory of Open Access Journals (Sweden)
Ł. Dworzak
2009-07-01
Full Text Available Application of the Grafpol method [1] for synthesising sequential control algorithms for pneumatic drives controlled by monostable valves is presented. The developed principles simplify the MTS method of programming production processes in the scope of the memory realisation [2]. Thanks to this, time for synthesising the schematic equation can be significantly reduced in comparison to the network transformation method [3]. The designed schematic equation makes a ground for writing an application program of a PLC using any language defined in IEC 61131-3.
Guidance Algorithms for Planar Path-based Motion Control Scenarios
Haugen, Joakim
2010-01-01
The problem of performing accurate path maneuvering tasks in planar space is investigated in thesis. The purpose is to utilize limited knowledge about the vehicle's maneuverability constraints to output feasible reference signals. Acceleration limitations of the vehicle have been used in an algorithm that determines forward speeds in such way that a predefined path can be followed at high speeds. The algorithm ensures that the speed is reduced before acute turns. Furthermore, an existing ste...
Power control algorithms for mobile ad hoc networks
Directory of Open Access Journals (Sweden)
Nuraj L. Pradhan
2011-07-01
We will also focus on an adaptive distributed power management (DISPOW algorithm as an example of the multi-parameter optimization approach which manages the transmit power of nodes in a wireless ad hoc network to preserve network connectivity and cooperatively reduce interference. We will show that the algorithm in a distributed manner builds a unique stable network topology tailored to its surrounding node density and propagation environment over random topologies in a dynamic mobile wireless channel.
Local minimization algorithms for dynamic programming equations
Kalise, Dante; Kröner, Axel; Kunisch, Karl
2015-01-01
The numerical realization of the dynamic programming principle for continuous-time optimal control leads to nonlinear Hamilton-Jacobi-Bellman equations which require the minimization of a nonlinear mapping over the set of admissible controls. This minimization is often performed by comparison over a finite number of elements of the control set. In this paper we demonstrate the importance of an accurate realization of these minimization problems and propose algorithms by which this can be achi...
On a reconstruction algorithm for the trajectory and control in a delay system
Blizorukova, M. S.; V.I. Maksimov
2013-01-01
We discuss a problem of the dynamic reconstruction of unmeasured coordinates of the phase vector and unknown controls in nonlinear vector equations with delay. A regularizing algorithm is proposed for the reconstruction of both controls and unmeasured coordinates simultaneously with the processes. The algorithm is stable with respect to information noises and computational errors. © 2013 Pleiades Publishing, Ltd.
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Dammann, Bernd; Madsen, Henrik;
2014-01-01
This paper presents a decomposition algorithm for solving the optimal control problem (OCP) that arises in Mean-Variance Economic Model Predictive Control of stochastic linear systems. The algorithm applies the alternating direction method of multipliers to a reformulation of the OCP that...
Self-learning Fuzzy Controllers Based On a Real-time Reinforcement Genetic Algorithm
Institute of Scientific and Technical Information of China (English)
FANG Jian-an; MIAO Qing-ying; GUO Zhao-xia; SHAO Shi-huang
2002-01-01
This paper presents a novel method for constructing fuzzy controllers based on a real time reinforcement genetic algorithm. This methodology introduces the real-time learning capability of neural networks into globally searching process of genetic algorithm, aiming to enhance the convergence rate and real-time learning ability of genetic algorithm, which is then used to construct fuzzy controllers for complex dynamic systems without any knowledge about system dynamics and prior control experience. The cart-pole system is employed as a test bed to demonstrate the effectiveness of the proposed control scheme, and the robustness of the acquired fuzzy controller with comparable result.
Yamamoto, Kensei; Aoki, Hidenori; Naoi, Kenji; Mizutani, Yoshibumi
This paper presents the result of executing the conventional genetic algorithm (GA) and a new method to the voltage and reactive power control (VQC). The conventional GA can give the control process and improve the fitness with the practical control times. And, the method to cancel the limited deviation as early as possible is implemented. Moreover, the method to reduce the control times to the fitness as much as possible is proposed. The proposed method is integrated the tabu search (TS) into the conventional GA. The proposed method generates next generation’s individual with the crossover of the conventional GA and the neighborhood search of the TS. Therefore, the proposed method executes an effective search. As a result, the proposed method can obtain better fitness than the conventional GA in the same calculation times. The effectiveness of the proposed method is demonstrated by practical 15-bus and 118-bus systems.
Hasbullah Mohd Isa, Wan; Taha, Zahari; Mohd Khairuddin, Ismail; Majeed, Anwar P. P. Abdul; Fikri Muhammad, Khairul; Abdo Hashem, Mohammed; Mahmud, Jamaluddin; Mohamed, Zulkifli
2016-02-01
This paper presents the modelling and control of a two degree of freedom upper extremity exoskeleton by means of an intelligent active force control (AFC) mechanism. The Newton-Euler formulation was used in deriving the dynamic modelling of both the anthropometry based human upper extremity as well as the exoskeleton that consists of the upper arm and the forearm. A proportional-derivative (PD) architecture is employed in this study to investigate its efficacy performing joint-space control objectives. An intelligent AFC algorithm is also incorporated into the PD to investigate the effectiveness of this hybrid system in compensating disturbances. The Mamdani Fuzzy based rule is employed to approximate the estimated inertial properties of the system to ensure the AFC loop responds efficiently. It is found that the IAFC-PD performed well against the disturbances introduced into the system as compared to the conventional PD control architecture in performing the desired trajectory tracking.
Directory of Open Access Journals (Sweden)
S.Augustilindiya
2013-08-01
Full Text Available Tuning PID controller parameters using Evolutionary algorithm for an asynchronous Buck converter is presented in this paper. PID controller is one of the solutions for controlling a Buck converter during transient conditions. There are straight forward ways for calculating the parameters for the PID controller in the literature and evolutionary algorithm based approach with a proper fitnessfunction gives superior performance when compared to other methods. Ziegler Nicholas method, Hurwitz polynomial method and Genetic Algorithm based method are compared. It is found that Genetic Algorithm based method yields better result. The hardware implementation of Genetic Algorithm assisted PID controller with low cost is desired and such an implementation is taken in this paper. A low cost microcontroller with built-in PWM modules is implemented and the performance is compared with simulations.
Algorithms and Complexity Analyses for Control of Singleton Attractors in Boolean Networks
Directory of Open Access Journals (Sweden)
Wai-Ki Ching
2008-09-01
Full Text Available A Boolean network (BN is a mathematical model of genetic networks. We propose several algorithms for control of singleton attractors in BN. We theoretically estimate the average-case time complexities of the proposed algorithms, and confirm them by computer experiments. The results suggest the importance of gene ordering. Especially, setting internal nodes ahead yields shorter computational time than setting external nodes ahead in various types of algorithms. We also present a heuristic algorithm which does not look for the optimal solution but for the solution whose computational time is shorter than that of the exact algorithms.
Stability of the Newton-Like algorithm in optimization flow control
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
The stability of the Newton-like algorithm in optimization flow control is considered in this paper.This algorithm is proved to be globally stable under a general network topology by means of Lyapunov stability theory, without considering the round trip time of each source. While the stability of this algorithm with considering the round trip time is analyzed as well. The analysis shows that the algorithm with only one bottleneck link accessed by several sources is also globally stable, and all trajectories described by this algorithm ultimately converge to the equilibrium point.
A guidance and control algorithm for scent tracking micro-robotic vehicle swarms
International Nuclear Information System (INIS)
Cooperative micro-robotic scent tracking vehicles are designed to collectively sniff out locations of high scent concentrations in unknown, geometrically complex environments. These vehicles are programmed with guidance and control algorithms that allow inter cooperation among vehicles. In this paper a cooperative guidance and control algorithm for scent tracking micro-robotic vehicles is presented. This algorithm is comprised of a sensory compensation sub-algorithm using point source cancellation, a guidance sub-algorithm using gradient descent tracking, and a control sub-algorithm using proportional feedback. The concepts of social rank and point source cancellation are new concepts introduced within. Simulation results for cooperative vehicles swarms are given. Limitations are discussed
A guidance and control algorithm for scent tracking micro-robotic vehicle swarms
Energy Technology Data Exchange (ETDEWEB)
Dohner, J.L. [Sandia National Labs., Albuquerque, NM (United States). Structural Dynamics Dept.
1998-03-01
Cooperative micro-robotic scent tracking vehicles are designed to collectively sniff out locations of high scent concentrations in unknown, geometrically complex environments. These vehicles are programmed with guidance and control algorithms that allow inter cooperation among vehicles. In this paper a cooperative guidance and control algorithm for scent tracking micro-robotic vehicles is presented. This algorithm is comprised of a sensory compensation sub-algorithm using point source cancellation, a guidance sub-algorithm using gradient descent tracking, and a control sub-algorithm using proportional feedback. The concepts of social rank and point source cancellation are new concepts introduced within. Simulation results for cooperative vehicles swarms are given. Limitations are discussed.
S.Augustilindiya; Palani, S.; K.Vijayarekha; M.BreethiYeltsina
2013-01-01
Tuning PID controller parameters using Evolutionary algorithm for an asynchronous Buck converter is presented in this paper. PID controller is one of the solutions for controlling a Buck converter during transient conditions. There are straight forward ways for calculating the parameters for the PID controller in the literature and evolutionary algorithm based approach with a proper fitnessfunction gives superior performance when compared to other methods. Ziegler Nicholas method, Hurwitz pol...
Genetic Algorithm Tuning of PID Controller in Smith Predictor for Glucose Concentration Control
Directory of Open Access Journals (Sweden)
Tsonyo Slavov
2011-07-01
Full Text Available This paper focuses on design of a glucose concentration control system based on nonlinear model plant of E. coli MC4110 fed-batch cultivation process. Due to significant time delay in real time glucose concentration measurement, a correction is proposed in glucose concentration measurement and a Smith predictor (SP control structure based on universal PID controller is designed. To reduce the influence of model error in SP structure the estimate of measured glucose concentration is used. For the aim an extended Kalman filter (EKF is designed. To achieve good closed-loop system performance genetic algorithm (GA based optimal controller tuning procedure is applied. A standard binary encoding GA is applied. The GA parameters and operators are specified for the considered here problem. As a result the optimal PID controller settings are obtained. The simulation experiments of the control systems based on SP with EKF and without EKF are performed. The results show that the control system based on SP with EKF has a better performance than the one without EKF. For a short time the controller sets the control variable and maintains it at the desired set point during the cultivation process. As a result, a high biomass concentration of 48.3 g·l-1 is obtained at the end of the process.
Institute of Scientific and Technical Information of China (English)
LI Hongbo; SUN Zengqi; CHEN Badong; LIU Huaping
2008-01-01
The use of communication networks in control loops has gained increasing attention in recent years due to its advantages and flexible applications. The network quality-of-service (QoS) in those so-called networked control systems always fluctuates due to changes of the traffic load and available network resources. This paper presents an intelligent scheduling controller design approach for a class of NCSs to handle network QoS variations. The sampling period and control parameters in the controller are simultane-ously scheduled to compensate for the network QoS variations. The estimation of distribution algorithm is used to optimize the sampling period and control parameters for better performance. Compared with exist-ing networked control methods, the controller has better ability to compensate for the network QoS varia-tions and to balance network loads. Simulation results show that the plant setting time with the intelligent scheduling controller is reduced by about 64.0% for the medium network load and 49.1% for high network load and demonstrate the effectiveness of the proposed approaches.
On admissible canonical mechanics
International Nuclear Information System (INIS)
General solution has been derived for the functional c-number equation which determines all admissible realisations of various mechanics with associative (but not necessary realizable by operators) law of multiplication of the observables. The general solution includes the algebras of observables for the classical and for the quantum mechanics. In addition, the solution includes one new algebra which corresponds formally to purely imaginary value to the Planck constant. The mathematical difficulties of treating the new algebra are discussed
Stoughton, John W.; Mielke, Roland R.
1988-01-01
An overview is presented of a model for describing data and control flow associated with the execution of large-grained, decision-free algorithms in a special distributed computer environment. The ATAMM (Algorithm-To-Architecture Mapping Model) model provides a basis for relating an algorithm to its execution in a dataflow multicomputer environment. The ATAMM model features a marked graph Petri net description of the algorithm behavior with regard to both data and control flow. The model provides an analytical basis for calculating performance bounds on throughput characteristics which are demonstrated here.
Ha, S. H.; Choi, S. B.; Lee, G. S.; Yoo, W. H.
2013-02-01
This paper presents control performance evaluation of railway vehicle featured by semi-active suspension system using magnetorheological (MR) fluid damper. In order to achieve this goal, a nine degree of freedom of railway vehicle model, which includes car body and bogie, is established. The wheel-set data is loaded from measured value of railway vehicle. The MR damper system is incorporated with the governing equation of motion of the railway vehicle model which includes secondary suspension. To illustrate the effectiveness of the controlled MR dampers on suspension system of railway vehicle, the control law using the sky-ground hook controller is adopted. This controller takes into account for both vibration control of car body and increasing stability of bogie by adopting a weighting parameter between two performance requirements. The parameters appropriately determined by employing a fuzzy algorithm associated with two fuzzy variables: the lateral speed of the car body and the lateral performance of the bogie. Computer simulation results of control performances such as vibration control and stability analysis are presented in time and frequency domains.
A Novel Control Algorithm for Static Series Compensators by Use of PQR Instantaneous Power Theory
DEFF Research Database (Denmark)
Lee, Sang-Joon; Kim, Hyosung; Sul, Seung-Ki;
2004-01-01
This paper describes an algorithm and the related implementations to control static series compensators (SSCs). Directly sensed three-phase voltages are transformed to coordinates without time delay, then the reference voltages in coordinates become very simple form: single dc value. The controller...... SSCs such as dynamic voltage restorer (DVRs), series active filters (SAFs), synchronous static series compensators (SSSCs), bootstrap variable inductances (BVIs). The control algorithm was applied to a DVR system. The experimental results verified the performance of the proposed control algorithm. p...
Development of real-time plasma analysis and control algorithms for the TCV tokamak using SIMULINK
International Nuclear Information System (INIS)
Highlights: • A new digital control system for the TCV tokamak has been commissioned. • The system is entirely programmable by SIMULINK, allowing rapid algorithm development. • Different control system nodes can run different algorithms at varying sampling times. • The previous control system functions have been emulated and improved. • New capabilities include MHD control, profile control, equilibrium reconstruction. - Abstract: One of the key features of the new digital plasma control system installed on the TCV tokamak is the possibility to rapidly design, test and deploy real-time algorithms. With this flexibility the new control system has been used for a large number of new experiments which exploit TCV's powerful actuators consisting of 16 individually controllable poloidal field coils and 7 real-time steerable electron cyclotron (EC) launchers. The system has been used for various applications, ranging from event-based real-time MHD control to real-time current diffusion simulations. These advances have propelled real-time control to one of the cornerstones of the TCV experimental program. Use of the SIMULINK graphical programming language to directly program the control system has greatly facilitated algorithm development and allowed a multitude of different algorithms to be deployed in a short time. This paper will give an overview of the developed algorithms and their application in physics experiments
Controller Parameter Optimization for Nonlinear Systems Using Enhanced Bacteria Foraging Algorithm
Directory of Open Access Journals (Sweden)
V. Rajinikanth
2012-01-01
Full Text Available An enhanced bacteria foraging optimization (EBFO algorithm-based Proportional + integral + derivative (PID controller tuning is proposed for a class of nonlinear process models. The EBFO algorithm is a modified form of standard BFO algorithm. A multiobjective performance index is considered to guide the EBFO algorithm for discovering the best possible value of controller parameters. The efficiency of the proposed scheme has been validated through a comparative study with classical BFO, adaptive BFO, PSO, and GA based controller tuning methods proposed in the literature. The proposed algorithm is tested in real time on a nonlinear spherical tank system. The real-time results show that, EBFO tuned PID controller gives a smooth response for setpoint tracking performance.
Algorithm for parallel control for an aerobic reactor
International Nuclear Information System (INIS)
Process control system typically utilize the same number of manipulated inputs and controlled outputs. A study biological system indicates that is possible to achieve superior performance by the judicious use of additional input variable. One can exploit the rectangular control structure to design redundant controllers working as a parallel control architecture which, under large load disturbance and control input saturations, can provide a smoother and safer process operation than the non-redundant control situation. (Author)
Self-Learning Algorithm for Coiling Temperature Controlling
Institute of Scientific and Technical Information of China (English)
WANG Jun; WANG Guo-dong; LIU Xiang-hua; ZHANG Dian-hua
2004-01-01
In order to establish a mathematical model for strip laminar cooling, the self-learning algorithm was introduced with the level learning for obvious heat flux fluctuation and the pattern learning for small heat flux fluctuation. The short self-learning calculation steps of water cooling and air cooling, and the long self-learning formula were given with some results.
Reinforcement Learning for Online Control of Evolutionary Algorithms
Eiben, A.; Horvath, Mark; Kowalczyk, Wojtek; Schut, Martijn
2007-01-01
The research reported in this paper is concerned with assessing the usefulness of reinforcment learning (RL) for on-line calibration of parameters in evolutionary algorithms (EA). We are running an RL procedure and the EA simultaneously and the RL is changing the EA parameters on-the-fly. We evalu
Development of adaptive IIR filtered-e LMS algorithm for active noise control
Institute of Scientific and Technical Information of China (English)
SUN Xu; MENG Guang; TENG Pengxiao; CHEN Duanshi
2003-01-01
Compared to finite impulse response (FIR) filters, infinite impulse response (IIR)filters can match the system better with much fewer coefficients, and hence the computationload is saved and the performance improves. Therefore, it is attractive to use IIR filters insteadof FIR filters in active noise control (ANC). However, filtered-U LMS (FULMS) algorithm, theIIR filter-based algorithm commonly used so far cannot ensure global convergence. A new IIRfilter based adaptive algorithm, which can ensure global convergence with computation loadonly slightly increasing, is proposed in this paper. The new algorithm is called as filtered-eLMS algorithm since the error signal of which need to be filtered. Simulation results show thatthe FELMS algorithm presents better performance than the FULMS algorithm.
Battiste, Vernol; Lawton, George; Lachter, Joel; Brandt, Summer; Koteskey, Robert; Dao, Arik-Quang; Kraut, Josh; Ligda, Sarah; Johnson, Walter W.
2012-01-01
Managing the interval between arrival aircraft is a major part of the en route and TRACON controller s job. In an effort to reduce controller workload and low altitude vectoring, algorithms have been developed to allow pilots to take responsibility for, achieve and maintain proper spacing. Additionally, algorithms have been developed to create dynamic weather-free arrival routes in the presence of convective weather. In a recent study we examined an algorithm to handle dynamic re-routing in the presence of convective weather and two distinct spacing algorithms. The spacing algorithms originated from different core algorithms; both were enhanced with trajectory intent data for the study. These two algorithms were used simultaneously in a human-in-the-loop (HITL) simulation where pilots performed weather-impacted arrival operations into Louisville International Airport while also performing interval management (IM) on some trials. The controllers retained responsibility for separation and for managing the en route airspace and some trials managing IM. The goal was a stress test of dynamic arrival algorithms with ground and airborne spacing concepts. The flight deck spacing algorithms or controller managed spacing not only had to be robust to the dynamic nature of aircraft re-routing around weather but also had to be compatible with two alternative algorithms for achieving the spacing goal. Flight deck interval management spacing in this simulation provided a clear reduction in controller workload relative to when controllers were responsible for spacing the aircraft. At the same time, spacing was much less variable with the flight deck automated spacing. Even though the approaches taken by the two spacing algorithms to achieve the interval management goals were slightly different they seem to be simpatico in achieving the interval management goal of 130 sec by the TRACON boundary.
Control and monitoring of on-line trigger algorithms using a SCADA system
van Herwijnen, E; Barczyk, A; Damodaran, B; Frank, M; Gaidioz, B; Gaspar, C; Jacobsson, R; Jost, B; Neufeld, N; Bonifazi, F; Callot, O; Lopes, H
2006-01-01
LHCb [1] has an integrated Experiment Control System (ECS) [2], based on the commercial SCADA system PVSS [3]. The novelty of this approach is that, in addition to the usual control and monitoring of experimental equipment, it provides control and monitoring for software processes, namely the on-line trigger algorithms. Algorithms based on Gaudi [4] (the LHCb software framework) compute the trigger decisions on an event filter farm of around 2000 PCs. Gaucho [5], the GAUdi Component Helping Online, was developed to allow the control and monitoring of Gaudi algorithms. Using Gaucho, algorithms can be monitored from the run control system provided by the ECS. To achieve this, Gaucho implements a hierarchical control system using Finite State Machines. In this article we describe the Gaucho architecture, the experience of monitoring a large number of software processes and some requirements for future extensions.
An Interactive Control Algorithm Used for Equilateral Triangle Formation with Robotic Sensors
LI, XIANG; Chen, Hongcai
2014-01-01
This paper describes an interactive control algorithm, called Triangle Formation Algorithm (TFA), used for three neighboring robotic sensors which are distributed randomly to self-organize into and equilateral triangle (E) formation. The algorithm is proposed based on the triangular geometry and considering the actual sensors used in robotics. In particular, the stability of the TFA, which can be executed by robotic sensors independently and asynchronously for E formation, is analyzed in deta...
Quasi-optimal algorithms for the control loops of the Fermilab energy saver satellite refrigerator
International Nuclear Information System (INIS)
The Cryogenic System of the Satellite Refrigerator for the Energy Saver Accelerator Ring comprises 12 interrelated closed loops and several open loops. A quasi-optimal algorithm to control the Cryogenic System, under different modes operation, is described. The constraints imposed to define these algorithms and the process followed to characterize the functional parameters are described. A report on the results obtained with the algorithms in a test facility will be presented. 6 refs
The Research on an Algorithm of Three-Dimensional Topology Control of Wireless Sensor Network
Directory of Open Access Journals (Sweden)
Xiao-Chun Hu
2012-11-01
Full Text Available Nowadays, the research about three-dimensional topology control has focused on ensuring the connectivity of the networks, and has seldom considered the balance between neighbor node degree and energy consumption minimum path. In order to solve this problem, this paper proposes an adjustable topology control algorithm in three-dimensional wireless sensor networks, and this algorithm can dynamically adjust the network topology control structure through changing the adjustment factor r(0
A noise filtering algorithm for the MFTF-B computer based control system
International Nuclear Information System (INIS)
An algorithm to reduce the message traffic in the MFTF-B computer based control system is described. The algorithm filters analog inputs to the control system. Its purpose is to distinguish between changes in the inputs due to noise and changes due to significant variations in the quantity being monitored. Noise is rejected while significant changes are reported to the control system data base, thus keeping the data base updated with a minimum number of messages. The algorithm is memory efficient, requiring only four bytes of storage per analog channel, and computationally simple, requiring only subtraction and comparison. Quantitative analysis of the algorithm is presented for the case of additive Gaussian noise. It is shown that the algorithm is stable and tends toward the mean value of the monitored variable over a wide variety of additive noise distributions
Noise filtering algorithm for the MFTF-B computer based control system
International Nuclear Information System (INIS)
An algorithm to reduce the message traffic in the MFTF-B computer based control system is described. The algorithm filters analog inputs to the control system. Its purpose is to distinguish between changes in the inputs due to noise and changes due to significant variations in the quantity being monitored. Noise is rejected while significant changes are reported to the control system data base, thus keeping the data base updated with a minimum number of messages. The algorithm is memory efficient, requiring only four bytes of storage per analog channel, and computationally simple, requiring only subtraction and comparison. Quantitative analysis of the algorithm is presented for the case of additive Gaussian noise. It is shown that the algorithm is stable and tends toward the mean value of the monitored variable over a wide variety of additive noise distributions
Genetic algorithms for optimal design and control of adaptive structures
Ribeiro, R; Dias-Rodrigues, J; Vaz, M
2000-01-01
Future High Energy Physics experiments require the use of light and stable structures to support their most precise radiation detection elements. These large structures must be light, highly stable, stiff and radiation tolerant in an environment where external vibrations, high radiation levels, material aging, temperature and humidity gradients are not negligible. Unforeseen factors and the unknown result of the coupling of environmental conditions, together with external vibrations, may affect the position stability of the detectors and their support structures compromising their physics performance. Careful optimization of static and dynamic behavior must be an essential part of the engineering design. Genetic Algorithms ( GA) belong to the group of probabilistic algorithms, combining elements of direct and stochastic search. They are more robust than existing directed search methods with the advantage of maintaining a population of potential solutions. There is a class of optimization problems for which Ge...
Reinforcement Learning for Online Control of Evolutionary Algorithms
A. Eiben; Horvath, Mark; Kowalczyk, Wojtek; Schut, Martijn
2007-01-01
The research reported in this paper is concerned with assessing the usefulness of reinforcment learning (RL) for on-line calibration of parameters in evolutionary algorithms (EA). We are running an RL procedure and the EA simultaneously and the RL is changing the EA parameters on-the-fly. We evaluate this approach experimentally on a range of fitness landscapes with varying degrees of ruggedness. The results show that EA calibrated by the RL-based approach outperforms a benchmark EA.
A Simple Algorithm for Eye Detection and Cursor Control
Surashree Kulkarni; Sagar Gala
2013-01-01
This paper presents an effective albeit simple technique to perform mouse cursor movement by first detecting the user’s eyes, and then calculating the position on screen at which the user is looking. The idea of our paper is to use a series of steps for image processing, and then use a certain algorithm to convert screen coordinates to world coordinates. For users without spectacles, the formula works quite well.
Institute of Scientific and Technical Information of China (English)
Minglei Fu; Zichun Le
2009-01-01
A novel assembly control algorithm named burst-size feedback adaptive assembly period(BFAAP)is proposed.The major difference between BFAAP and other similar adaptive assembly algorithms is that the control curve of BFAAP is dynamically adjusted according to the feedback of outgoing burst size.BFAAP is compared with two typical algorithms fixed assembly period(FAP)aild min-burst length max assembly period(MBMAP)in simulation in terms of burst size distribution and assembly period.Moreover,the transmission control protocol(TCP)performance over BFAAP is also considered and simulated.
Time-optimal monotonic convergent algorithms for the control of quantum systems
Lapert, M; Sugny, D
2012-01-01
We present a new formulation of monotonically convergent algorithms which allows to optimize both the control duration and the field fluence. A standard algorithm designs a control field of fixed duration which both brings the system close to the target state and minimizes its fluence, whereas here we include in addition the optimization of the duration in the cost functional. We apply this new algorithm to the control of spin systems in Nuclear Magnetic Resonance. We show how to implement CNOT gates in systems of two and four coupled spins.
International Nuclear Information System (INIS)
In this paper, genetic algorithms are used in the design and robustification various mo el-ba ed/non-model-based fuzzy-logic controllers for robotic manipulators. It is demonstrated that genetic algorithms provide effective means of designing the optimal set of fuzzy rules as well as the optimal domains of associated fuzzy sets in a new class of model-based-fuzzy-logic controllers. Furthermore, it is shown that genetic algorithms are very effective in the optimal design and robustification of non-model-based multivariable fuzzy-logic controllers for robotic manipulators
Cabaret, S; Coppier, H; Rachid, A; Barillère, R; CERN. Geneva. IT Department
2007-01-01
The GCS (Gas Control System) project team at CERN uses a Model Driven Approach with a Framework - UNICOS (UNified Industrial COntrol System) - based on PLC (Programming Language Controller) and SCADA (Supervisory Control And Data Acquisition) technologies. The first' UNICOS versions were able to provide a PID (Proportional Integrative Derivative) controller whereas the Gas Systems required more advanced control strategies. The MultiController is a new UNICOS object which provides the following advanced control algorithms: Smith Predictor, PFC (Predictive Function Control), RST* and GPC (Global Predictive Control). Its design is based on a monolithic entity with a global structure definition which is able to capture the desired set of parameters of any specific control algorithm supported by the object. The SCADA system -- PVSS - supervises the MultiController operation. The PVSS interface provides users with supervision faceplate, in particular it links any MultiController with recipes: the GCS experts are ab...
Cull, R. C.; Eltimsahy, A. H.
1983-01-01
The present investigation is concerned with the formulation of energy management strategies for stand-alone photovoltaic (PV) systems, taking into account a basic control algorithm for a possible predictive, (and adaptive) controller. The control system controls the flow of energy in the system according to the amount of energy available, and predicts the appropriate control set-points based on the energy (insolation) available by using an appropriate system model. Aspects of adaptation to the conditions of the system are also considered. Attention is given to a statistical analysis technique, the analysis inputs, the analysis procedure, and details regarding the basic control algorithm.
Tilt Servo Control by Intelligent Algorithm in Holographic Data Storage System
Kim, Jang Hyun; Jeong, Wooyoung; Yang, Hyunseok
2013-09-01
Tracking servo and tilt servo control are very important research in holographic data storage system. In this paper, we propose intelligent servo control by fuzzy rules in holographic data storage system. Hence, we have found pattern of tilt servo control in holographic data storage system through fuzzy system. Fuzzy rules were generated by subtractive clustering algorithm for controlling tilt servo. Therefore, we control tilt servo using fuzzy rules in holographic data storage system. Consequently, practical pattern of tilt servo control was found by intelligence algorithm in holographic data storage system.
Control Algorithms of Propulsion Unit with Induction Motors for Electric Vehicle
Directory of Open Access Journals (Sweden)
PALACKY, P.
2014-05-01
Full Text Available The article deals with the research of algorithms for controlling electronic differential and differential lock of an electrically driven vehicle. The simulation part addresses the development of algorithms suitable for the implementation into a real system of a road vehicle. The algorithms are then implemented into a vehicle, a propulsion unit of which is consists of two separate electric drives with induction motors fed by voltage inverters with own control units using advanced signal processors. Communication among control units is provided by means of SPI interface. A method of vector control is used for the control of induction motors. The developed algorithms are experimentally verified for correct function in a laboratory using a roll test stand and while driving an electrically driven vehicle on the road.
Simulation and Tuning of PID Controllers using Evolutionary Algorithms
K.R.S. Narayanan; T. Jayanthi; T. Lakshmi Priyanka; S.A.V. Satya Murty
2012-01-01
The Proportional Integral Derivative (PID) controller is the most widely used control strategy in the Industry. The popularity of PID controllers can be attributed to their robust performance in a wide range of operating conditions and partly to their functional simplicity. The process of setting of PID controller can be determined as an optimization task. Over the years, use of intelligent strategies for tuning of these controllers has been growing. Biologically inspired evolutionary strateg...
National Aeronautics and Space Administration — SSCI proposes to develop and test a framework referred to as the ADVANCE (Algorithm Design and Validation for Adaptive Nonlinear Control Enhancement), within which...
Fault Tolerant Control Using Proportional-Integral-Derivative Controller Tuned by Genetic Algorithm
Directory of Open Access Journals (Sweden)
S. Kanthalakshmi
2011-01-01
Full Text Available Problem statement: The growing demand for reliability, maintainability and survivability in industrial processes has drawn significant research in fault detection and fault tolerant control domain. A fault is usually defined as an unexpected change in a system, such as component malfunction and variations in operating condition, which tends to degrade the overall system performance. The purpose of fault detection is to detect these malfunctions to take proper action in order to prevent faults from developing into a total system failure. Approach: In this study an effective integrated fault detection and fault tolerant control scheme was developed for a class of LTI system. The scheme was based on a Kalman filter for simultaneous state and fault parameter estimation, statistical decisions for fault detection and activation of controller reconfiguration. Proportional-Integral-Derivative (PID control schemes continue to provide the simplest and yet effective solutions to most of the control engineering applications today. Determination or tuning of the PID parameters continues to be important as these parameters have a great influence on the stability and performance of the control system. In this study GA was proposed to tune the PID controller. Results: The results reflect that proposed scheme improves the performance of the process in terms of time domain specifications, robustness to parametric changes and optimum stability. Also, A comparison with the conventional Ziegler-Nichols method proves the superiority of GA based system. Conclusion: This study demonstrates the effectiveness of genetic algorithm in tuning of a PID controller with optimum parameters. It is, moreover, proved to be robust to the variations in plant dynamic characteristics and disturbances assuring a parameter-insensitive operation of the process.
Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm
Directory of Open Access Journals (Sweden)
Feifei Dong
2014-01-01
Full Text Available Considering that common subsynchronous resonance controllers cannot adapt to the characteristics of the time-varying and nonlinear behavior of a power system, the cosine migration model, the improved migration operator, and the mutative scale of chaos and Cauchy mutation strategy are introduced into an improved biogeography-based optimization (IBBO algorithm in order to design an optimal subsynchronous damping controller based on the mechanism of suppressing SSR by static var compensator (SVC. The effectiveness of the improved controller is verified by eigenvalue analysis and electromagnetic simulations. The simulation results of Jinjie plant indicate that the subsynchronous damping controller optimized by the IBBO algorithm can remarkably improve the damping of torsional modes and thus effectively depress SSR, and ensure the safety and stability of units and power grid operation. Moreover, the IBBO algorithm has the merits of a faster searching speed and higher searching accuracy in seeking the optimal control parameters over traditional algorithms, such as BBO algorithm, PSO algorithm, and GA algorithm.
Generalized cyclic algorithms for formation acquisition and control
Ramirez-Riberos, Jaime; Slotine, Jean-Jacques
2010-01-01
This paper presents a new approach to distributed nonlinear control for formation acquisition and maintenance, inspired by recent results on cyclic topologies and based on tools from contraction theory. First, simple nonlinear control laws are derived to achieve global exponential convergence to basic symmetric formations. Next, convergence to more complex structures is obtained using control laws based on the idea of convergence primitives, linear combinations of basic control elements. All ...
Different Control Algorithms for a Platoon of Autonomous Vehicles
Directory of Open Access Journals (Sweden)
Zoran Gacovski
2014-05-01
Full Text Available This paper presents a concept of platoon movement of autonomous vehicles (smart cars. These vehicles have Adaptive or Advanced cruise control (ACC system also called Intelligent cruise control (ICC or Adaptive Intelligent cruise control (AICC system. The vehicles are suitable to follow other vehicles on desired distance and to be organized in platoons. To perform a research on the control and stability of an AGV (Automated Guided Vehicles string, we have developed a car-following model. To do this, first a single vehicle is modeled and since all cars in the platoon have the same dynamics, the single vehicle model is copied ten times to form model of platoon (string with ten vehicles. To control this string, we have applied equal PID controllers to all vehicles, except the leading vehicle. These controllers try to keep the headway distance as constant as possible and the velocity error between subsequent vehicles - small. For control of vehicle with nonlinear dynamics combination of feedforward control and feedback control approach is used. Feedforward control is based on the inverse model of nominal dynamics of the vehicle, and feedback PID control is designed based on the linearized model of the vehicle. For simulation and analysis of vehicle and platoon of vehicles – we have developed Matlab/Simulink models. Simulation results, discussions and conclusions are given at the end of the paper.
Control algorithm for multiscale flow simulations of water
DEFF Research Database (Denmark)
Kotsalis, E. M.; Walther, Jens Honore; Kaxiras, E.;
2009-01-01
We present a multiscale algorithm to couple atomistic water models with continuum incompressible flow simulations via a Schwarz domain decomposition approach. The coupling introduces an inhomogeneity in the description of the atomistic domain and prevents the use of periodic boundary conditions....... The use of a mass conserving specular wall results in turn to spurious oscillations in the density profile of the atomistic description of water. These oscillations can be eliminated by using an external boundary force that effectively accounts for the virial component of the pressure. In this Rapid...
Optimization of S-surface controller for autonomous underwater vehicle with immune-genetic algorithm
Institute of Scientific and Technical Information of China (English)
LI Ye; ZHANG Lei; WAN Lei; LIANG Xiao
2008-01-01
To deduce error and fussy work of manual adjustment of parameters for an S-surface controller in underwater vehicle motion control, the immune-genetic optimization of S-surface controller of an underwater vehicle was proposed. The ability of producing various antibodies for the immune algorithm, the self-adjustment of antibody density, and the antigen immune memory were used to realize the rapid convergence of S-surface controller parameters. It avoided loitering near the local peak value. Deduction of the S-surface controller was given. General process of the immune-genetic algorithm was described and immune-genetic optimization of S-surface controller parameters was discussed. Definitive results were obtained from many simulation experiments and lake experiments, which indicate that the algorithm can get good effect in optimizing the nonlinear motion controller parameters of an underwater vehicle.
The Ways of Fuzzy Control Algorithms Using for Harvesting Machines Tracking
Directory of Open Access Journals (Sweden)
L. Tóth
2013-09-01
Full Text Available This contribution is oriented to ways of a fuzzy regulation using for machine tracking of the harvest machines. The main aim of this work was to practice verify and evaluate of functionality of control fuzzy algorithms for an Ackerman’s chassis which are generally used in agriculture machines for the crops harvesting. Design of the fuzzy control algorithm was focused to the wall following algorithm and obstacle avoidance. To achieve of the reliable results was made the real model of vehicle with Ackerman’s chassis type, which was controlled by PC with using development board Stellaris LM3S8962 based on ARM processor. Fuzzy control algorithms were developed in LabView application. Deviations were up to 0.2 m, which can be reduced to 0.1 m by hardware changing.
Elevator Group-Control Policy Based on Neural Network Optimized by Genetic Algorithm
Institute of Scientific and Technical Information of China (English)
SHEN Hong; WAN Jianru; ZHANG Zhichao; LIU Yingpei; LI Guangye
2009-01-01
Aiming at the diversity and nonlinearity of the elevator system control target, an effective group method based on a hybrid algorithm of genetic algorithm and neural network is presented in this paper. The genetic algo-rithm is used to search the weight of the neural network. At the same time, the multi-objective-based evaluation function is adopted, in which there are three main indicators including the passenger waiting time, car passengers number and the number of stops. Different weights are given to meet the actual needs. The optimal values of the evaluation function are obtained, and the optimal dispatch control of the elevator group control system based on neural network is realized. By analyzing the running of the elevator group control system, all the processes and steps are presented. The validity of the hybrid algorithm is verified by the dynamic imitation performance.
Well Control Optimization using Derivative-Free Algorithms and a Multiscale Approach
Wang, Xiang; Feng, Qihong
2015-01-01
In this paper, we use numerical optimization algorithms and a multiscale approach in order to find an optimal well management strategy over the life of the reservoir. The large number of well rates for each control step make the optimization problem more difficult and at a high risk of achieving a suboptimal solution. Moreover, the optimal number of adjustments is not known a priori. Adjusting well controls too frequently will increase unnecessary well management and operation cost, and an excessively low number of control adjustments may not be enough to obtain a good yield. We investigate three derivative-free optimization algorithms, chosen for their robust and parallel nature, to determine optimal well control strategies. The algorithms chosen include generalized pattern search (GPS), particle swarm optimization (PSO) and covariance matrix adaptation evolution strategy (CMA-ES). These three algorithms encompass the breadth of available black-box optimization strategies: deterministic local search, stochas...
National Aeronautics and Space Administration — SSCI is proposing to develop a set of topology control algorithms for a formation flying spacecraft that can be used to design and evaluate candidate formation...
National Aeronautics and Space Administration — SSCI is proposing to develop, test and deliver a set of topology control algorithms and software for a formation flying spacecraft that can be used to design and...
Ant colony optimization algorithm and its application to Neuro-Fuzzy controller design
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
An adaptive ant colony algorithm is proposed based on dynamically adjusting the strategy of updating trail information.The algorithm can keep good balance between accelerating convergence and averting precocity and stagnation.The results of function optimization show that the algorithm has good searching ability and high convergence speed.The algorithm is employed to design a neuro-fuzzy controller for real-time control of an inverted pendulum.In order to avoid the combinatorial explosion of fuzzy.rules due to multivariable inputs,a state variable synthesis scheme is emploved to reduce the number of fuzzy rules greatly.The simulation results show that the designed controller can control the inverted pendulum successfully.
Active Engine Mounting Control Algorithm Using Neural Network
Directory of Open Access Journals (Sweden)
Fadly Jashi Darsivan
2009-01-01
Full Text Available This paper proposes the application of neural network as a controller to isolate engine vibration in an active engine mounting system. It has been shown that the NARMA-L2 neurocontroller has the ability to reject disturbances from a plant. The disturbance is assumed to be both impulse and sinusoidal disturbances that are induced by the engine. The performance of the neural network controller is compared with conventional PD and PID controllers tuned using Ziegler-Nichols. From the result simulated the neural network controller has shown better ability to isolate the engine vibration than the conventional controllers.
A Novel Control algorithm based DSTATCOM for Load Compensation
R, Sreejith; Pindoriya, Naran M.; Srinivasan, Babji
2015-11-01
Distribution Static Compensator (DSTATCOM) has been used as a custom power device for voltage regulation and load compensation in the distribution system. Controlling the switching angle has been the biggest challenge in DSTATCOM. Till date, Proportional Integral (PI) controller is widely used in practice for load compensation due to its simplicity and ability. However, PI Controller fails to perform satisfactorily under parameters variations, nonlinearities, etc. making it very challenging to arrive at best/optimal tuning values for different operating conditions. Fuzzy logic and neural network based controllers require extensive training and perform better under limited perturbations. Model predictive control (MPC) is a powerful control strategy, used in the petrochemical industry and its application has been spread to different fields. MPC can handle various constraints, incorporate system nonlinearities and utilizes the multivariate/univariate model information to provide an optimal control strategy. Though it finds its application extensively in chemical engineering, its utility in power systems is limited due to the high computational effort which is incompatible with the high sampling frequency in these systems. In this paper, we propose a DSTATCOM based on Finite Control Set Model Predictive Control (FCS-MPC) with Instantaneous Symmetrical Component Theory (ISCT) based reference current extraction is proposed for load compensation and Unity Power Factor (UPF) action in current control mode. The proposed controller performance is evaluated for a 3 phase, 3 wire, 415 V, 50 Hz distribution system in MATLAB Simulink which demonstrates its applicability in real life situations.
The Phase-locked loop Algorithm of the Function Generation Controller
Magrans De Abril, Marc; King, Quentin
2015-01-01
This paper describes the phase-locked loop algorithms that are used by the real-time power converter controllers at CERN. The algorithms allow the recovery of the machine time and events received by an embedded controller through WorldFIP or Ethernet-based fieldbuses. During normal operation, the algorithm provides less than 10 _s of time precision and 0.5 _s of clock jitter for the WorldFIP case, and less than 2.5 _s of time precision and 40 ns of clock jitter for the Ethernet case.
Chaos control of ferroresonance system based on RBF-maximum entropy clustering algorithm
International Nuclear Information System (INIS)
With regards to the ferroresonance overvoltage of neutral grounded power system, a maximum-entropy learning algorithm based on radial basis function neural networks is used to control the chaotic system. The algorithm optimizes the object function to derive learning rule of central vectors, and uses the clustering function of network hidden layers. It improves the regression and learning ability of neural networks. The numerical experiment of ferroresonance system testifies the effectiveness and feasibility of using the algorithm to control chaos in neutral grounded system
Oscillation Control Algorithms for Resonant Sensors with Applications to Vibratory Gyroscopes
Directory of Open Access Journals (Sweden)
Sung Kyung Hong
2009-07-01
Full Text Available We present two oscillation control algorithms for resonant sensors such as vibratory gyroscopes. One control algorithm tracks the resonant frequency of the resonator and the other algorithm tunes it to the specified resonant frequency by altering the resonator dynamics. Both algorithms maintain the specified amplitude of oscillations. The stability of each of the control systems is analyzed using the averaging method, and quantitative guidelines are given for selecting the control gains needed to achieve stability. The effects of displacement measurement noise on the accuracy of tracking and estimation of the resonant frequency are also analyzed. The proposed control algorithms are applied to two important problems in a vibratory gyroscope. The first is the leading-following resonator problem in the drive axis of MEMS dual-mass vibratory gyroscope where there is no mechanical linkage between the two proof-masses and the second is the on-line modal frequency matching problem in a general vibratory gyroscope. Simulation results demonstrate that the proposed control algorithms are effective. They ensure the proof-masses to oscillate in an anti-phase manner with the same resonant frequency and oscillation amplitude in a dual-mass gyroscope, and two modal frequencies to match in a general vibratory gyroscope.
A Review of Router based Congestion Control Algorithms
Directory of Open Access Journals (Sweden)
Vandana Kushwaha
2013-11-01
Full Text Available This paper presents a study of Router based Congestion control approaches in wired network. As network is considered as a distributed system, any problem arises in such a system requires a distributed solution. Thus for good congestion control in the network we also need a solution distributed at source as well as router ends. The purpose of this study is to review the router based Congestion control research for wired network and characterize the different approaches to Congestion control design, by considering their advantages and limitations.
Machnes, S; Glaser, S J; de Fouquieres, P; Gruslys, A; Schirmer, S; Schulte-Herbrueggen, T
2010-01-01
For paving the way to novel applications in quantum simulation, computation, and technology, increasingly large quantum systems have to be steered with high precision. It is a typical task amenable to numerical optimal control to turn the time course of pulses, i.e. piecewise constant control amplitudes, iteratively into an optimised shape. Here, we present the first comparative study of optimal control algorithms for a wide range of finite-dimensional applications. We focus on the most commonly used algorithms: GRAPE methods which update all controls concurrently, and KROTOV-type methods which do so sequentially. Guidelines for their use are given and open research questions are pointed out. --- Moreover we introduce a novel unifying algorithmic framework, DYNAMO (Dynamic Optimisation Platform) designed to provide the quantum-technology community with a convenient MATLAB-based toolset for optimal control. In addition, it gives researchers in optimal-control techniques a framework for benchmarking and compari...
A distributed admission approach based on marking mechanism over Bluetooth best-effort network
DEFF Research Database (Denmark)
Son, L.T.; Schiøler, Henrik; Madsen, Ole Brun
2002-01-01
The end-to-end Quality of Service delivered in Bluetooth networks depends on a large number of parameters at different levels, e.g. link capacity, packet delays, etc, which are requested in certain patterns and controlled by various algorithms. In this paper, a method of adaptive distributed...... admission with end-to-end Quality of Service (QoS) provisions based marking information for real time and non real time traffics in Bluetooth networks is highlighted, its mathematical background is analyzed and a simulation with bursty traffic sources, Interrupted Bernoulli Process (IBP), is carried out....... The simulation results show that the performance of Bluetooth network is improved when applying the distributed admission method....
Efficient Nonlinear Programming Algorithms for Chemical Process Control and Operations
Biegler, Lorenz T.
Optimization is applied in numerous areas of chemical engineering including the development of process models from experimental data, design of process flowsheets and equipment, planning and scheduling of chemical process operations, and the analysis of chemical processes under uncertainty and adverse conditions. These off-line tasks require the solution of nonlinear programs (NLPs) with detailed, large-scale process models. Recently, these tasks have been complemented by time-critical, on-line optimization problems with differential-algebraic equation (DAE) process models that describe process behavior over a wide range of operating conditions, and must be solved sufficiently quickly. This paper describes recent advances in this area especially with dynamic models. We outline large-scale NLP formulations and algorithms as well as NLP sensitivity for on-line applications, and illustrate these advances on a commercial-scale low density polyethylene (LDPE) process.
Online Model Learning Algorithms for Actor-Critic Control
Grondman, I.
2015-01-01
Classical control theory requires a model to be derived for a system, before any control design can take place. This can be a hard, time-consuming process if the system is complex. Moreover, there is no way of escaping modelling errors. As an alternative approach, there is the possibility of having
Benchmarking Advanced Control Algorithms for a Laser Scanner System
DEFF Research Database (Denmark)
Stoustrup, Jakob; Ordys, A.W.; Smillie, I.
1996-01-01
The paper describes tests performed on the laser scanner system toassess feasibility of modern control techniques in achieving a requiredperformance in the trajectory following problem. The two methods tested areQTR H-infinity and Predictive Control. The results are ilustated ona simulation example....
A robust total compensation algorithm for the torque control of a synchronous servomotor
Le Pioufle, Bruno; Georgiou, G.; Louis, J.-P.
1992-01-01
In this paper, we present a performing torque controller for a synchronous servomotor. As we will see, this controller, called the total compensation controller, brings a new solution to the defects of the well known proportional integral controller in the D-Q frame, omnipresent in industrial applications. Here, we propose a comparative study of these two algorithms, the main problem of the proportional integral controller in the D-Q frame being its high sensitivity to the speed's dynamics. W...
International Nuclear Information System (INIS)
Reactive power dispatch for voltage profile modification has been of interest to power utilities. Usually local bus voltages can be altered by changing generator voltages, reactive shunts, ULTC transformers and SVCs. Determination of optimum values for control parameters, however, is not simple for modern power system networks. Heuristic and rather intelligent algorithms have to be sought. In this paper a new algorithm is proposed that is based on a variant of a genetic algorithm combined with simulated annealing updates. In this algorithm a fuzzy multi-objective a approach is used for the fitness function of the genetic algorithm. This fuzzy multi-objective function can efficiently modify the voltage profile in order to minimize transmission lines losses, thus reducing the operating costs. The reason for such a combination is to utilize the best characteristics of each method and overcome their deficiencies. The proposed algorithm is much faster than the classical genetic algorithm and cna be easily integrated into existing power utilities software. The proposed algorithm is tested on an actual system model of 1284 buses, 799 lines, 1175 fixed and ULTC transformers, 86 generators, 181 controllable shunts and 425 loads
A chaos-based image encryption algorithm with variable control parameters
International Nuclear Information System (INIS)
In recent years, a number of image encryption algorithms based on the permutation-diffusion structure have been proposed. However, the control parameters used in the permutation stage are usually fixed in the whole encryption process, which favors attacks. In this paper, a chaos-based image encryption algorithm with variable control parameters is proposed. The control parameters used in the permutation stage and the keystream employed in the diffusion stage are generated from two chaotic maps related to the plain-image. As a result, the algorithm can effectively resist all known attacks against permutation-diffusion architectures. Theoretical analyses and computer simulations both confirm that the new algorithm possesses high security and fast encryption speed for practical image encryption.
A FUZZY-LOGIC CONTROL ALGORITHM FOR ACTIVE QUEUE MANAGEMENT IN IP NETWORKS
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Active Queue Management (AQM) is an active research area in the Internet community. Random Early Detection (RED) is a typical AQM algorithm, but it is known that it is difficult to configure its parameters and its average queue length is closely related to the load level. This paper proposes an effective fuzzy congestion control algorithm based on fuzzy logic which uses the predominance of fuzzy logic to deal with uncertain events. The main advantage of this new congestion control algorithm is that it discards the packet dropping mechanism of RED, and calculates packet loss according to a preconfigured fuzzy logic by using the queue length and the buffer usage ratio. Theoretical analysis and Network Simulator (NS) simulation results show that the proposed algorithm achieves more throughput and more stable queue length than traditional schemes. It really improves a router's ability in network congestion control in IP network.
International Nuclear Information System (INIS)
Research highlights: → A closed-loop fuzzy logic controller based on the particle swarm optimization algorithm was proposed for controlling the power level of nuclear research reactors. → The proposed control system was tested for various initial and desired power levels, and it could control the reactor successfully for most situations. → The proposed controller is robust against the disturbances. - Abstract: In this paper, a closed-loop fuzzy logic controller based on the particle swarm optimization algorithm is proposed for controlling the power level of nuclear research reactors. The principle of the fuzzy logic controller is based on the rules constructed from numerical experiments made by means of a computer code for the core dynamics calculation and from human operator's experience and knowledge. In addition to these intuitive and experimental design efforts, consequent parts of the fuzzy rules are optimally (or near optimally) determined using the particle swarm optimization algorithm. The contribution of the proposed algorithm to a reactor control system is investigated in details. The performance of the controller is also tested with numerical simulations in numerous operating conditions from various initial power levels to desired power levels, as well as under disturbance. It is shown that the proposed control system performs satisfactorily under almost all operating conditions, even in the case of very small initial power levels.
Extracting quantum dynamics from genetic learning algorithms through principal control analysis
International Nuclear Information System (INIS)
Genetic learning algorithms are widely used to control ultrafast optical pulse shapes for photo-induced quantum control of atoms and molecules. An unresolved issue is how to use the solutions found by these algorithms to learn about the system's quantum dynamics. We propose a simple method based on covariance analysis of the control space, which can reveal the degrees of freedom in the effective control Hamiltonian. We have applied this technique to stimulated Raman scattering in liquid methanol. A simple model of two-mode stimulated Raman scattering is consistent with the results. (letter to the editor)
Optimization of PID controller based on The Bees Algorithm for one leg of a quadruped robot
Directory of Open Access Journals (Sweden)
Bakırcıoğlu Veli
2016-01-01
Full Text Available In this paper, we apply The Bees Algorithm to find optimal PID controller gains to control angular positions of robot leg joints with the minimum position error. In order to present more realistic simulation, system modelled in MATLAB/Simulink environment which is close to experimental set up. Solid model of system, which has two degrees of freedom, drawn by using a CAD software. Required physical specifications of robot leg for MATLAB/Simulink modelling is obtained from this CAD model. Controller of the system is designed in MATLAB/Simulink interface. Simulation results derived to show effectiveness of The Bees Algorithm to find optimal PID controller gains.
Study of predictive control algorithms for parallel robot structures
Czech Academy of Sciences Publication Activity Database
Belda, Květoslav; Böhm, Josef; Valášek, M.
Pardubice: University of Pardubice, 2004 - (Krejčí, S.; Taufer, I.), s. 1-9 ISBN 80-7194-662-1. [Process Control 2004 - ŘÍP 2004 /6./. Kouty nad Desnou (CZ), 08.06.2004-11.06.2004] R&D Projects: GA ČR GA101/03/0620 Grant ostatní: IG CTU(CZ) 0406413 Institutional research plan: CEZ:AV0Z1075907 Keywords : generalized predictive control * parallel robot structures * nonlinear prediction Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0106269.pdf
Directory of Open Access Journals (Sweden)
Iraj Hassanzadeh
2008-01-01
Full Text Available The Rotary Inverted Pendulum (RIP system is a significant classical problem of control engineering which has been investigated in the past decades. This study presents an optimum Input-Output Feedback Linearization (IOFL cascade controller utilized Genetic Algorithm (GA. Due to the non-minimum phase behavior of the system, IOFL controller leads to unstable internal dynamics. Therefore a cascade structure is proposed consisting IOFL controller for inner loop with PD controller forming the outer loop. The primary design goal is to balance the pendulum in an inverted position. The control criterion is to minimize the Integral Absolute Error (IAE of system angles. By minimizing the objective function related to IAE using Binary Genetic Algorithm (BGA, the optimal controller parameters can be assigned. The results verified capability and competent characteristics of the proposed controller. The method can be considered as a promising way for control of various similar nonlinear and under-actuated systems.
Incremental Sampling Algorithms for Robust Propulsion Control Project
National Aeronautics and Space Administration — Aurora Flight Sciences proposes to develop a system for robust engine control based on incremental sampling, specifically Rapidly-Expanding Random Tree (RRT)...
Model Predictive Control Algorithms for Pen and Pump Insulin Administration
Boiroux, Dimitri; Jørgensen, John Bagterp; Poulsen, Niels Kjølstad; Madsen, Henrik
2012-01-01
Despite recent developments within diabetes management such as rapidacting insulin, continuous glucose monitors (CGM) and insulin pumps, tight blood glucose control still remains a challenge. A fully automated closedloop controller, also known as an artificial pancreas (AP), has the potential to ease the life and reduce the risk of acute and chronic diabetic complications. However, the noise associated to CGMs, the long insulin action time for continuous subcutaneous infusion of insulin (CSII...
Randomized Algorithms for Analysis and Control of Uncertain Systems With Applications
Tempo, Roberto; Dabbene, Fabrizio
2013-01-01
The presence of uncertainty in a system description has always been a critical issue in control. The main objective of Randomized Algorithms for Analysis and Control of Uncertain Systems, with Applications (Second Edition) is to introduce the reader to the fundamentals of probabilistic methods in the analysis and design of systems subject to deterministic and stochastic uncertainty. The approach propounded by this text guarantees a reduction in the computational complexity of classical control algorithms and in the conservativeness of standard robust control techniques. The second edition has been thoroughly updated to reflect recent research and new applications with chapters on statistical learning theory, sequential methods for control and the scenario approach being completely rewritten. Features: · self-contained treatment explaining Monte Carlo and Las Vegas randomized algorithms from their genesis in the principles of probability theory to their use for system analysis; · ...
Learning tensegrity locomotion using open-loop control signals and coevolutionary algorithms.
Iscen, Atil; Caluwaerts, Ken; Bruce, Jonathan; Agogino, Adrian; SunSpiral, Vytas; Tumer, Kagan
2015-01-01
Soft robots offer many advantages over traditional rigid robots. However, soft robots can be difficult to control with standard control methods. Fortunately, evolutionary algorithms can offer an elegant solution to this problem. Instead of creating controls to handle the intricate dynamics of these robots, we can simply evolve the controls using a simulation to provide an evaluation function. In this article, we show how such a control paradigm can be applied to an emerging field within soft robotics: robots based on tensegrity structures. We take the model of the Spherical Underactuated Planetary Exploration Robot ball (SUPERball), an icosahedron tensegrity robot under production at NASA Ames Research Center, develop a rolling locomotion algorithm, and study the learned behavior using an accurate model of the SUPERball simulated in the NASA Tensegrity Robotics Toolkit. We first present the historical-average fitness-shaping algorithm for coevolutionary algorithms to speed up learning while favoring robustness over optimality. Second, we use a distributed control approach by coevolving open-loop control signals for each controller. Being simple and distributed, open-loop controllers can be readily implemented on SUPERball hardware without the need for sensor information or precise coordination. We analyze signals of different complexities and frequencies. Among the learned policies, we take one of the best and use it to analyze different aspects of the rolling gait, such as lengths, tensions, and energy consumption. We also discuss the correlation between the signals controlling different parts of the tensegrity robot. PMID:25951199
Issues in College Admissions Testing.
Noble, Julie P.; Camara, Wayne J.
College admissions tests provide a standardized and objective measure of student achievement and generalized skills. Unlike high school grades or rank, admission tests are a common measure for comparing students who have attended different high schools, completed different courses, received different grades in courses taught by different teachers,…
Robust PD Sway Control of a Lifted Load for a Crane Using a Genetic Algorithm
Kawada, Kazuo; Sogo, Hiroyuki; Yamamoto, Toru; Mada, Yasuhiro
PID control schemes still continue to be widely used for most industrial control systems. This is mainly because PID controllers have simple control structures, and are simple to maintain and tune. However, it is difficult to find a set of suitable control parameters in the case of time-varying and/or nonlinear systems. For such a problem, the robust controller has been proposed.Although it is important to choose the suitable nominal model in designing the robust controller, it is not usually easy.In this paper, a new robust PD controller design scheme is proposed, which utilizes a genetic algorithm.
An algorithm for formation control of mobile robots
Directory of Open Access Journals (Sweden)
Ćosić Aleksandar
2013-01-01
Full Text Available Solution of the formation guidance in structured static environments is presented in this paper. It is assumed that high level planner is available, which generates collision free trajectory for the leader robot. Leader robot is forced to track generated trajectory, while followers’ trajectories are generated based on the trajectory realized by the real leader. Real environments contain large number of static obstacles, which can be arbitrarily positioned. Hence, formation switching becomes necessary in cases when followers can collide with obstacles. In order to ensure trajectory tracking, as well as object avoidance, control structure with several controllers of different roles (trajectory tracking, obstacle avoiding, vehicle avoiding and combined controller has been adopted. Kinematic model of differentially driven two-wheeled mobile robot is assumed. Simulation results show the efficiency of the proposed approach. [Projekat Ministarstva nauke Republike Srbije, br. TR-35003 i br. III-44008
Spacecraft Magnetic Control Using Dichotomous Coordinate Descent Algorithm with Box Constraints
Directory of Open Access Journals (Sweden)
Rune Schlanbusch
2010-10-01
Full Text Available In this paper we present magnetic control of a spacecraft using the Dichotomous Coordinate Descent (DCD algorithm with box constraints. What is common for most work on magnetic spacecraft control is the technique for solving for the control variables of the magnetic torquers where a cross product is included which is well known to be singular. The DCD algorithm provides a new scheme which makes it possible to use a general control law and then adapt it to work for magnetic torquers including restrictions in available magnetic moment, instead of designing a specialized controller for the magnetic control problem. A non-linear passivity-based sliding surface controller is derived for a fully actuated spacecraft and is then implemented for magnetic control by utilizing the previous mentioned algorithm. Results from two simulations are provided, the first comparing the results from the DCD algorithm with older results, and the second showing how easily the derived sliding surface controller may be implemented, improving our results.
Bat algorithm optimized fuzzy PD based speed controller for brushless direct current motor
Directory of Open Access Journals (Sweden)
K. Premkumar
2016-06-01
Full Text Available In this paper, design of fuzzy proportional derivative controller and fuzzy proportional derivative integral controller for speed control of brushless direct current drive has been presented. Optimization of the above controllers design is carried out using nature inspired optimization algorithms such as particle swarm, cuckoo search, and bat algorithms. Time domain specifications such as overshoot, undershoot, settling time, recovery time, and steady state error and performance indices such as root mean squared error, integral of absolute error, integral of time multiplied absolute error and integral of squared error are measured and compared for the above controllers under different operating conditions such as varying set speed and load disturbance conditions. The precise investigation through simulation is performed using simulink toolbox. From the simulation test results, it is evident that bat optimized fuzzy proportional derivative controller has superior performance than the other controllers considered. Experimental test results have also been taken and analyzed for the optimal controller identified through simulation.
A Modern Control Theory Based Algorithm for Control of the NASA/JPL 70-Meter Antenna Axis Servos
Hill, R. E.
1987-09-01
A digital computer-based state variable controller has been designed and applied to the 70-m antenna azis servos. The general equations and structure of the algorithm and provisions for alternate position error feedback modes to accomodate intertarget slew, encoder references tracking, and precision tracking modes are described. Development of the discrete time domain control model and computation of estimator and control gain parameters based on closed loop pole placement criteria are discussed. The new algorithm has been successfully implemented and tested in the 70-m antenna at Deep Space Station (DSS) 63 in Spain.
A modern control theory based algorithm for control of the NASA/JPL 70-meter antenna axis servos
Hill, R. E.
1987-01-01
A digital computer-based state variable controller was designed and applied to the 70-m antenna axis servos. The general equations and structure of the algorithm and provisions for alternate position error feedback modes to accommodate intertarget slew, encoder referenced tracking, and precision tracking modes are descibed. Development of the discrete time domain control model and computation of estimator and control gain parameters based on closed loop pole placement criteria are discussed. The new algorithm was successfully implemented and tested in the 70-m antenna at Deep Space Network station 63 in Spain.
Optimal Regulator Algorithms For The Control Of Linear Systems (ORACLS)
Frisch, Harold P.
1990-01-01
Control theory design package offers engineer full range of subroutines to manipulate and solve Linear-Quadratic-Gaussian types of problems. ORACLS is rigorous tool, intended for multi-input and multi-output dynamic systems in both continuous and discrete form. Written in FORTRAN.
Robot Control near Singularity and Joint Limit Using a Continuous Task Transition Algorithm
Hyejin Han; Jaeheung Park
2013-01-01
When robots are controlled in the task space, singularities and joint limits are among the most critical and difficult issues that can arise. In this paper, we propose a new approach for the robots to operate in the regions near singularities and joint limits using the operational space control framework. Specifically, a continuous task transition algorithm called the intermediate desired value approach is applied to the hierarchically structured controller in the operational space control fr...
A Novel Robust Communication Algorithm for Distributed Secondary Control of Islanded MicroGrids
Shafiee, Qobad; Dragicevic, Tomislav; Vasquez, Juan Carlos; Josep M. Guerrero; Stefanovic, Cedomir; Popovski, Petar
2013-01-01
Distributed secondary control (DSC) is a new approach for MicroGrids (MGs) such that frequency, voltage and power regulation is made in each unit locally to avoid using a central controller. Due to the constrained traffic pattern required by the secondary control, it is viable to implement dedicated local area communication functionality among the local controllers. This paper presents a new, wireless-based robust communication algorithm for DSC of MGs designed to avoid communication bottlene...
Fuzzy-PID control algorithm of a loop reactor for microbial corrosion testing
D. Rangel-Miranda; D. Alaniz-Lumbreras; Victor Castano
2015-01-01
The thermal control of loop reactor utilized to run hydrodynamic tests of microbical corrosion, where full control of the temperature is crucial, is presented. Since the accuracy of the temperature is critical along the pipe trajectory for the microbial culture, it must be controlled with an accuracy of ± 0.5°C, which is achieved by an implemented fuzzy-PID (Proportional Integral and Derivative) control algorithm, capable to provide the accuracy at the temperature range required. The system c...
Automatic Tuning of PID Controller for a 1-D Levitation System Using a Genetic Algorithm
DEFF Research Database (Denmark)
Yang, Zhenyu; Pedersen, Gerulf K.m.
2006-01-01
The automatic PID control design for a onedimensional magnetic levitation system is investigated. The PID controller is automatically tuned using the non-dominated sorting genetic algorithm (NSGA-II) based on a nonlinear system model. The developed controller is digitally implemented and tested....... The preliminary simulation and test results show a bright potential to use artificial intelligence methods for supporting the control design for complicated nonlinear and open-loop unstable systems....
Fuzzy Algorithm for Supervisory Voltage/Frequency Control of a Self Excited Induction Generator
Hussein F. Soliman; Abdel-Fattah Attia; S. M. Mokhymar; M. A. L. Badr
2006-01-01
This paper presents the application of a Fuzzy Logic Controller (FLC) to regulate the voltage of a Self Excited Induction Generator (SEIG) driven by Wind Energy Conversion Schemes (WECS). The proposed FLC is used to tune the integral gain (KI) of a Proportional plus Integral (PI) controller. Two types of controls, for the generator and for the wind turbine, using a FLC algorithm, are introduced in this paper. The voltage control is performed to adapt the terminal voltage via self excitation. ...
Validation of space/ground antenna control algorithms using a computer-aided design tool
Gantenbein, Rex E.
1995-01-01
The validation of the algorithms for controlling the space-to-ground antenna subsystem for Space Station Alpha is an important step in assuring reliable communications. These algorithms have been developed and tested using a simulation environment based on a computer-aided design tool that can provide a time-based execution framework with variable environmental parameters. Our work this summer has involved the exploration of this environment and the documentation of the procedures used to validate these algorithms. We have installed a variety of tools in a laboratory of the Tracking and Communications division for reproducing the simulation experiments carried out on these algorithms to verify that they do meet their requirements for controlling the antenna systems. In this report, we describe the processes used in these simulations and our work in validating the tests used.
Efficiency analysis of control algorithms in spatially distributed systems with chaotic behavior
Directory of Open Access Journals (Sweden)
Korus Łukasz
2014-12-01
Full Text Available The paper presents results of examination of control algorithms for the purpose of controlling chaos in spatially distributed systems like the coupled map lattice (CML. The mathematical definition of the CML, stability analysis as well as some basic results of numerical simulation exposing complex, spatiotemporal and chaotic behavior of the CML were already presented in another paper. The main purpose of this article is to compare the efficiency of controlling chaos by simple classical algorithms in spatially distributed systems like CMLs. This comparison is made based on qualitative and quantitative evaluation methods proposed in the previous paper such as the indirect Lyapunov method, Lyapunov exponents and the net direction phase indicator. As a summary of this paper, some conclusions which can be useful for creating a more efficient algorithm of controlling chaos in spatially distributed systems are made.
Two neural network algorithms for designing optimal terminal controllers with open final time
Plumer, Edward S.
1992-01-01
Multilayer neural networks, trained by the backpropagation through time algorithm (BPTT), have been used successfully as state-feedback controllers for nonlinear terminal control problems. Current BPTT techniques, however, are not able to deal systematically with open final-time situations such as minimum-time problems. Two approaches which extend BPTT to open final-time problems are presented. In the first, a neural network learns a mapping from initial-state to time-to-go. In the second, the optimal number of steps for each trial run is found using a line-search. Both methods are derived using Lagrange multiplier techniques. This theoretical framework is used to demonstrate that the derived algorithms are direct extensions of forward/backward sweep methods used in N-stage optimal control. The two algorithms are tested on a Zermelo problem and the resulting trajectories compare favorably to optimal control results.
A Modified LQG Algorithm (MLQG for Robust Control of Nonlinear Multivariable Systems
Directory of Open Access Journals (Sweden)
Jens G. Balchen
1993-07-01
Full Text Available The original LQG algorithm is often characterized for its lack of robustness. This is because in the design of the estimator (Kalman filter the process disturbance is assumed to be white noise. If the estimator is to give good estimates, the Kalman gain is increased which means that the estimator fails to become robust. A solution to this problem is to replace the proportional Kalman gain matrix by a dynamic PI algorithm and the proportional LQ feedback gain matrix by a PI algorithm. A tuning method is developed which facilitates the tuning of a modified LQG control system (MLQG by only two tuning parameters.
Distributed power control algorithm based on game theory for wireless sensor networks
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Energy saving is the most important issue in research and development for wireless sensor networks. A power control mechanism can reduce the power consumption of the whole network.Because the character of wireless sensor networks is restrictive energy,this paper proposes a distributed power control algorithm based on game theory for wireless sensor networks which objects of which are reducing power consumption and decreasing overhead and increasing network lifetime.The game theory and OPNET simulation shows that the power control algorithm converges to a Nash Equilibrium when decisions are updated according to a better response dynamic.
DEFF Research Database (Denmark)
Endelt, Benny Ørtoft; Volk, Wolfram
2013-01-01
, the reaction speed may be insufficient compared to the production rate in an industrial application. We propose to design an iterative learning control (ILC) algorithm which can control and update the blank-holder force as well as the distribution of the blank-holder force based on limited geometric data from......, there is a number of obstacles which need to be addressed before an industrial implementation is possible, e.g. the proposed control algorithms are often limited by the ability to sample process data with both sufficient accuracy and robustness - this lack of robust sampling technologies is one of the main barriers...
Fu, X.; S. Li; Fairbank, M.; Wunsch, D. C.; Alonso, E.
2015-01-01
This paper investigates how to train a recurrent neural network (RNN) using the Levenberg-Marquardt (LM) algorithm as well as how to implement optimal control of a grid-connected converter (GCC) using an RNN. To successfully and efficiently train an RNN using the LM algorithm, a new forward accumulation through time (FATT) algorithm is proposed to calculate the Jacobian matrix required by the LM algorithm. This paper explores how to incorporate FATT into the LM algorithm. The results show tha...
The Distribution Population-based Genetic Algorithm for Parameter Optimization PID Controller
Institute of Scientific and Technical Information of China (English)
CHENQing-Geng; WANGNing; HUANGShao-Feng
2005-01-01
Enlightened by distribution of creatures in natural ecology environment, the distribution population-based genetic algorithm (DPGA) is presented in this paper. The searching capability of the algorithm is improved by competition between distribution populations to reduce the search zone.This method is applied to design of optimal parameters of PID controllers with examples, and the simulation results show that satisfactory performances are obtained.
Design and experimental evaluation of flexible manipulator control algorithms
International Nuclear Information System (INIS)
Within the Environmental Restoration and Waste Management Program of the US Department of Energy, the remediation of single-shell radioactive waste storage tanks is one of the areas that challenge state-of-the-art equipment and methods. The use of long-reach manipulators is being seriously considered for this task. Because of high payload capacity and high length-to-cross-section ratio requirements, these long-reach manipulator systems are expected to use hydraulic actuators and to exhibit significant structural flexibility. The controller has been designed to compensate for the hydraulic actuator dynamics by using a load-compensated velocity feedforward loop and to increase the bandwidth by using an inner pressure feedback loop. Shaping filter techniques have been applied as feedforward controllers to avoid structural vibrations during operation. Various types of shaping filter methods have been investigated. Among them, a new approach, referred to as a ''feedforward simulation filter'' that uses embedded simulation, has been presented
Model classification rate control algorithm for video coding
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
A model classification rate control method for video coding is proposed. The macro-blocks are classified according to their prediction errors, and different parameters are used in the rate-quantization and distortion-quantization model.The different model parameters are calculated from the previous frame of the same type in the process of coding. These models are used to estimate the relations among rate, distortion and quantization of the current frame. Further steps,such as R-D optimization based quantization adjustment and smoothing of quantization of adjacent macroblocks, are used to improve the quality. The results of the experiments prove that the technique is effective and can be realized easily. The method presented in the paper can be a good way for MPEG and H. 264 rate control.
Autonomous Car Fuzzy Control Modeled by Iterative Genetic Algorithms
Onieva, Enrique; Alonso, Javier; Pérez Rastelli, Joshué; Milanés, Vicente; De Pedro, Teresa
2009-01-01
The techniques of Soft Computing are recognized as having a strong learning and cognition capability as well as good tolerance to uncertainty and imprecision. These properties allow them to be applied successfully to Intelligent Transportation Systems (ITS), a broad range of diverse technologies that designed to answer many transportation problems. The unmanned control of the steering wheel is one of the most important challenges faced by researchers in this area. This paper presents a method...
A novel algorithm for sensorless motion control of flexible structures
KHALIL, Islam Shoukry Mohammed; KUNT, Emrah Deniz; Sabanovic, Asif
2010-01-01
This article demonstrates the validity of using an actuator as a single platform for measurements during a motion control assignment of flexible systems kept free from any kind of measurement. System acceleration level dynamics, parameters and interaction forces with the environment are coupled in an incident reaction torque that naturally rises when a flexible system is subjected to an action imposed by an attached actuator to the system. This work attempts to decouple each of the sy...
Voltage and Reactive Power Control by Integration of Genetic Algorithm and Tabu Search
Aoki, Hidenori; Yamamoto, Kensei; Mizutani, Yoshibumi
This paper presents on the result of voltage and reactive power control by use of the proposed method. The feature of proposed method is integration of genetic algorithm (GA) and tabu search (TS). This method obtains an excellent fitness at shorter calculation time than GA considering conventional control process. The effectiveness of this method is shown by a practicable 15-bus system.
Control Algorithms Along Relative Equilibria of Underactuated Lagrangian Systems on Lie Groups
DEFF Research Database (Denmark)
Nordkvist, Nikolaj; Bullo, F.
2008-01-01
We present novel algorithms to control underactuated mechanical systems. For a class of invariant systems on Lie groups, we design iterative small-amplitude control forces to accelerate along, decelerate along, and stabilize relative equilibria. The technical approach is based upon a perturbation...
Control algorithms along relative equilibria of underactuated Lagrangian systems on Lie groups
DEFF Research Database (Denmark)
Nordkvist, Nikolaj; Bullo, Francesco
We present novel algorithms to control underactuated mechanical systems. For a class of invariant systems on Lie groups, we design iterative small-amplitude control forces to accelerate along, decelerate along, and stabilize relative equilibria. The technical approach is based upon a perturbation...
Interpolative Control for a d.c. Motor Drive With Genetic Algorithm-based Tuning
Sanda Dale
2009-01-01
There are presented main theoretical and procedural aspects related to design and implementation of interpolative controllers as well as the tuning procedure based on genetic algorithms. As a study case an interpolative control structure for the speed of a d.c. motor drive is developed. Comparisons with initial adaptive system without GA improvements are made through simulations.
Interpolative Control for a d.c. Motor Drive With Genetic Algorithm-based Tuning
Directory of Open Access Journals (Sweden)
Sanda Dale
2009-05-01
Full Text Available There are presented main theoretical and procedural aspects related to design and implementation of interpolative controllers as well as the tuning procedure based on genetic algorithms. As a study case an interpolative control structure for the speed of a d.c. motor drive is developed. Comparisons with initial adaptive system without GA improvements are made through simulations.
Pawelczak, P.; Pollin, S.; So, H.-S.W.; Bahai, A.R.S.; Prasad, R.V.; Hekmat, R.
2009-01-01
In this paper, different control channel (CC) implementations for multichannel medium access control (MAC) algorithms are compared and analyzed in the context of opportunistic spectrum access (OSA) as a function of spectrum-sensing performance and licensed user activity. The analysis is based on a d
A Sequential Shifting Algorithm for Variable Rotor Speed Control
Litt, Jonathan S.; Edwards, Jason M.; DeCastro, Jonathan A.
2007-01-01
A proof of concept of a continuously variable rotor speed control methodology for rotorcraft is described. Variable rotor speed is desirable for several reasons including improved maneuverability, agility, and noise reduction. However, it has been difficult to implement because turboshaft engines are designed to operate within a narrow speed band, and a reliable drive train that can provide continuous power over a wide speed range does not exist. The new methodology proposed here is a sequential shifting control for twin-engine rotorcraft that coordinates the disengagement and engagement of the two turboshaft engines in such a way that the rotor speed may vary over a wide range, but the engines remain within their prescribed speed bands and provide continuous torque to the rotor; two multi-speed gearboxes facilitate the wide rotor speed variation. The shifting process begins when one engine slows down and disengages from the transmission by way of a standard freewheeling clutch mechanism; the other engine continues to apply torque to the rotor. Once one engine disengages, its gear shifts, the multi-speed gearbox output shaft speed resynchronizes and it re-engages. This process is then repeated with the other engine. By tailoring the sequential shifting, the rotor may perform large, rapid speed changes smoothly, as demonstrated in several examples. The emphasis of this effort is on the coordination and control aspects for proof of concept. The engines, rotor, and transmission are all simplified linear models, integrated to capture the basic dynamics of the problem.
Measurement-Based Performance and Admission Controlin Wireless Sensor Networks
Orhan, Ibrahim; Lindh, Thomas
2011-01-01
This journal paper presents a measurement-basedperformance management system for contention-based wireless sensor networks. Its main features are admission andperformance control based on measurement data from lightweight performance meters in the endpoints. Test results showthat admission and performance control improve the predictability and level of performance. The system can also be used asa tool for dimensioning and configuration of services in wireless sensor networks. Among the rapidl...
Kleman, G L; Chalmers, J J; Luli, G W; Strohl, W R
1991-04-01
A combined predictive and feedback control algorithm based on measurements of the concentration of glucose on-line has been developed to control fed-batch fermentations of Escherichia coli. The predictive control algorithm was based on the on-line calculation of glucose demand by the culture and plotting a linear regression to the next datum point to obtain a predicted glucose demand. This provided a predictive "coarse" control for the glucose-based nutrient feed. A direct feedback control using a proportional controller, based on glucose measurements every 2 min, fine-tuned the feed rate. These combined control schemes were used to maintain glucose concentrations in fed-batch fermentations as tight as 0.49 +/- 0.04 g/liter during growth of E. coli to high cell densities. PMID:2059049
Damping of Power Systems Oscillations by using Genetic Algorithm-Based Optimal Controller
Directory of Open Access Journals (Sweden)
Akram F. Bat
2010-06-01
Full Text Available In this paper, the power system stabilizer (PSS and Thyristor controlled phase shifter(TCPS interaction is investigated . The objective of this work is to study and design a controller capable of doing the task of damping in less economical control effort, and to globally link all controllers of national network in an optimal manner , toward smarter grids . This can be well done if a specific coordination between PSS and FACTS devices , is accomplished . Firstly, A genetic algorithm-based controller is used. Genetic Algorithm (GA is utilized to search for optimum controller parameter settings that optimize a given eigenvalue based objective function. Secondly, an optimal pole shifting, based on modern control theory for multi-input multi-output systems, is used. It requires solving first order or second order linear matrix Lyapunov equation for shifting dominant poles to much better location that guaranteed less overshoot and less settling time of system transient response following a disturbance.
Lin, Jeng-Wen; Shen, Pu Fun; Wen, Hao-Ping
2015-10-01
The application of a repetitive control mechanism for use in a mechanical control system has been a topic of investigation. The fundamental purpose of repetitive control is to eliminate disturbances in a mechanical control system. This paper presents two different repetitive control laws using individual types of basis function feedback and their combinations. These laws adjust the command given to a feedback control system to eliminate tracking errors, generally resulting from periodic disturbance. Periodic errors can be reduced through linear basis functions using regression and a genetic algorithm. The results illustrate that repetitive control is most effective method for eliminating disturbances. When the data are stabilized, the tracking error of the obtained convergence value, 10-14, is the optimal solution, verifying that the proposed regression and genetic algorithm can satisfactorily reduce periodic errors.
Optimization of PID Controller for Brushless DC Motor by using Bio-inspired Algorithms
Directory of Open Access Journals (Sweden)
Sanjay Kr. Singh
2014-02-01
Full Text Available This study presents the use and comparison of various bio-inspired algorithms for optimizing the response of a PID controller for a Brushless DC Motor in contrast to the conventional methods of tuning. For the optimization of the PID controllers Genetic Algorithm, Multi-objective Genetic Algorithm and Simulated Annealing have been used. PID controller tuning with soft-computing algorithms comprises of obtaining the best possible outcome for the three PID parameters for improving the steady state characteristics and performance indices like overshoot percentage, rise time and settling time. For the calculation and simulation of the results the Brushless DC Motor model, Maxon EC 45 flat ф 45 mm with Hall Sensors Motor has been used. The results obtained the optimization using Genetic Algorithms, Multi-objective Genetic Algorithm and Simulated Annealing is compared with the ones derived from the Ziegler-Nichols method and the MATLAB SISO Tool. And it is observed that comparatively better results are obtained by optimization using Simulated Annealing offering better steady state response.
A Beacon Transmission Power Control Algorithm Based on Wireless Channel Load Forecasting in VANETs.
Mo, Yuanfu; Yu, Dexin; Song, Jun; Zheng, Kun; Guo, Yajuan
2015-01-01
In a vehicular ad hoc network (VANET), the periodic exchange of single-hop status information broadcasts (beacon frames) produces channel loading, which causes channel congestion and induces information conflict problems. To guarantee fairness in beacon transmissions from each node and maximum network connectivity, adjustment of the beacon transmission power is an effective method for reducing and preventing channel congestion. In this study, the primary factors that influence wireless channel loading are selected to construct the KF-BCLF, which is a channel load forecasting algorithm based on a recursive Kalman filter and employs multiple regression equation. By pre-adjusting the transmission power based on the forecasted channel load, the channel load was kept within a predefined range; therefore, channel congestion was prevented. Based on this method, the CLF-BTPC, which is a transmission power control algorithm, is proposed. To verify KF-BCLF algorithm, a traffic survey method that involved the collection of floating car data along a major traffic road in Changchun City is employed. By comparing this forecast with the measured channel loads, the proposed KF-BCLF algorithm was proven to be effective. In addition, the CLF-BTPC algorithm is verified by simulating a section of eight-lane highway and a signal-controlled urban intersection. The results of the two verification process indicate that this distributed CLF-BTPC algorithm can effectively control channel load, prevent channel congestion, and enhance the stability and robustness of wireless beacon transmission in a vehicular network. PMID:26571042
Model Predictive Control Algorithms for Pen and Pump Insulin Administration
DEFF Research Database (Denmark)
Boiroux, Dimitri
ARMAX model in which we estimate the parameters of the stochastic part using a Recursive Least Square (RLS) method. We test the controller in a virtual clinic of 100 patients. This virtual clinic is based on the Hovorka model. We consider the case where only half of the bolus is administrated...... at mealtime, and the case where the insulin sensitivity increases during the night. This thesis consists of a summary report, glucose and insulin proles of the clinical studies and research papers submitted, peer-reviewed and/or published in the period September 2009 - September 2012....
Control of Hidden Mode Hybrid Systems: Algorithm termination
Verma, Rajeev; Del Vecchio, Domitilla
2011-01-01
We consider the problem of safety control in Hidden Mode Hybrid Systems (HMHS) that arises in the development of a semi-autonomous cooperative active safety system for collision avoidance at an intersection. We utilize the approach of constructing a new hybrid automaton whose discrete state is an estimate of the HMHS mode. A dynamic feedback map can then be designed that guarantees safety on the basis of the current mode estimate and the concept of the capture set. In this work, we relax the ...
Routing Algorithm for DTN Based on Congestion Control
Directory of Open Access Journals (Sweden)
Song Ningning
2013-10-01
Full Text Available Different from Internet networks, DTN has its own unique characteristics, like intermittent connectivity, low data transfer rate, high latency and limited storage and node resources. Routing technology is always the key to DTN research. In this paper, a routing protocol that is PNCMOP was proposed. It makes some improvement of Epidemic routing protocol, and also to decrease the end-to-end average delay and improve delivery ratio, especially with congestion control. Simulation results show that PNCMOP achieved a good performance.
AN ALGORITHM FOR STEERING CONTROL WITH SIMULATION RESULTS
Apeksha V. Sakhare,; Prof. Dr. V. M. Thakare; Prof. R. V. Dharaskar
2010-01-01
The idea behind the paper was channelization of human thoughts to automated realization. It is decided to implement the theme of automatic maneuvering of vehicles and the unanimous choice of sensor was touch screen. It was started with the thought of being able to replace the steering of a car completely by a touch screen. It is drawn on the experience of driving to reach at the choice of touch screen as a drive interface. Another innovation was the touch screen controller being wireless. The...
Machine vision algorithms applied to dynamic traffic light control
Directory of Open Access Journals (Sweden)
Fabio Andrés Espinosa Valcárcel
2013-01-01
número de autos presentes en imágenes capturadas por un conjunto de cámaras estratégicamente ubicadas en cada intersección. Usando esta información, el sistema selecciona la secuencia de acciones que optimicen el flujo vehicular dentro de la zona de control, en un escenario simulado. Los resultados obtenidos muestran que el sistema disminuye en un 20% los tiempos de retraso para cada vehículo y que además es capaz de adaptarse rápida y eficientemente a los cambios de flujo.
Cohesive Motion Control Algorithm for Formation of Multiple Autonomous Agents
Directory of Open Access Journals (Sweden)
Debabrata Atta
2010-01-01
Full Text Available This paper presents a motion control strategy for a rigid and constraint consistent formation that can be modeled by a directed graph whose each vertex represents individual agent kinematics and each of directed edges represents distance constraints maintained by an agent, called follower, to its neighbouring agent. A rigid and constraint consistent graph is called persistent graph. A persistent graph is minimally persistent if it is persistent, and no edge can be removed without losing its persistence. An acyclic (free of cycles in its sensing pattern minimally persistent graph of Leader-Follower structure has been considered here which can be constructed from an initial Leader-Follower seed (initial graph with two vertices, one is Leader and another one is First Follower and one edge in between them is directed towards Leader by Henneberg sequence (a procedure of growing a graph containing only vertex additions. A set of nonlinear optimization-based decentralized control laws for mobile autonomous point agents in two dimensional plane have been proposed. An infinitesimal deviation in formation shape created continuous motion of Leader is compensated by corresponding continuous motion of other agents fulfilling the shortest path criteria.
Admissibility of logical inference rules
Rybakov, VV
1997-01-01
The aim of this book is to present the fundamental theoretical results concerning inference rules in deductive formal systems. Primary attention is focused on: admissible or permissible inference rules the derivability of the admissible inference rules the structural completeness of logics the bases for admissible and valid inference rules. There is particular emphasis on propositional non-standard logics (primary, superintuitionistic and modal logics) but general logical consequence relations and classical first-order theories are also considered. The book is basically self-contained and
Yung-Chang Luo; Zhi-Sheng Ke; Ying-Piao Kuo
2014-01-01
A sensorless rotor-field oriented control induction motor drive with particle swarm optimization algorithm speed controller design strategy is presented. First, the rotor-field oriented control scheme of induction motor is established. Then, the current-and-voltage serial-model rotor-flux estimator is developed to identify synchronous speed for coordinate transformation. Third, the rotor-shaft speed on-line estimation is established applying the model reference adaptive system method based on...
An Energy-Efficient, Application-Oriented Control Algorithm for MAC Protocols in WSN
Li, Deliang; Peng, Fei; Qian, Depei
Energy efficiency has been a main concern in wireless sensor networks where Medium Access Control (MAC) protocol plays an important role. However, current MAC protocols designed for energy saving have seldom considered multiple applications coexisting in WSN with variation of traffic load dynamics and different QoS requirements. In this paper, we propose an adaptive control algorithm at MAC layer to promote energy efficiency. We focus on the tradeoff relation between collisions and control overhead as a reflection of traffic load and propose to balance the tradeoff under the constraints of QoS options. We integrate the algorithm into S-MAC and verify it through NS-2 platform. The results demonstrate the algorithm achieves observable improvement in energy performance while meeting QoS requirement for different coexisting applications in comparison with S-MAC.
Control and monitoring of On-line Trigger Algorithms using gaucho
Van Herwijnen, Eric
2005-01-01
In the LHCb experiment, the trigger decisions are computed by Gaudi (the LHCb software framework) algorithms running on an event filter farm of around 2000 PCs. The control and monitoring of these algorithms has to be integrated in the overall experiment control system (ECS). To enable and facilitate this integration Gaucho, the GAUdi Component Helping Online, was developed. Gaucho consists of three parts: a C++ package integrated with Gaudi, the communications package DIM, and a set of PVSS panels and libraries. PVSS is a commercial SCADA system chosen as toolkit and framework for the LHCb controls system. The C++ package implements monitor service interface (IMonitorSvc) following the Gaudi specifications, with methods to declare variables and histograms for monitoring. Algorithms writers use them to indicate which quantities should be monitored. Since the interface resides in the GaudiKernel the code does not need changing if the monitoring services are not present. The Gaudi main job implements a state ma...
一种自适应PID控制算法%AN ADAPTIVE PID CONTROL ALGORITHM
Institute of Scientific and Technical Information of China (English)
赵建华; 沈永良
2001-01-01
In this paper, by combining PID control algorithm with adaptive technology of modern control theory, we obtain an adaptive PID control algorithm and make computer simulation for various time varying parametric models. Results of the simulation prove effectiveness of the algorithm.%将现代控制理论的自适应技术与经典的PID控制算法相结合，推导出一种自适应PID控制算法，并在计算机上对不同对象及时变参数进行了数字仿真.结果表明这种自适应PID控制算法的有效性.
Algorithm of Attitude Control and Its Simulation of Free-Flying Space Robot
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Reaction wheel or reaction thruster is employed to maintain the attitude of the base of space robot fixed in attitude control of free-flying space robot.However, in this method, a large amount of fuel will be consumed, and it will shorten the on-orbit life span of space robot, it also vibrate the system and make the system unsteady.The restricted minimum disturbance map (RMDM) based algorithm of attitude control is presented to keep the attitude of the base fixed during the movement of the manipulator.In this method it is realized by planning motion trajectory of the end-effector of manipulator without using reaction wheel or reaction thruster.In order to verify the feasibility and effectiveness of the algorithm attitude control presented in this paper, computer simulation experiments have been made and the experimental results demonstrate that this algorithm is feasible.
On-line critical control rod pattern prediction algorithm for BWR plant startup
International Nuclear Information System (INIS)
This paper describes an on-line algorithm for predicting the critical control rod pattern, which has been developed to reduce the mental strain on operators while withdrawing control rods in the BWR plant startup operation. The proposed algorithm estimates a target eigenvalue (eigenvalue bias) for a three-dimensional neutron kinetics model with a neutron source incorporating actual neutron detector readings. The critical control rod pattern is then predicted based on the estimated eigenvalue bias. The algorithm has been verified using data obtained from an actual startup operation on a BWR model-5 plant, and the estimated eigenvalue bias agreed well with the effective multiplication factor at the criticality actually determined from the operator's judgement. (author)
Sum-of-squares-based fuzzy controller design using quantum-inspired evolutionary algorithm
Yu, Gwo-Ruey; Huang, Yu-Chia; Cheng, Chih-Yung
2016-07-01
In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi-Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used.
Nonlinear Model Algorithmic Control of a pH Neutralization Process
Institute of Scientific and Technical Information of China (English)
ZOU Zhiyun; YU Meng; WANG Zhizhen; LIU Xinghong; GUO Yuqing; ZHANG Fengbo; GUO Ning
2013-01-01
Control of pH neutralization processes is challenging in the chemical process industry because of their inherent strong nonlinearity.In this paper,the model algorithmic control (MAC) strategy is extended to nonlinear processes using Hammerstein model that consists of a static nonlinear polynomial function followed in series by a linear impulse response dynamic element.A new nonlinear Hammerstein MAC algorithm (named NLH-MAC) is presented in detail.The simulation control results of a pH neutralization process show that NLH-MAC gives better control performance than linear MAC and the commonly used industrial nonlinear propotional plus integral plus derivative (PID) controller.Further simulation experiment demonstrates that NLH-MAC not only gives good control response,but also possesses good stability and robustness even with large modeling errors.
DEFF Research Database (Denmark)
Sossan, Fabrizio; Bindner, Henrik W.
2012-01-01
, DSRs, are electric loads whose power consumption can be shifted without having a big impact on the primary services they are supplying and they are suitable for being controlled according the needs of regulating power in the electric power system. In this paper the performances and the aggregate...... responses provided by three algorithms for controlling electric space heating through a broadcasted price signal are compared. The algorithms have been tested in a software platform with a population of buildings using a hardware-in-the-loop approach that allows to feedback into the simulation the thermal...
DEFF Research Database (Denmark)
Sossan, Fabrizio; Bindner, Henrik W.
2012-01-01
responses provided by three algorithms for controlling electric space heating through a broadcasted price signal are compared. The algorithms have been tested in a software platform with a population of buildings using a hardware-in-the-loop approach that allows to feedback into the simulation the thermal...... response of a real office building; the experimental results of using a model predictive controller for heating a real building in a variable price context are also presented. This study is part of the Flexpower project whose aim is investigating the possibility of creating an electric market for...
Comparison of Reconstruction and Control algorithms on the ESO end-to-end simulator OCTOPUS
Montilla, I.; Béchet, C.; Lelouarn, M.; Correia, C.; Tallon, M.; Reyes, M.; Thiébaut, É.
Extremely Large Telescopes are very challenging concerning their Adaptive Optics requirements. Their diameters, the specifications demanded by the science for which they are being designed for, and the planned use of Extreme Adaptive Optics systems, imply a huge increment in the number of degrees of freedom in the deformable mirrors. It is necessary to study new reconstruction algorithms to implement the real time control in Adaptive Optics at the required speed. We have studied the performance, applied to the case of the European ELT, of three different algorithms: the matrix-vector multiplication (MVM) algorithm, considered as a reference; the Fractal Iterative Method (FrIM); and the Fourier Transform Reconstructor (FTR). The algorithms have been tested on ESO's OCTOPUS software, which simulates the atmosphere, the deformable mirror, the sensor and the closed-loop control. The MVM is the default reconstruction and control method implemented in OCTOPUS, but it scales in O(N2) operations per loop so it is not considered as a fast algorithm for wave-front reconstruction and control on an Extremely Large Telescope. The two other methods are the fast algorithms studied in the E-ELT Design Study. The performance, as well as their response in the presence of noise and with various atmospheric conditions, has been compared using a Single Conjugate Adaptive Optics configuration for a 42 m diameter ELT, with a total amount of 5402 actuators. Those comparisons made on a common simulator allow to enhance the pros and cons of the various methods, and give us a better understanding of the type of reconstruction algorithm that an ELT demands.
A MATLAB and.NET based Windows Application for controller design using Genetic algorithm
Batık, Zeynep; KAÇAR, Sezgin; ÇAVUŞOĞLU, Ünal; Akif AKGÜL; Sevin, Abdullah
2014-01-01
In this study, it is purposed that a windows application based on Genetic Algorithms (GA) is developed by using MATLAB and.NET platforms together. Controller design for automatic control systems has been choosen as the implementation field. For realizing the application, the GA and Builder NE tools of MATLAB programme have been utilized and the interface has been designed by Visual Studio. As the result, a software for determining the coefficients of P, PI and PID controllers by GA optimizati...
Xing Wu; Peihuang Lou; Dunbing Tang
2011-01-01
This paper presents a multi-objective genetic algorithm (MOGA) with Pareto optimality and elitist tactics for the control system design of automated guided vehicle (AGV). The MOGA is used to identify AGV driving system model and optimize its servo control system sequentially. In system identification, the model identified by least square method is adopted as an evolution tutor who selects the individuals having balanced performances in all objectives as elitists. In controller optimization, t...
Algorithm and data support of traffic congestion forecasting in the controlled transport
Dmitriev, S. V.
2015-06-01
The topicality of problem of the traffic congestion forecasting in the logistic systems of product movement highways is considered. The concepts: the controlled territory, the highway occupancy by vehicles, the parking and the controlled territory are introduced. Technical realizabilityof organizing the necessary flow of information on the state of the transport system for its regulation has been marked. Sequence of practical implementation of the solution is given. An algorithm for predicting traffic congestion in the controlled transport system is suggested.
On-line multiobjective automatic control system generation by evolutionary algorithms
Stewart, Paul; Stone, D. A.; Fleming, P.A.
2006-01-01
Evolutionary algorithms are applied to the on- line generation of servo-motor control systems. In this paper, the evolving population of controllers is evaluated at run-time via hardware in the loop, rather than on a simulated model. Disturbances are also introduced at run-time in order to pro- duce robust performance. Multiobjective optimisation of both PI and Fuzzy Logic controllers is considered. Finally an on-line implementation of Genetic Programming is presented based around the Simulin...
Dynamic Routing Algorithm Based on the Channel Quality Control for Farmland Sensor Networks
Directory of Open Access Journals (Sweden)
Dongfeng Xu
2014-04-01
Full Text Available This article reports a Dynamic Routing Algorithm for Farmland Sensor Networks (DRA-FSN based on channel quality control to improve energy efficiency, which combines the distance and communication characteristics of farmland wireless sensor network. The functional architecture of the DRA-FSN algorithm, routing establish the mechanisms, the communication transmission mechanism, the global routing beacon return mechanism, abnormal node handling mechanism and sensor networks timing control mechanisms were designed in detail in this article. This article also evaluates and simulated the performance of DRA-FSN algorithm in different conditions from energy efficiency, packet energy consumption and packet distribution balance by comparing DRA-FSN algorithm with DSDV, EAP algorithm. Simulations showed that the DRA-FSN was more energy efficient than EAP and DSDV, the DRA-FSN algorithm overcame the shortcoming that capacity and bandwidth of the routing table correspondingly increase as more and more nodes joining the network. It has better performance in scalability and network loading balance
Algorithm Design and Application of Laminar Cooling Feedback Control in Hot Strip Mill
Institute of Scientific and Technical Information of China (English)
LIU En-yang; ZHANG Dian-hua; SUN Jie; PENG Liang-gui; GAO Bai-hong; SU Li-tao
2012-01-01
Feedback control is one of the most important ways to improve coiling temperature control precision during laminar cooling process.Laminar cooling equipments of a hot strip mill and structure of the control system were introduced.Feedback control algorithm based on PI controller and that based on Smith predictor were designed and tested in a hot strip mill respectively.Practical application shows that the feedback control system based on PI controller plays a limited role in improving coiling temperature control precision.The feedback control system based on Smith predictor runs stable and reliable.When the measured coiling temperature deviates from the target value,it can be adjusted to the required range quickly and steadily by Smith predictor feedback control,which improves the coiling temperature control precision greatly,and qualities of hot rolled strips are improved significantly
Institute of Scientific and Technical Information of China (English)
TIAN Ye; SHENG Min; LI Jiandong
2007-01-01
This Paper presents a novel distributed media access control(MAC)address assignment algorithm,namely virtual grid spatial reusing(VGSR),for wireless sensor networks,which reduces the size of the MAC address efficiently on the basis of both the spatial reuse of MAC address and the mapping of geographical position.By adjusting the communication range of sensor nodes,VGSR algorithm can minimize the size of MAC address and meanwhile guarantee the connectivity of the sensor network.Theoretical analysis and experimental results show that VGSR algorithm is not only of low energy cost,but also scales well with the network ize,with its performance superior to that of other existing algorithms.
Road Traffic Control Based on Genetic Algorithm for Reducing Traffic Congestion
Shigehiro, Yuji; Miyakawa, Takuya; Masuda, Tatsuya
In this paper, we propose a road traffic control method for reducing traffic congestion with genetic algorithm. In the not too distant future, the system which controls the routes of all vehicles in a certain area must be realized. The system should optimize the routes of all vehicles, however the solution space of this problem is enormous. Therefore we apply the genetic algorithm to this problem, by encoding the route of all vehicles to a fixed length chromosome. To improve the search performance, a new genetic operator called “path shortening” is also designed. The effectiveness of the proposed method is shown by the experiment.
Novel Control Algorithm for the Foot Placement of a Walking Bipedal Robot
Directory of Open Access Journals (Sweden)
Wanli Liu
2013-04-01
Full Text Available A novel control algorithm for the foot placement of walking bipedal robots is proposed which can output the optimal step time and step location to obtain a desired walking gait from every feasible robot state. The step time and step location are determined by approximating the robot dynamics with the 3D linear inverted pendulum model and analytically solving the constraint equations. Intensive simulation studies are conducted to check the validity of the theoretical results. The results of this study show that the proposed control algorithm can get the system to a desired gait cycle from every feasible state within a finite number of steps.
ABC Algorithm Based Interval Type-2 Fuzzy Logic Controller for an Inverted Pendulum
Anita Khosla; Leena G.; M.K. Soni
2014-01-01
In this paper, a hybrid control technique is proposed for managing the variation of angle and velocity of the inverted pendulum. The proposed hybrid technique is the combination of ABC algorithm and interval type-2 Fuzzy Logic System (IT2FLS). The objective of the proposed hybrid control technique is to achieve the stability position of the pendulum. Here, the ABC algorithm is used to optimize the change of angle and change of velocity of the pendulum. With the optimized value, the optimal me...
Self-Correcting HVAC Controls: Algorithms for Sensors and Dampers in Air-Handling Units
Energy Technology Data Exchange (ETDEWEB)
Fernandez, Nicholas; Brambley, Michael R.; Katipamula, Srinivas
2009-12-31
This report documents the self-correction algorithms developed in the Self-Correcting Heating, Ventilating and Air-Conditioning (HVAC) Controls project funded jointly by the Bonneville Power Administration and the Building Technologies Program of the U.S. Department of Energy. The algorithms address faults for temperature sensors, humidity sensors, and dampers in air-handling units and correction of persistent manual overrides of automated control systems. All faults considered create energy waste when left uncorrected as is frequently the case in actual systems.
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Standardi, Laura; Edlund, Kristian;
2014-01-01
This paper presents a warm-started Dantzig–Wolfe decomposition algorithm tailored to economic model predictive control of dynamically decoupled subsystems. We formulate the constrained optimal control problem solved at each sampling instant as a linear program with state space constraints, input...... limits, input rate limits, and soft output limits. The objective function of the linear program is related directly to the cost of operating the subsystems, and the cost of violating the soft output constraints. Simulations for large-scale economic power dispatch problems show that the proposed algorithm...
International Nuclear Information System (INIS)
The emphasis of this work is the development and implementation of an automatic control philosophy which uses the classical operational philosophies as a foundation. Three control algorithms were derived based on various simplifying assumptions. Two of the algorithms were tested in computer simulations. After realizing the insensitivity of the system to the simplifications, the most reduced form of the algorithms was implemented on the computer control system at the University of Utah (UNEL). Since the operational philosophies have a higher priority than automatic control, they determine when automatic control may be utilized. Unlike the operational philosophies, automatic control is not concerned with component failures. The object of this philosophy is the movement of absorber rods to produce a requested power. When the current power level is compared to the requested power level, an error may be detected which will require the movement of a control rod to correct the error. The automatic control philosophy adds another dimension to the classical operational philosophies. Using this philosophy, normal operator interactions with the computer would be limited only to run parameters such as power, period, and run time. This eliminates subjective judgements, objective judgements under pressure, and distractions to the operator and insures the reactor will be operated in a safe and controlled manner as well as providing reproducible operations
Seltzer, S. M.
1976-01-01
The problem discussed is to design a digital controller for a typical satellite. The controlled plant is considered to be a rigid body acting in a plane. The controller is assumed to be a digital computer which, when combined with the proposed control algorithm, can be represented as a sampled-data system. The objective is to present a design strategy and technique for selecting numerical values for the control gains (assuming position, integral, and derivative feedback) and the sample rate. The technique is based on the parameter plane method and requires that the system be amenable to z-transform analysis.
Directory of Open Access Journals (Sweden)
V.Sinthu Janita Prakash
2012-10-01
Full Text Available Wireless links are characterized by high error rates and intermittent connectivity. TCP congestion control has been developed on the assumption that network congestion is the only cause for packet loss. Upon detecting a packet loss, TCP drops its transmit window resulting in an unnecessary reduction of end-to-end throughput which results in suboptimal performance.The sender has to be made aware by some feedback mechanism that some of the losses reported are not due to congestion. The Active Queue Management algorithms (AQM are used to reduce congestion, and in this paper, we have analysed four AQM algorithms, Random Early Deduction (RED, Wireless Explicit Congestion Notification (WECN, Queue Management Backward Congestion Control Algorithm (QMBCCA and its enhanced version Extended Queue Management Backward Congestion Control Algorithm (EQMBCCA. WECN, QMBCCA & EQMBCCA algorithms make use of feedback mechanisms. WECN gives feedback using the CE bit. QMBCCA and EQMBCCA make use of ISQ notifications and also the CE bit whenever the average queue size crosses minimum threshold value. EQMBCCA reduces the reverse ISQ traffic by introducing a configurable intermediate threshold value IntThres. The comparison is made in terms of Delay, HTTP packet loss percentage and fairness for FTP flows in a wireless environment. It is found that the performance of EQMBCCA is almost equal to that of QMBCCA and better than RED and WECN.
Directory of Open Access Journals (Sweden)
Eskandar Gholipour
2013-02-01
Full Text Available Power-system dynamic stability improvement by a static synchronous series compensator (SSSC based damping controller is thoroughly investigated in this paper. In order to design the optimal parameters of the controller, Imperialist Competitive Algorithm (ICA is employed to search for the optimal controller parameters. Both local and remote signals are considered in the present study and the performance of the proposed controllers with variations in the signal transmission delays has been investigated. The performances of the proposed controllers are evaluated under different disturbances for both single-machine-infinite-bus and multi-machine power systems. Finally, the results of ICA method are compared with the results of Genetic Algorithm (GA.
International Nuclear Information System (INIS)
When elaborating software for the standard algorithms of the information support of the efficient control (keeping) of water chemistry operation (WCO) at the NPP power units one introduces an approach when the systems of chemical control are realized as the systems of quality control of in-loop physical and chemical processes gathering force in the course of time. Elaboration of algorithms to proceed data of the operational chemical control seeks for elaboration of the statistic procedures to detect anomalies of the processes at the early stages of their development more efficient in contrast to the standard procedures of control. The introduced procedure is used in the demonstration model of the system for diagnostics of some typical reasons of violation of the first circuit WCO of WWER-1000 power units
Bhole, Gaurav; Anjusha, V. S.; Mahesh, T. S.
2016-04-01
A robust control over quantum dynamics is of paramount importance for quantum technologies. Many of the existing control techniques are based on smooth Hamiltonian modulations involving repeated calculations of basic unitaries resulting in time complexities scaling rapidly with the length of the control sequence. Here we show that bang-bang controls need one-time calculation of basic unitaries and hence scale much more efficiently. By employing a global optimization routine such as the genetic algorithm, it is possible to synthesize not only highly intricate unitaries, but also certain nonunitary operations. We demonstrate the unitary control through the implementation of the optimal fixed-point quantum search algorithm in a three-qubit nuclear magnetic resonance (NMR) system. Moreover, by combining the bang-bang pulses with the crusher gradients, we also demonstrate nonunitary transformations of thermal equilibrium states into effective pure states in three- as well as five-qubit NMR systems.
CARDIOTOCOGRAPH: ADMISSION TEST AND OUTCOME
Directory of Open Access Journals (Sweden)
Nesam Susana
2015-12-01
Full Text Available The main objective of intrapartum fetal monitoring is reduction or prevention of congenital neurological deficit and other intrapartum adverse events by screening for intrapartum hypoxia/acidosis. With an aim of evaluating role of admission test in predicting the adverse fetal outcome in high risk pregnancies in Government Chengalpattu Medical College, a cross-sectional study was designed including 50 high risk patients and 50 low risk patients. All the patients were subjected to a standard clinical evaluation using a proforma and subsequently subjected to admission test for 20 mins and their readings were grouped into 1. Reactive, 2. Suspicious, 3. Ominous. Intervention is planned based on the tracings of the admission test. The data from the admission test were compiled and subjected to statistical analysis. At the end of statistical analysis, it is found that electronic fetal monitoring has high sensitivity and low specificity. Antepartum risk factors are a poor predictors of fetal outcome. A normal tracing carries a predictive value of over 95% for APGAR score of 7 or greater and an abnormal tracing carries a predictive value of about 50% for APGAR score less than 7. In high risk cases admission test is more sensitive and in low risk cases the admission test is more specific. The negative predictive value for both groups were 85.2% and 97.7%
ENHANCED RABIN ALGORITHM BASED ERROR CONTROL MECHANISM FOR WIRELESS SENSOR NETWORKS
Directory of Open Access Journals (Sweden)
M.R.Ebenezar Jebarani
2012-12-01
Full Text Available In wireless sensor nodes, the data transmitted from the sensor nodes are prune to corruption by induced errors by noisy channels and other relevant parameters. Hence it is always vital to provide an effective and efficient error control methodology to minimize the bit error rate (BER.Due to the presence of scarce energy available in thesensor networks, it is important to use a high throughput, low end to end delay and energy aware error control scheme. In this paper, the performance analysis of three error control codes namely Enhanced Rabin Algorithm Based HARQ (ERABHARQ, Enhanced linear feedback shift register based mechanism (ELFSRM and Hadamard code are analyzed based on the performance metrics namely Throughput, BER, End to End Delay and energy utilization by varying the sensor nodes. To elaborate the error control schemes with different situational parameters are simulated using ns-2. The Enhanced Rabin Algorithm Based HARQ code is the improved methodology when compared to Automatic Repeat Request, because the retransmission of the packetsdo not takes place automatically rather than it takes place based on the success or failure of the Enhanced Rabin’s Algorithm. In this paper, three different error control codes are compared and it is concluded that Enhanced Rabin Algorithm Based HARQ performs better and it is well suited for wireless sensor networks
Genetic Algorithm Based Control System Design of a Self-Excited Induction Generator
Directory of Open Access Journals (Sweden)
A.-F. Attia
2006-01-01
Full Text Available This paper presents an application of the genetic algorithm (GA for optimizing controller gains of the Self-Excited Induction Generator (SEIG driven by the Wind Energy Conversion Scheme (WECS. The proposed genetic algorithm is introduced to adapt the integral gains of the conventional controllers of the active and reactive control loop of the system under study, where GA calculates the optimum value for the gains of the variables based on the best dynamic performance and a domain search of the integral gains. The proposed genetic algorithm is used to regulate the terminal voltage or reactive power control, by adjusting the self excitation, and to control the mechanical input power or active power control by adapting the blade angle of WECS, in order to adjust the stator frequency. The GA is used for optimizing these gains, for an active and reactive power loop, by solving the related optimization problem. The simulation results show a better dynamic performance using the GA than using the conventional PI controller for active and reactive control.
A Novel Sliding Mode Variable Structure Controller Based on a Genetic Algorithm
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
A novel control method has been proposed by using the genetic algorithm ( GA ) for nonlinear and complex plants. The proposed control strategy is based on a variable structure control, it overcomes the defects of other adaptive methods such as strong dependence to the system. A GA is used to learn to optimally select integral coefficient C. Simulation results verified the effectiveness of the controller. For position control of Direct Current (DC) motor in practice, this method has good performance and strong robustness, and both dynamic and steady performances were improved.
Application of Improved Neural Adaptive PSD Algorithm in Temperature Control of INS
Institute of Scientific and Technical Information of China (English)
缪玲娟; 郭振西; 崔燕
2004-01-01
A neural adaptive proportion sum differential (PSD) algorithm with errors prediction is researched. It is applied in inertial navigation system(INS) temperature control. The algorithm do not need the process's precise mathematical model and can adapt to the process pareters changing, and can deal with the process with nonlinearity. According to the Smith predictor, author developed a method that takes the predicted process error and error change as neural adaptive PSD algorithm's input. The method is effective to the system with long dead time. The results of compute simulation show that this system has characters of quickly reaction, low overshoot and good stability. It can meet the requirements of temperature control of INS.
A chaos search immune algorithm with its application to neuro-fuzzy controller design
Energy Technology Data Exchange (ETDEWEB)
Zuo, X.Q. [Department of Automation, Tsinghua University, Beijing 100084 (China)]. E-mail: zuoxq@tsinghua.edu.cn; Fan, Y.S. [Department of Automation, Tsinghua University, Beijing 100084 (China)
2006-10-15
In this paper, a chaos search immune algorithm (CSIA) is proposed by integrating the chaos optimization algorithm and the clonal selection algorithm. First, optimization variables are expressed by chaotic variables through solution space transformation. Then, taking advantages of the ergodic and stochastic properties of chaotic variables, a chaos search is performed in the neighbourhoods of high affinity antibodies to exploit local solution space, and the motion of the chaotic variables in their ergodic space is used to explore the whole solution space. Furthermore, a generalized radial basis function neuro-fuzzy controller (GRBFNFC) is constructed and designed automatically by the proposed CSIA. Application of the CSIA-designed GRBFNFC to real-time control of an inverted pendulum system is discussed. Experimental results demonstrate that the designed GRBFNFC has very satisfactory performance.
Temperature effects on hospital admissions for kidney morbidity in Taiwan
Energy Technology Data Exchange (ETDEWEB)
Lin, Yu-Kai [Department of Environmental Health, Harvard School of Public Health, 665 Huntington Avenue, Boston, MA 02115 (United States); Wang, Yu-Chun [Department of Bioenvironmental Engineering, College of Engineering, Chung Yuan Christian University, 200 Chung-Pei Road, Chung Li 320, Taiwan (China); Research Center for Environmental Risk Management, Chung Yuan Christian University, 200 Chung-Pei Road, Chung Li 320, Taiwan (China); Ho, Tsung-Jung [The Division of Chinese Medicine, China Medical University Beigang Hospital, Taiwan (China); School Of Chinese Medicine, College of Chinese Medicine, China Medical University, 91 Xueshi Road, Taichung City 404, Taiwan (China); Lu, Chensheng, E-mail: cslu@hsph.harvard.edu [Department of Environmental Health, Harvard School of Public Health, 665 Huntington Avenue, Boston, MA 02115 (United States)
2013-01-15
Objective: This study aimed to associate hospital admissions of kidney diseases with extreme temperature and prolonged heat/cold events in 7 regions of Taiwan. Methods: Age-specific (< 65 years, 65 + years and all ages) hospital admission records of nephritis, nephrotic syndrome, or nephrosis, in the form of electronic insurance reimbursement claims, were retrieved from Taiwan's National Health Insurance Research Database during the period of 2000–2008. The area–age-specific relative risk (RR) accounting for 8 days of lag for temperature on hospital admissions of kidney diseases were estimated using distributed lag non-linear models with the Poisson distribution controlling for extreme temperature events, levels of air pollutants (PM{sub 10}, O{sub 3}, and NO{sub 2}) and potential confounders. Results: We observed a V or J-shape association between daily average temperatures and the RR estimates for hospital admissions of kidney diseases in Taiwan. The lowest risk for hospital admissions of kidney diseases was found at around 25 °C, and risk increased as temperatures deviated from 25 °C. The pooled cumulative 8-day RR for all ages of population of the 7 study areas were 1.10 (95% confidence interval (CI): 1.01, 1.19) at 18 °C and 1.45 (95% CI: 1.27, 1.64) at 30 °C. High temperature has more profound influence on hospital admission of kidney diseases than low temperature. Temperature risks for hospital admissions were similar between younger (< 65 years) and elderly (65 + years) population. This study observed no significant effects of prolonged heat extremes on hospital admissions of kidney diseases. Conclusions: The heat effect for kidney morbidities leading to hospital admission was more significant than that of the cold temperature. This study did not find the age-dependent relative risks for temperature associating with hospital admissions of kidney diseases. - Highlights: ► V or J-shaped association was observed between daily temperatures and
Admissible consensus for heterogeneous descriptor multi-agent systems
Yang, Xin-Rong; Liu, Guo-Ping
2016-09-01
This paper focuses on the admissible consensus problem for heterogeneous descriptor multi-agent systems. Based on algebra, graph and descriptor system theory, the necessary and sufficient conditions are proposed for heterogeneous descriptor multi-agent systems achieving admissible consensus. The provided conditions depend on not only the structure properties of each agent dynamics but also the topologies within the descriptor multi-agent systems. Moreover, an algorithm is given to design the novel consensus protocol. A numerical example demonstrates the effectiveness of the proposed design approach.
Robust Control Algorithm for a Two Cart System and an Inverted Pendulum
Wilson, Chris L.; Capo-Lugo, Pedro
2011-01-01
The Rectilinear Control System can be used to simulate a launch vehicle during liftoff. Several control schemes have been developed that can control different dynamic models of the rectilinear plant. A robust control algorithm was developed that can control a pendulum to maintain an inverted position. A fluid slosh tank will be attached to the pendulum in order to test robustness in the presence of unknown slosh characteristics. The rectilinear plant consists of a DC motor and three carts mounted in series. Each cart s weight can be adjusted with brass masses and the carts can be coupled with springs. The pendulum is mounted on the first cart and an adjustable air damper can be attached to the third cart if desired. Each cart and the pendulum have a quadrature encoder to determine position. Full state feedback was implemented in order to develop the control algorithm along with a state estimator to determine the velocity states of the system. A MATLAB program was used to convert the state space matrices from continuous time to discrete time. This program also used a desired phase margin and damping ratio to determine the feedback gain matrix that would be used in the LabVIEW program. This experiment will allow engineers to gain a better understanding of liquid propellant slosh dynamics, therefore enabling them to develop more robust control algorithms for launch vehicle systems
DEFF Research Database (Denmark)
Meng, Lexuan; Dragicevic, Tomislav; Guerrero, Josep M.;
2014-01-01
. Accordingly, this paper proposes a dynamic consensus algorithm based distributed optimization method aiming at improving the system efficiency while offering higher expandability and flexibility when compared to centralized control. Hardware-in-the-loop (HIL) results are shown to demonstrate the effectiveness...
Operational performance of the three bean salad control algorithm on the ACRR
Ball, Russell M.; Madaras, John J.; Trowbridge, F. Ray; Talley, Darren G.; Parma, Edward J.
1991-01-01
Experimental tests on the Annular Core Research Reactor have confirmed that the ``Three-Bean-Salad'' control algorithm based on the Pontryagin maximum principle can change the power of a nuclear reactor many decades with a very fast startup rate and minimal overshoot. The paper describes the results of simulations and operations up to 25 MW and 87 decades per minute.
Operational performance of the three bean salad control algorithm on the ACRR
International Nuclear Information System (INIS)
Experimental tests on the Annular Core Research Reactor have confirmed that the ''Three-Bean-Salad'' control algorithm based on the Pontryagin maximum principle can change the power of a nuclear reactor many decades with a very fast startup rate and minimal overshoot. The paper describes the results of simulations and operations up to 25 MW and 87 decades per minute
44 CFR 68.9 - Admissible evidence.
2010-10-01
... 44 Emergency Management and Assistance 1 2010-10-01 2010-10-01 false Admissible evidence. 68.9 Section 68.9 Emergency Management and Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY, DEPARTMENT OF... admissible. (b) Documentary and oral evidence shall be admissible. (c) Admissibility of non-expert...
Robot Control near Singularity and Joint Limit Using a Continuous Task Transition Algorithm
Directory of Open Access Journals (Sweden)
Hyejin Han
2013-10-01
Full Text Available When robots are controlled in the task space, singularities and joint limits are among the most critical and difficult issues that can arise. In this paper, we propose a new approach for the robots to operate in the regions near singularities and joint limits using the operational space control framework. Specifically, a continuous task transition algorithm called the intermediate desired value approach is applied to the hierarchically structured controller in the operational space control framework. In this approach, new tasks are defined for dealing with singularities and joint limits, and the tasks are activated or deactivated using the continuous task transition algorithm to guarantee the continuous execution of the tasks during the execution of the main task. The proposed approach is implemented on a 6-DOF manipulator called Roman-MD. The experimental results demonstrate its performance near the singular regions and joint limits.
Polynomial-Time Algorithm for Controllability Test of a Class of Boolean Biological Networks
Directory of Open Access Journals (Sweden)
Koichi Kobayashi
2010-01-01
Full Text Available In recent years, Boolean-network-model-based approaches to dynamical analysis of complex biological networks such as gene regulatory networks have been extensively studied. One of the fundamental problems in control theory of such networks is the problem of determining whether a given substance quantity can be arbitrarily controlled by operating the other substance quantities, which we call the controllability problem. This paper proposes a polynomial-time algorithm for solving this problem. Although the algorithm is based on a sufficient condition for controllability, it is easily computable for a wider class of large-scale biological networks compared with the existing approaches. A key to this success in our approach is to give up computing Boolean operations in a rigorous way and to exploit an adjacency matrix of a directed graph induced by a Boolean network. By applying the proposed approach to a neurotransmitter signaling pathway, it is shown that it is effective.
Searching for full power control rod patterns in a boiling water reactor using genetic algorithms
Energy Technology Data Exchange (ETDEWEB)
Montes, Jose Luis [Departamento Sistemas Nucleares, ININ, Carr. Mexico-Toluca Km. 36.5, Ocoyoacac, Edo. de Mexico (Mexico)]. E-mail: jlmt@nuclear.inin.mx; Ortiz, Juan Jose [Departamento Sistemas Nucleares, ININ, Carr. Mexico-Toluca Km. 36.5, Ocoyoacac, Edo. de Mexico (Mexico)]. E-mail: jjortiz@nuclear.inin.mx; Requena, Ignacio [Departamento Ciencias Computacion e I.A. ETSII, Informatica, Universidad de Granada, C. Daniel Saucedo Aranda s/n. 18071 Granada (Spain)]. E-mail: requena@decsai.ugr.es; Perusquia, Raul [Departamento Sistemas Nucleares, ININ, Carr. Mexico-Toluca Km. 36.5, Ocoyoacac, Edo. de Mexico (Mexico)]. E-mail: rpc@nuclear.inin.mx
2004-11-01
One of the most important questions related to both safety and economic aspects in a nuclear power reactor operation, is without any doubt its reactivity control. During normal operation of a boiling water reactor, the reactivity control of its core is strongly determined by control rods patterns efficiency. In this paper, GACRP system is proposed based on the concepts of genetic algorithms for full power control rod patterns search. This system was carried out using LVNPP transition cycle characteristics, being applied too to an equilibrium cycle. Several operation scenarios, including core water flow variation throughout the cycle and different target axial power distributions, are considered. Genetic algorithm fitness function includes reactor security parameters, such as MLHGR, MCPR, reactor k{sub eff} and axial power density.
DC Voltage Droop Control Implementation in the AC/DC Power Flow Algorithm: Combinational Approach
DEFF Research Database (Denmark)
Akhter, F.; Macpherson, D.E.; Harrison, G.P.;
2015-01-01
In this paper, a combinational AC/DC power flow approach is proposed for the solution of the combined AC/DC network. The unified power flow approach is extended to include DC voltage droop control. In the VSC based MTDC grids, DC droop control is regarded as more advantageous in terms of...... operational flexibility, as more than one VSC station controls the DC link voltage of the MTDC system. This model enables the study of the effects of DC droop control on the power flows of the combined AC/DC system for steady state studies after VSC station outages or transient conditions without needing to...... use its complete dynamic model. Further, the proposed approach can be extended to include multiple AC and DC grids for combined AC/DC power flow analysis. The algorithm is implemented by modifying the MATPOWER based MATACDC program and the results shows that the algorithm works efficiently....
ABC Algorithm Based Interval Type-2 Fuzzy Logic Controller for an Inverted Pendulum
Directory of Open Access Journals (Sweden)
Anita Khosla
2014-05-01
Full Text Available In this paper, a hybrid control technique is proposed for managing the variation of angle and velocity of the inverted pendulum. The proposed hybrid technique is the combination of ABC algorithm and interval type-2 Fuzzy Logic System (IT2FLS. The objective of the proposed hybrid control technique is to achieve the stability position of the pendulum. Here, the ABC algorithm is used to optimize the change of angle and change of velocity of the pendulum. With the optimized value, the optimal membership functions and the interference system are developed using IT2FLS. Using the ABC based IT2FLS, the position of the inverted pendulum is maintained towards the reference position. The proposed hybrid control technique is implemented in MATLAB/Simulink working platform and the control performances are evaluated.
Institute of Scientific and Technical Information of China (English)
叶涛锋; 达庆利
2011-01-01
研究面向2个任务类的损失系统中的动态准入控制策略.任务有不同的服务时间要求和不同的报酬,对于到达的任务,服务提供者无法直接判断每个任务属于哪一类,但能观测到每个任务所带的信号.证明了值函数的次模性和凹性,且存在一个唯一的用于对任务进行归类的信号阈值,建立了一个4层的准入控制策略.当任务信号的信息量较少时,在一定的条件下所建立的准入策略仍然有效.最后,将所建立的4层准入控制策略应用于不完美信息条件下的库存配给问题,应用结果表明该控制策略是可行而有效的.%This paper considers the dynamic admission control policy in a two-class loss system.Each class of jobs requires different service rates and offer different rewards.The service provider cannot directly determine the identities but can observe the signals of the jobs in a batch.The submodularity and concavity properties of the value function are proved. There is a signal threshold such that the jobs with signals larger than or equal to it are classified as class 1,and those with signals smaller than it are classified as class 2.Consequently,a four-layer admission control policy is established.When the signals are less informative,the main results are also available under some certain conditions.Finally,the resulting admission control policy is applied to an inventory rationing problem with imperfect information,and the feasibility and effectiveness of such a polity is identified.
A Novel Genetic Algorithm and Its Application in Variable Structure Control of Robot
Institute of Scientific and Technical Information of China (English)
王建平; 许春山; 孙兴进; 赵锡芳
2005-01-01
A novel genetic algorithm (NGA) is proposed, which possesses micro-regulation and renascence operation. The optimized variable searching interval is regulated gradually according to the sub-group of excellent individuals. The NGA is used to optimize the parameters of the variable structure control (VSC), which satisfies the new reaching law and sliding mode. It is used in robot control systems. Simulation results are given.
An Expedite Approximate Algorithm for Calculating the Controls in the Longitudinal Maneuver
Directory of Open Access Journals (Sweden)
Laurentiu MORARU
2015-09-01
Full Text Available This paper discusses an expedite approximate algorithm for obtaining the controls in the longitudinal maneuver of the aerospace vehicles. The equations of motion are written in terms of the flight path (the trajectory that is desired is also given in terms of flight path, that is the local radius of curvature is given as a function of flight path and the controls required for following a desired trajectory obtained accordingly. A finite terms integration procedure is subsequently presented.
Practical Velocity Tracking Control of a Parallel Robot Based on Fuzzy Adaptive Algorithm
Xiang Wu; Quan Liu; Qingsong Ai; Zude Zhou; Wei Meng
2013-01-01
Due to the advantages of its compact structure and high operation accuracy, the six degrees of freedom (6-DOF) parallel platform has been widely used as a carrier of medical rehabilitation devices. Fuzzy adaptive algorithm does not depend on the mathematical model of controlled object, which possesses good nonlinear characteristics. Those entire features make it an effective method to control such complex and coupling platforms. To facilitate the application of robotics in lower limb rehabili...
An Analysis of the Control-Algorithm Re-solving Issue in Inventory and Revenue Management
Nicola Secomandi
2008-01-01
While inventory- and revenue-management problems can be represented as Markov decision process (MDP) models, in some cases the well-known dynamic-programming curse of dimensionality makes it computationally prohibitive to solve them exactly. An alternative solution, called here the control-algorithm approach, is to use a math program (MP) to approximately represent the MDP and use its optimal solution to heuristically instantiate the parameters of the decision rules of a given set of control ...
Optimization of PID controller based on The Bees Algorithm for one leg of a quadruped robot
Bakırcıoğlu Veli; Arif Şen M.; Kalyoncu Mete
2016-01-01
In this paper, we apply The Bees Algorithm to find optimal PID controller gains to control angular positions of robot leg joints with the minimum position error. In order to present more realistic simulation, system modelled in MATLAB/Simulink environment which is close to experimental set up. Solid model of system, which has two degrees of freedom, drawn by using a CAD software. Required physical specifications of robot leg for MATLAB/Simulink modelling is obtained from this CAD model. Contr...
Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm
Feifei Dong; Dichen Liu; Jun Wu; Bingcheng Cen; Haolei Wang; Chunli Song; Lina Ke
2014-01-01
Considering that common subsynchronous resonance controllers cannot adapt to the characteristics of the time-varying and nonlinear behavior of a power system, the cosine migration model, the improved migration operator, and the mutative scale of chaos and Cauchy mutation strategy are introduced into an improved biogeography-based optimization (IBBO) algorithm in order to design an optimal subsynchronous damping controller based on the mechanism of suppressing SSR by static var compensator (SV...
An O(log N) Parallel Algorithm for Newton Step Computation in Model Predictive Control
Nielsen, Isak; Axehill, Daniel
2014-01-01
The use of Model Predictive Control in industry is steadily increasing as more complicated problems can be addressed. Due to that online optimization is usually performed, the main bottleneck with Model Predictive Control is the relatively high computational complexity. Hence, a lot of research has been performed to find efficient algorithms that solve the optimization problem. As parallelism is becoming more commonly used in hardware, the demand for efficient parallel solvers for Model Predi...
Rizzo, Renato; Andrea DEL PIZZO; Ivan SPINA
2012-01-01
This paper deals with Permanent Magnet Brushless Motors. In particular is proposed a new set of control algorithm expressions that is realized taking into account resistive parameters of the motor, differently from simplified models of this type of motors where these parameters are usually neglected. The control is set up and an analysis of the performance is reported in the paper, where the validation of the new expressions is done with reference to a motor prototype particularly compact bec...
Directory of Open Access Journals (Sweden)
Ankur Bhattacharjee
2012-09-01
Full Text Available This paper contains the design of a three stage solar battery charge controller and a comparative study of this charge control technique with three conventional solar battery charge control techniques such as 1. Constant Current (CC charging, 2. Two stage constant current constant voltage (CC-CV charging technique. The analysis and the comparative study of the aforesaid charging techniques are done in MATLAB/SIMULINK environment. Here the practical data used to simulate the charge control algorithms are based on a 12Volts 7Ah Sealed lead acid battery.
Research on Air Flow Measurement and Optimization of Control Algorithm in Air Disinfection System
Bing-jie, Li; Jia-hong, Zhao; Xu, Wang; Amuer, Mohamode; Zhi-liang, Wang
2013-01-01
As the air flow control system has the characteristics of delay and uncertainty, this research designed and achieved a practical air flow control system by using the hydrodynamic theory and the modern control theory. Firstly, the mathematical model of the air flow distribution of the system is analyzed from the hydrodynamics perspective. Then the model of the system is transformed into a lumped parameter state space expression by using the Galerkin method. Finally, the air flow is distributed more evenly through the estimation of the system state and optimal control. The simulation results show that this algorithm has good robustness and anti-interference ability
Genetic algorithm combined with immune mechanism and its application in skill fuzzy control
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Automation of skill fuzzy control system is an important research aspect of fuzzy control fields. It's significant for those control instances consisted in production and people's daily life. But, how to control a system not movement or behavior rules but only relied on movement parameters, that problem still had not be resolved. This paper proposes a new method used a genetic algorithm based on immune mechanism to learn the degree of membership, at same time, simplifying the corresponding movement equation; its efficiency will be indicated by an example.
Step-coordination Algorithm of Traffic Control Based on Multi-agent System
Institute of Scientific and Technical Information of China (English)
Hai-Tao Zhang; Fang Yu; Wen Li
2009-01-01
Aiming at the deficiency of conventional traffic control method, this paper proposes a new method based on multi-agent technology for traffic control. Different from many existing methods, this paper distinguishes traffic control on the basis of the agent technology from conventional traffic control method. The composition and structure of a multi-agent system (MAS) is first discussed. Then, the step-coordination strategies of intersection-agent, segment-agent, and area-agent are put forward. The advantages of the algorithm are demonstrated by a simulation study.
International Nuclear Information System (INIS)
This paper presents the application of an improved fuzzy controller to vibration suppression of a cantilever beam structure. A Genetic Algorithm (G A) optimizer, which emulates natural biological evolutionary theories, offers a technology that supports optimization of the parameters of fuzzy logic and other parameterized non-linear controllers. This paper shows how G As can effectively and efficiently optimize the performance of fuzzy net controllers. Some results are presented which show the ability of the improved fuzzy controller to highly improve the vibration cancellation performance of the flexible beam. (author). 25 refs. 3 tab., 10 figs
An optimal consensus tracking control algorithm for autonomous underwater vehicles with disturbances
Zhang, Jian Yuan Wen-Xia
2012-01-01
The optimal disturbance rejection control problem is considered for consensus tracking systems affected by external persistent disturbances and noise. Optimal estimated values of system states are obtained by recursive filtering for the multiple autonomous underwater vehicles modeled to multi-agent systems with Kalman filter. Then the feedforward-feedback optimal control law is deduced by solving the Riccati equations and matrix equations. The existence and uniqueness condition of feedforward-feedback optimal control law is proposed and the optimal control law algorithm is carried out. Lastly, simulations show the result is effectiveness with respect to external persistent disturbances and noise.
International Nuclear Information System (INIS)
Highlights: ► This paper presents MPPT based control for optimal wind energy capture using RBFN. ► MPSO is adopted to adjust the learning rates to improve the learning capability. ► This technique can maintain the system stability and reach the desired performance. ► The EMF in the rotating reference frame is utilized in order to estimate speed. - Abstract: This paper presents maximum-power-point-tracking (MPPT) based control algorithms for optimal wind energy capture using radial basis function network (RBFN) and a proposed torque observer MPPT algorithm. The design of a high-performance on-line training RBFN using back-propagation learning algorithm with modified particle swarm optimization (MPSO) regulating controller for the sensorless control of a permanent magnet synchronous generator (PMSG). The MPSO is adopted in this study to adapt the learning rates in the back-propagation process of the RBFN to improve the learning capability. The PMSG is controlled by the loss-minimization control with MPPT below the base speed, which corresponds to low and high wind speed, and the maximum energy can be captured from the wind. Then the observed disturbance torque is feed-forward to increase the robustness of the PMSG system
Genetic Optimization Algorithm of PID Decoupling Control for VAV Air-Conditioning System
Institute of Scientific and Technical Information of China (English)
WANG Jiangjiang; AN Dawei; ZHANG Chunfa; JING Youyin
2009-01-01
Variable-air-volume (VAV) air-conditioning system is a multi-variable system and has multi coupling control loops. While all of the control loops are working together, they interfere and influence each other. A multi-variable decoupling PID controller is designed for VAV air-conditioning system. Diagonal matrix decoupling method is employed to eliminate the coupling between the loop of supply air temperature and that of thermal-space air temperature. The PID controller parameters are optimized by means of an improved genetic algorithm in floating point representations to obtain better performance. The population in the improved genetic algorithm mutates before crossover, which is helpful for the convergence. Additionally the micro mutation algorithm is proposed and applied to improve the convergence during the later evolution. To search the best parameters, the optimized parameters ranges should be amplified l0 times the initial ideal parameters. The simulation and experiment results show that the decoupling control system is effective and feasible. The method can overcome the strong coupling feature of the system and has shorter governing time and less over-shoot than non-optimization PID control.
Hierarchal Scheduling Algorithm for Congestion Traffi Control Using Multi-Agent Systems
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Ma’en Saleh
2014-12-01
Full Text Available Congestion on roads may lead to a catastrophe, especially for those large urban areas. Accordingly, different intelligent traffic-control methodologies had been implemented based on a variety of technologies such as DSP (Digital Signal Processing, WSNs (Wireless Sensors Networks, Image processing, etc. The design process depends on different factors such as fuel consumption, waiting time, traffic volume, and vehicle density. In this paper, we propose an adaptive traffic light control design based on hierarchal scheduling algorithm (WFQ/FCFS. The congestion control problem was modeled based on multi-agent systems, where the whole process was decomposed into a set of communicating sub agents. The traffic congestion control is based on minimizing the average total waiting time of vehicles at each lane in a single intersection. Our proposed control system is mainly designed and modeled based on packet switched networking model, where different classes of real-time traffics (video, audio requesting the best QoS to be guaranteed. Simulation studies shows that the proposed adaptive-weighted-agent-based algorithm (AW Agent Based, the core of control design, outperforms the baseline algorithm as the variance in arrival rates increases.
Optimal fuzzy PID controller with adjustable factors based on flexible polyhedron search algorithm
Institute of Scientific and Technical Information of China (English)
谭冠政; 肖宏峰; 王越超
2002-01-01
A new kind of optimal fuzzy PID controller is proposed, which contains two parts. One is an on-line fuzzy inference system, and the other is a conventional PID controller. In the fuzzy inference system, three adjustable factors xp, xi, and xd are introduced. Their functions are to further modify and optimize the result of the fuzzy inference so as to make the controller have the optimal control effect on a given object. The optimal values of these adjustable factors are determined based on the ITAE criterion and the Nelder and Mead′s flexible polyhedron search algorithm. This optimal fuzzy PID controller has been used to control the executive motor of the intelligent artificial leg designed by the authors. The result of computer simulation indicates that this controller is very effective and can be widely used to control different kinds of objects and processes.
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S. I. Samsudin
2014-01-01
Full Text Available The wastewater treatment plant (WWTP is highly known with the nonlinearity of the control parameters, thus it is difficult to be controlled. In this paper, the enhancement of nonlinear PI controller (ENon-PI to compensate the nonlinearity of the activated sludge WWTP is proposed. The ENon-PI controller is designed by cascading a sector-bounded nonlinear gain to linear PI controller. The rate variation of the nonlinear gain kn is automatically updated based on adaptive interaction algorithm. Initiative to simplify the ENon-PI control structure by adapting kn has been proved by significant improvement under various dynamic influents. More than 30% of integral square error and 14% of integral absolute error are reduced compared to benchmark PI for DO control and nitrate in nitrogen removal control. Better average effluent qualities, less number of effluent violations, and lower aeration energy consumption resulted.
Fuzzy Algorithm for Supervisory Voltage/Frequency Control of a Self Excited Induction Generator
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Hussein F. Soliman
2006-01-01
Full Text Available This paper presents the application of a Fuzzy Logic Controller (FLC to regulate the voltage of a Self Excited Induction Generator (SEIG driven by Wind Energy Conversion Schemes (WECS. The proposed FLC is used to tune the integral gain (KI of a Proportional plus Integral (PI controller. Two types of controls, for the generator and for the wind turbine, using a FLC algorithm, are introduced in this paper. The voltage control is performed to adapt the terminal voltage via self excitation. The frequency control is conducted to adjust the stator frequency through tuning the pitch angle of the WECS blades. Both controllers utilize the Fuzzy technique to enhance the overall dynamic performance. The simulation result depicts a better dynamic response for the system under study during the starting period, and the load variation. The percentage overshoot, rising time and oscillation are better with the fuzzy controller than with the PI controller type.
Robust design of reactor power control system with genetic algorithm-applied weighting functions
International Nuclear Information System (INIS)
The H∞ algorithms of the mixed weight sensitivity is used for the robust design of the reactor power control system. The mixed weight sensitivity method requires the selection of the proper weighting functions for the loop shaping in frequency domain. The complexity of the system equation and the non-convexity of the problem make it very difficult to determine the weighting functions. The genetic algorithm which is improved and hybridized with the simulated annealing is applied to determine the weighting functions. This approach permits an automatic calculation and the resultant system shows good robustness and performance. (author)
Algorithms bio-inspired for the pattern obtention of control bars in BWR reactors
International Nuclear Information System (INIS)
In this work methods based on Genetic Algorithms and Systems based on ant colonies for the obtention of the patterns of control bars of an equilibrium cycle of 18 months for the Laguna Verde nuclear power station are presented. A comparison of obtained results with the methods and with those of design of such equilibrium cycle is presented. As consequence of the study, it was found that the algorithm based on the ant colonies reached to diminish the coast down period (decrease of power at the end of the cycle) in five and half days with respect to the original design what represents an annual saving of $US 100,000. (Author)
An Algorithm of Policy Gradient Reinforcement Learning with a Fuzzy Controller in Policies
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Harukazu Igarashi
2013-04-01
Full Text Available Typical fuzzy reinforcement learning algorithms take value-function based approaches, such as fuzzy Q-learning in Markov Decision Processes (MDPs, and use constant or linear functions in the consequent parts of fuzzy rules. Instead of taking such approaches, we propose a fuzzy reinforcement learning algorithm in another approach. That is the policy gradient approach. Our method can handle fuzzy sets even in the consequent part and also learn the rule weights of fuzzy rules. Specifically, we derived learning rules of membership functions and rule weights for both cases when input/output variables to/from the control system are discrete and continuous.
Ahmed Sabah Al-Araji
2014-01-01
In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tu...
Fu, Xingang; Li, Shuhui; Fairbank, Michael; Wunsch, Donald C; Alonso, Eduardo
2015-09-01
This paper investigates how to train a recurrent neural network (RNN) using the Levenberg-Marquardt (LM) algorithm as well as how to implement optimal control of a grid-connected converter (GCC) using an RNN. To successfully and efficiently train an RNN using the LM algorithm, a new forward accumulation through time (FATT) algorithm is proposed to calculate the Jacobian matrix required by the LM algorithm. This paper explores how to incorporate FATT into the LM algorithm. The results show that the combination of the LM and FATT algorithms trains RNNs better than the conventional backpropagation through time algorithm. This paper presents an analytical study on the optimal control of GCCs, including theoretically ideal optimal and suboptimal controllers. To overcome the inapplicability of the optimal GCC controller under practical conditions, a new RNN controller with an improved input structure is proposed to approximate the ideal optimal controller. The performance of an ideal optimal controller and a well-trained RNN controller was compared in close to real-life power converter switching environments, demonstrating that the proposed RNN controller can achieve close to ideal optimal control performance even under low sampling rate conditions. The excellent performance of the proposed RNN controller under challenging and distorted system conditions further indicates the feasibility of using an RNN to approximate optimal control in practical applications. PMID:25330496
Personalized tuning of a reinforcement learning control algorithm for glucose regulation.
Daskalaki, Elena; Diem, Peter; Mougiakakou, Stavroula G
2013-01-01
Artificial pancreas is in the forefront of research towards the automatic insulin infusion for patients with type 1 diabetes. Due to the high inter- and intra-variability of the diabetic population, the need for personalized approaches has been raised. This study presents an adaptive, patient-specific control strategy for glucose regulation based on reinforcement learning and more specifically on the Actor-Critic (AC) learning approach. The control algorithm provides daily updates of the basal rate and insulin-to-carbohydrate (IC) ratio in order to optimize glucose regulation. A method for the automatic and personalized initialization of the control algorithm is designed based on the estimation of the transfer entropy (TE) between insulin and glucose signals. The algorithm has been evaluated in silico in adults, adolescents and children for 10 days. Three scenarios of initialization to i) zero values, ii) random values and iii) TE-based values have been comparatively assessed. The results have shown that when the TE-based initialization is used, the algorithm achieves faster learning with 98%, 90% and 73% in the A+B zones of the Control Variability Grid Analysis for adults, adolescents and children respectively after five days compared to 95%, 78%, 41% for random initialization and 93%, 88%, 41% for zero initial values. Furthermore, in the case of children, the daily Low Blood Glucose Index reduces much faster when the TE-based tuning is applied. The results imply that automatic and personalized tuning based on TE reduces the learning period and improves the overall performance of the AC algorithm. PMID:24110480
Directory of Open Access Journals (Sweden)
Muhammad Aizzat Zakaria
2013-08-01
Full Text Available Trajectory tracking is an important aspect of autonomous vehicles. The idea behind trajectory tracking is the ability of the vehicle to follow a predefined path with zero steady state error. The difficulty arises due to the nonlinearity of vehicle dynamics. Therefore, this paper proposes a stable tracking control for an autonomous vehicle. An approach that consists of steering wheel control and lateral control is introduced. This control algorithm is used for a non-holonomic navigation problem, namely tracking a reference trajectory in a closed loop form. A proposed future prediction point control algorithm is used to calculate the vehicle’s lateral error in order to improve the performance of the trajectory tracking. A feedback sensor signal from the steering wheel angle and yaw rate sensor is used as feedback information for the controller. The controller consists of a relationship between the future point lateral error, the linear velocity, the heading error and the reference yaw rate. This paper also introduces a spike detection algorithm to track the spike error that occurs during GPS reading. The proposed idea is to take the advantage of the derivative of the steering rate. This paper aims to tackle the lateral error problem by applying the steering control law to the vehicle, and proposes a new path tracking control method by considering the future coordinate of the vehicle and the future estimated lateral error. The effectiveness of the proposed controller is demonstrated by a simulation and a GPS experiment with noisy data. The approach used in this paper is not limited to autonomous vehicles alone since the concept of autonomous vehicle tracking can be used in mobile robot platforms, as the kinematic model of these two platforms is similar.
Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV
Ali, Zain Anwar; Wang, Daobo; Aamir, Muhammad
2016-01-01
In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC) motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability. PMID:27171084
Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV.
Ali, Zain Anwar; Wang, Daobo; Aamir, Muhammad
2016-01-01
In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC) motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability. PMID:27171084
Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV
Directory of Open Access Journals (Sweden)
Zain Anwar Ali
2016-05-01
Full Text Available In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV. The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST controller with model reference adaptive control (MRAC, in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability.
Adaptive fuzzy multivariable controller design based on genetic algorithm for an air handling unit
International Nuclear Information System (INIS)
In HVAC (Heating, Ventilation and Air Conditioning systems, effective thermal management is required because energy and operation costs of buildings are directly influenced by how well an air-conditioning system performs. HVAC systems are typically nonlinear time varying with disturbances, where conventional PID controllers may trade-off between stability and rise time. To overcome this limitation, a Genetic Algorithm based AFLC (Adaptive Fuzzy Logic Controller design has been proposed for the multivariable control of temperature and humidity of a typical AHU (air handling unit by manipulating valve positions to adjust the water and steam flow rates. Modulating equal percentage Globe valves for chilled water and steam have been modeled according to exact flow rates of water and steam. A novel method for the adaptation of FLC (Fuzzy Logic Controller by modifying FRM (Fuzzy Rule Matrix based on GA (genetic algorithm) has been proposed. This requires re-designing the complete FLC in MATLAB/Simulink whose procedure has also been proposed. The proposed adaptive controller outperforms the existing fuzzy controller in terms of steady state error, rise time and settling time. - Highlights: • GA based Adaptive Fuzzy Logic Controller to improve performance of HVAC system. • Multivariable control of an air handling unit to adjust the water and steam flow rates. • Significant improvement in steady state error, rise time and settling time of the control system
Novel Algorithm for Active Noise Control Systems Based on Frequency Selective Filters
Institute of Scientific and Technical Information of China (English)
Hong-liang ZHAO
2010-01-01
A novel algorithm for active noise control systems based on frequency selective filters (FSFANC)is presented in the paper.The FSFANC aims at the m lti-tonal noise attenuation problem.One FSFANC system copes with one of the tonal components,and several FSFANC systems can nun independently in parallel to cancel the selected multiple tones.The proposed algorithm adopts a simple structrue with only two coefficients that can be explained as the real and imaginary parts of the structure to modelthesecondary path,and estimates the secondary path by injecting sinusoidal identification signals.Theoretical analysis and laboratory experiments show that the proposed algorithm possesses some advantages,such as simpler stricture,less computational burden,greater stability,and fast canverging speed.
An Interactive Control Algorithm Used for Equilateral Triangle Formation with Robotic Sensors
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Xiang Li
2014-04-01
Full Text Available This paper describes an interactive control algorithm, called Triangle Formation Algorithm (TFA, used for three neighboring robotic sensors which are distributed randomly to self-organize into and equilateral triangle (E formation. The algorithm is proposed based on the triangular geometry and considering the actual sensors used in robotics. In particular, the stability of the TFA, which can be executed by robotic sensors independently and asynchronously for E formation, is analyzed in details based on Lyapunov stability theory. Computer simulations are carried out for verifying the effectiveness of the TFA. The analytical results and simulation studies indicate that three neighboring robots employing conventional sensors can self-organize into E formations successfully regardless of their initial distribution using the same TFAs.
DEFF Research Database (Denmark)
Ursem, Rasmus Kjær
patchwork model, which is a fundamentally new approach to parameter control based on agents moving in a spatial grid world. For multimodal optimization problems, algorithms are typically designed with two objectives in mind. First, the algorithm shall find the global optimum and avoid stagnation at local...... simulate an evolutionary process where the goal is to evolve solutions by means of crossover, mutation, and selection based on their quality (fitness) with respect to the optimization problem at hand. Evolutionary algorithms (EAs) are highly relevant for industrial applications, because they are capable...... a significant number of generations before superior parameters are evolved. In my study, I experimented with two artificial dynamic problems and showed that the technique fails on even rather simple time-varying problems. In a different study on static problems, Thiemo Krink and I suggested the terrain-based...
Energy management algorithm for an optimum control of a photovoltaic water pumping system
International Nuclear Information System (INIS)
The effectiveness of photovoltaic water pumping systems depends on the adequacy between the generated energy and the volume of pumped water. This paper presents an intelligent algorithm which makes decision on the interconnection modes and instants of photovoltaic installation components: battery, water pump and photovoltaic panel. The decision is made by fuzzy rules on the basis of the Photovoltaic Panel Generation (PVPG) forecast during a considered day, on the load required power, and by considering the battery safety. The algorithm aims to extend operation time of the water pump by controlling a switching unit which links the system components with respect to multi objective management criteria. The algorithm implementation demonstrates that the approach extends the pumping period for more than 5 h a day which gives a mean daily improvement of 97% of the water pumped volume.
Application of hybrid coded genetic algorithm in fuzzy neural network controller
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Presents the fuzzy neural network optimized by hybrid coded genetic algorithm of decimal encoding and bi nary encoding, the searching ability and stability of genetic algorithms enhanced by using binary encoding during the crossover operation and decimal encoding during the mutation operation, and the way of accepting new individuals by probability adopted, by which a new individual is accepted and its parent is discarded when its fitness is higher than that of its parent, and a new individual is accepted by probability when its fitness is lower than that of its parent. And concludes with calculations made with an example that these improvements enhance the speed of genetic algorithms to optimize the fuzzy neural network controller.
A Novel Algorithm of Quantum Random Walk in Server Traffic Control and Task Scheduling
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Dong Yumin
2014-01-01
Full Text Available A quantum random walk optimization model and algorithm in network cluster server traffic control and task scheduling is proposed. In order to solve the problem of server load balancing, we research and discuss the distribution theory of energy field in quantum mechanics and apply it to data clustering. We introduce the method of random walk and illuminate what the quantum random walk is. Here, we mainly research the standard model of one-dimensional quantum random walk. For the data clustering problem of high dimensional space, we can decompose one m-dimensional quantum random walk into m one-dimensional quantum random walk. In the end of the paper, we compare the quantum random walk optimization method with GA (genetic algorithm, ACO (ant colony optimization, and SAA (simulated annealing algorithm. In the same time, we prove its validity and rationality by the experiment of analog and simulation.
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Jérôme Viéron
2004-03-01
Full Text Available This paper introduces source-channel adaptive rate control (SARC, a new congestion control algorithm for layered video transmission in large multicast groups. In order to solve the well-known feedback implosion problem in large multicast groups, we first present a mechanism for filtering RTCP receiver reports sent from receivers to the whole session. The proposed filtering mechanism provides a classification of receivers according to a predefined similarity measure. An end-to-end source and FEC rate control based on this distributed feedback aggregation mechanism coupled with a video layered coding system is then described. The number of layers, their rate, and their levels of protection are adapted dynamically to aggregated feedbacks. The algorithms have been validated with the NS2 network simulator.
Directory of Open Access Journals (Sweden)
Liying Zhang
2013-11-01
Full Text Available Compared with the conventional control systems, networked control systems (NCSs are more open to the external network. As a result, they are more vulnerable to attacks from disgruntled insiders or malicious cyber-terrorist organizations. Therefore, the security issues of NCSs have been receiving a lot of attention recently. In this brief, we review the existing literature on security issues of NCSs and propose some security solutions for the DC motor networked control system. The typical Data Encryption Standard (DES algorithm is adopted to implement data encryption and decryption. Furthermore, we design a Detection and Reaction Mechanism (DARM on the basis of DES algorithm and the improved grey prediction model. Finally, our proposed security solutions are tested with the established models of deception and DOS attacks. According to the results of numerical experiments, it's clear to see the great feasibility and effectiveness of the proposed solutions above.
Guidance and Control Algorithms for the Mars Entry, Descent and Landing Systems Analysis
Davis, Jody L.; CwyerCianciolo, Alicia M.; Powell, Richard W.; Shidner, Jeremy D.; Garcia-Llama, Eduardo
2010-01-01
The purpose of the Mars Entry, Descent and Landing Systems Analysis (EDL-SA) study was to identify feasible technologies that will enable human exploration of Mars, specifically to deliver large payloads to the Martian surface. This paper focuses on the methods used to guide and control two of the contending technologies, a mid- lift-to-drag (L/D) rigid aeroshell and a hypersonic inflatable aerodynamic decelerator (HIAD), through the entry portion of the trajectory. The Program to Optimize Simulated Trajectories II (POST2) is used to simulate and analyze the trajectories of the contending technologies and guidance and control algorithms. Three guidance algorithms are discussed in this paper: EDL theoretical guidance, Numerical Predictor-Corrector (NPC) guidance and Analytical Predictor-Corrector (APC) guidance. EDL-SA also considered two forms of control: bank angle control, similar to that used by Apollo and the Space Shuttle, and a center-of-gravity (CG) offset control. This paper presents the performance comparison of these guidance algorithms and summarizes the results as they impact the technology recommendations for future study.
An Algorithm for Design of Decentralized Suboptimal Controllers with Specified Structure
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David Di Ruscio
1990-07-01
Full Text Available In this paper we present a method for the design of controllers with a specified arbitrary structure for linear multivariable time invariant systems. Both decentralized controllers as well as feedback from a reduced state vector can be designed by this method. The controller will become optimal in the sense that it yields a minimum of a quadratic cost criterion and suboptimal in the sense that it yields a higher value of this criterion than a controller without restrictions. The algorithm makes it possible to specify a stability margin on the feedback system. This means that the feedback system will have eigenvalues located to the left of a certain line (-alpha in the complex plane. The unknown parameters of the controller are collected in a parameter vector. The algorithm is based upon a modified Newton-method for searching towards the 'optimal' parameter vector. The algorithm ensures that the closed loop system is stable at any iteration in the case of an initially stable plant, and after the final iteration in the case of an initially unstable plant.
Design and Implementation of an Optimal Fuzzy Logic Controller Using Genetic Algorithm
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S. Khan
2008-01-01
Full Text Available All control systems suffer from problems related to undesirable overshoot, longer settling times and vibrations while going form one state to another state. Most of relevant techniques had been in the form of suggesting modification and improvement in the instrumentation or interfacing part of the control system and the results reported, remain suffering from shortcomings related to hardware parameter dependence and maintenance and operational complexities. Present study was based on a software approach which was focusing on an algorithmic approach for programming a PIC16F877A microcontroller, for eliminating altogether the parametric dependence issues while adding the benefits of easier modification to suit a given control system to changing operational conditions. Said approach was first simulated using MATLAB/SIMULINK using the techniques of Proportional Derivative Fuzzy Logic Controller (PD-FLC whose membership function, fuzzy logic rules and scaling gains were optimized by the genetic algorithm technique. Simulated results were verified by programming the PIC16F877A microcontroller with the algorithm and using it on a temperature control system where a fan was regulated in response to variations in the ambient system temperature. Resulting tabulated performance indices showed a considerable improvement in rising and settling time besides reducing overshoot and steady state error.
Improvement of Networked Control Systems Performance Using a New Encryption Algorithm
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Seyed Ali Mesbahifard
2014-07-01
Full Text Available Networked control systems are control systems which controllers and plants are connected via telecommunication network. One of the most important challenges in networked control systems is the problem of network time delay. Increasing of time delay may affect on control system performance extremely. Other important issue in networked control systems is the security problems. Since it is possible that unknown people access to network especially Internet, the probability of terrible attacks such as deception attacks is greater, therefore presentation of methods which could decrease time delay and increase system immunity are desired. In this paper a symmetric encryption with low data volume against deception attacks is proposed. This method has high security and low time delay rather than the other encryption algorithms and could improve the control system performance against deception attacks.
An ECN-based Optimal Flow Control Algorithm for the Internet
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
According to the Wide Area Network model, we formulate Internet flow control as a constrained convex programming problem, where the objective is to maximize the total utility of all sources over their transmission rates. Based on this formulation, flow control can be converted to a normal unconstrained optimization problem through the barrier function method, so that it can be solved by means of a gradient projection algorithm with properly rate iterations. We prove that the algorithm converges to the global optimal point, which is also a stable proportional fair rate allocation point, provided that the step size is properly chosen. The main difficulty facing the realization of iteration algorithm is the distributed computation of congestion measure. Fortunately, Explicit Congestion Notification (ECN) is likely to be used to improve the performance of TCP in the near future. By using ECN, it is possible to realize the iteration algorithm in IP networks. Our algorithm is divided into two parts, algorithms in the router and in the source. The router marks the ECN bit with a probability that varies as its buffer occupancy varies, so that the congestion measure of links can be communicated to the source when the marked ECN bits are reflected back from its destination. Source rates are then updated by all sessions according to the received congestion measure. The main advantage of our scheme is its fast convergence ability and robustness; it can also provide the network with zero packet loss by properly choosing the queue threshold and provide differentiated service to users by applying different utility functions.
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B. SENTHILKUMAR
2015-05-01
Full Text Available A novel implementation of code based cryptography (Cryptocoding technique for multi-layer key distribution scheme is presented. VLSI chip is designed for storing information on generation of round keys. New algorithm is developed for reduced key size with optimal performance. Error Control Algorithm is employed for both generation of round keys and diffusion of non-linearity among them. Two new functions for bit inversion and its reversal are developed for cryptocoding. Probability of retrieving original key from any other round keys is reduced by diffusing nonlinear selective bit inversions on round keys. Randomized selective bit inversions are done on equal length of key bits by Round Constant Feedback Shift Register within the error correction limits of chosen code. Complexity of retrieving the original key from any other round keys is increased by optimal hardware usage. Proposed design is simulated and synthesized using VHDL coding for Spartan3E FPGA and results are shown. Comparative analysis is done between 128 bit Advanced Encryption Standard round keys and proposed round keys for showing security strength of proposed algorithm. This paper concludes that chip based multi-layer key distribution of proposed algorithm is an enhanced solution to the existing threats on cryptography algorithms.
Montilla, I; Béchet, C; Le Louarn, M; Reyes, M; Tallon, M
2010-11-01
Extremely Large Telescopes (ELTs) are very challenging with respect to their adaptive optics (AO) requirements. Their diameters and the specifications required by the astronomical science for which they are being designed imply a huge increment in the number of degrees of freedom in the deformable mirrors. Faster algorithms are needed to implement the real-time reconstruction and control in AO at the required speed. We present the results of a study of the AO correction performance of three different algorithms applied to the case of a 42-m ELT: one considered as a reference, the matrix-vector multiply (MVM) algorithm; and two considered fast, the fractal iterative method (FrIM) and the Fourier transform reconstructor (FTR). The MVM and the FrIM both provide a maximum a posteriori estimation, while the FTR provides a least-squares one. The algorithms are tested on the European Southern Observatory (ESO) end-to-end simulator, OCTOPUS. The performance is compared using a natural guide star single-conjugate adaptive optics configuration. The results demonstrate that the methods have similar performance in a large variety of simulated conditions. However, with respect to system misregistrations, the fast algorithms demonstrate an interesting robustness. PMID:21045895
Integrated Multiobjective Optimal Design for Active Control System Based on Genetic Algorithm
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Ma Yong-Quan
2014-01-01
Full Text Available The integrated multiobjective optimal design method for structural active control system is put forward based on improved Pareto multiobjective genetic algorithm, through which the position of actuator is synchronously optimized with active controller. External excitation is simulated by stationary filtered white noise. The root-mean-square (RMS of structural response and active control force can be achieved by solving Lyapunov equation in the state space. The design of active controller adopts linear quadratic regulator (LQR control algorithm. Minimum ratio of the maximum RMS of controlled structural displacement divided by the maximum RMS of uncontrolled structural displacement and minimum ratio of the maximum RMS of controlled structural shear divided by the maximum RMS of uncontrolled structural shear, together with minimization of the sum of RMS of active control force, are used as the three objective functions of multiobjective optimization. The optimization process takes the impact of structure and excitation parameter on the optimized results. An eight-storey six-span plane steel frame was used as an emulational example to demonstrate the validity of this optimization method. Results show that the proposed integrated multiobjective optimal design method is simple, efficient, and practical with good universality.
Frost, Susan A.; Bodson, Marc; Acosta, Diana M.
2009-01-01
The Next Generation (NextGen) transport aircraft configurations being investigated as part of the NASA Aeronautics Subsonic Fixed Wing Project have more control surfaces, or control effectors, than existing transport aircraft configurations. Conventional flight control is achieved through two symmetric elevators, two antisymmetric ailerons, and a rudder. The five effectors, reduced to three command variables, produce moments along the three main axes of the aircraft and enable the pilot to control the attitude and flight path of the aircraft. The NextGen aircraft will have additional redundant control effectors to control the three moments, creating a situation where the aircraft is over-actuated and where a simple relationship does not exist anymore between the required effector deflections and the desired moments. NextGen flight controllers will incorporate control allocation algorithms to determine the optimal effector commands and attain the desired moments, taking into account the effector limits. Approaches to solving the problem using linear programming and quadratic programming algorithms have been proposed and tested. It is of great interest to understand their relative advantages and disadvantages and how design parameters may affect their properties. In this paper, we investigate the sensitivity of the effector commands with respect to the desired moments and show on some examples that the solutions provided using the l2 norm of quadratic programming are less sensitive than those using the l1 norm of linear programming.
Luo, Yugong; Chen, Tao; Li, Keqiang
2015-12-01
The paper presents a novel active distance control strategy for intelligent hybrid electric vehicles (IHEV) with the purpose of guaranteeing an optimal performance in view of the driving functions, optimum safety, fuel economy and ride comfort. Considering the complexity of driving situations, the objects of safety and ride comfort are decoupled from that of fuel economy, and a hierarchical control architecture is adopted to improve the real-time performance and the adaptability. The hierarchical control structure consists of four layers: active distance control object determination, comprehensive driving and braking torque calculation, comprehensive torque distribution and torque coordination. The safety distance control and the emergency stop algorithms are designed to achieve the safety and ride comfort goals. The optimal rule-based energy management algorithm of the hybrid electric system is developed to improve the fuel economy. The torque coordination control strategy is proposed to regulate engine torque, motor torque and hydraulic braking torque to improve the ride comfort. This strategy is verified by simulation and experiment using a forward simulation platform and a prototype vehicle. The results show that the novel control strategy can achieve the integrated and coordinated control of its multiple subsystems, which guarantees top performance of the driving functions and optimum safety, fuel economy and ride comfort.
Energy Technology Data Exchange (ETDEWEB)
Larbes, C.; Ait Cheikh, S.M.; Obeidi, T.; Zerguerras, A. [Laboratoire des Dispositifs de Communication et de Conversion Photovoltaique, Departement d' Electronique, Ecole Nationale Polytechnique, 10, Avenue Hassen Badi, El Harrach, Alger 16200 (Algeria)
2009-10-15
This paper presents an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and irradiance conditions. First, for the purpose of comparison and because of its proven and good performances, the perturbation and observation (P and O) technique is briefly introduced. A fuzzy logic controller based MPPT (FLC) is then proposed which has shown better performances compared to the P and O MPPT based approach. The proposed FLC has been also improved using genetic algorithms (GA) for optimisation. Different development stages are presented and the optimized fuzzy logic MPPT controller (OFLC) is then simulated and evaluated, which has shown better performances. (author)
STRUCTURED PARAMETRIC OPTIMIZATION OF MULTIVARIABLE ROBUST CONTROL BASED ON GENETIC ALGORITHMS
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Anatoliy A. Tunik
2008-02-01
Full Text Available This paper is devoted to the parametric robust - optimization of the LQG- controller designed for multivariable flight control system. At the 1St stage LQG- regulator is designed using the separation theorem. At the 2nd stage this controller was parametrically optimized on the basis of -criterion using genetic algorithm to find the trade-off between the performance and robustness. The sensitivity theory is applied to reduce the number of parameters involved in the optimization procedure.
A Path Select Algorithm with Error Control Schemes and Energy Efficient Wireless Sensor Networks
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Sandeep Dahiya
2012-04-01
Full Text Available A wireless sensor network consists of a large number of sensor nodes that are spread densely to observe the phenomenon. The whole network lifetime relies on the lifetime of the each sensor node. If one node dies, it could lead to a separation of the sensor network. Also a multi hop structure and broadcast channel of wireless sensornecessitate error control scheme to achieve reliable data transmission. Automatic repeat request (ARQ and forward error correction (FEC are the key error control strategies in wire sensor network. In this paper we propose a path selection algorithm with error control schemes using energy efficient analysis.
Coordinated Control of PV Generation and EVs Charging Based on Improved DECell Algorithm
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Guo Zhao
2015-01-01
Full Text Available Recently, the coordination of EVs’ charging and renewable energy has become a hot research all around the globe. Considering the requirements of EV owner and the influence of the PV output fluctuation on the power grid, a three-objective optimization model was established by controlling the EVs charging power during charging process. By integrating the meshing method into differential evolution cellular (DECell genetic algorithm, an improved differential evolution cellular (IDECell genetic algorithm was presented to solve the multiobjective optimization model. Compared to the NSGA-II and DECell, the IDECell algorithm showed better performance in the convergence and uniform distribution. Furthermore, the IDECell algorithm was applied to obtain the Pareto front of nondominated solutions. Followed by the normalized sorting of the nondominated solutions, the optimal solution was chosen to arrive at the optimized coordinated control strategy of PV generation and EVs charging. Compared to typical charging pattern, the optimized charging pattern could reduce the fluctuations of PV generation output power, satisfy the demand of EVs charging quantity, and save the total charging cost.
Filtered-X Affine Projection Algorithms for Active Noise Control Using Volterra Filters
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Sicuranza Giovanni L
2004-01-01
Full Text Available We consider the use of adaptive Volterra filters, implemented in the form of multichannel filter banks, as nonlinear active noise controllers. In particular, we discuss the derivation of filtered-X affine projection algorithms for homogeneous quadratic filters. According to the multichannel approach, it is then easy to pass from these algorithms to those of a generic Volterra filter. It is shown in the paper that the AP technique offers better convergence and tracking capabilities than the classical LMS and NLMS algorithms usually applied in nonlinear active noise controllers, with a limited complexity increase. This paper extends in two ways the content of a previous contribution published in Proc. IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP '03, Grado, Italy, June 2003. First of all, a general adaptation algorithm valid for any order of affine projections is presented. Secondly, a more complete set of experiments is reported. In particular, the effects of using multichannel filter banks with a reduced number of channels are investigated and relevant results are shown.
Fuzzy Control and Connected Region Marking Algorithm-Based SEM Nanomanipulation
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Dongjie Li
2012-01-01
Full Text Available The interactive nanomanipulation platform is established based on fuzzy control and connected region marking (CRM algorithm in SEM. The 3D virtual nanomanipulation model is developed to make up the insufficiency of the 2D SEM image information, which provides the operator with depth and real-time visual feedback information to guide the manipulation. The haptic device Omega3 is used as the master to control the 3D motion of the nanopositioner in master-slave mode and offer the force sensing to the operator controlled with fuzzy control algorithm. Aiming at sensing of force feedback during the nanomanipulation, the collision detection method of the virtual nanomanipulation model and the force rending model are studied to realize the force feedback of nanomanipulation. The CRM algorithm is introduced to process the SEM image which provides effective position data of the objects for updating the virtual environment (VE, and relevant issues such as calibration and update rate of VE are also discussed. Finally, the performance of the platform is validated by the ZnO nanowire manipulation experiments.
Multi-agent coordination algorithms for control of distributed energy resources in smart grids
Cortes, Andres
Sustainable energy is a top-priority for researchers these days, since electricity and transportation are pillars of modern society. Integration of clean energy technologies such as wind, solar, and plug-in electric vehicles (PEVs), is a major engineering challenge in operation and management of power systems. This is due to the uncertain nature of renewable energy technologies and the large amount of extra load that PEVs would add to the power grid. Given the networked structure of a power system, multi-agent control and optimization strategies are natural approaches to address the various problems of interest for the safe and reliable operation of the power grid. The distributed computation in multi-agent algorithms addresses three problems at the same time: i) it allows for the handling of problems with millions of variables that a single processor cannot compute, ii) it allows certain independence and privacy to electricity customers by not requiring any usage information, and iii) it is robust to localized failures in the communication network, being able to solve problems by simply neglecting the failing section of the system. We propose various algorithms to coordinate storage, generation, and demand resources in a power grid using multi-agent computation and decentralized decision making. First, we introduce a hierarchical vehicle-one-grid (V1G) algorithm for coordination of PEVs under usage constraints, where energy only flows from the grid in to the batteries of PEVs. We then present a hierarchical vehicle-to-grid (V2G) algorithm for PEV coordination that takes into consideration line capacity constraints in the distribution grid, and where energy flows both ways, from the grid in to the batteries, and from the batteries to the grid. Next, we develop a greedy-like hierarchical algorithm for management of demand response events with on/off loads. Finally, we introduce distributed algorithms for the optimal control of distributed energy resources, i
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Tine L. Vandoorn
2015-06-01
Full Text Available The increasing share of distributed energy resources poses a challenge to the distribution network operator (DNO to maintain the current availability of the system while limiting the investment costs. Related to this, there is a clear trend in DNOs trying to better monitor their grid by installing a distribution management system (DMS. This DMS enables the DNOs to remotely switch their network or better localize and solve faults. Moreover, the DMS can be used to centrally control the grid assets. Therefore, in this paper, a control strategy is discussed that can be implemented in the DMS for solving current congestion problems posed by the increasing share of renewables in the grid. This control strategy controls wind turbines in order to avoid congestion while mitigating the required investment costs in order to achieve a global cost-efficient solution. Next to the application and objective of the control, the parameter tuning of the control algorithm is discussed.
Study of On-Ramp PI Controller Based on Dural Group QPSO with Different Well Centers Algorithm
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Tao Wu
2015-01-01
Full Text Available A novel quantum-behaved particle swarm optimization (QPSO algorithm, dual-group QPSO with different well centers (DWC-QPSO algorithm, is proposed by constructing the master-slave subswarms. The new algorithm was applied in the parameter optimization of on-ramp traffic PI controller combining with nonlinear feedback theory. With the critical information contained in the searching space and results of the basic QPSO algorithm, this algorithm avoids the rapid disappearance of swarm diversity and enhances the global searching ability through collaboration between subswarms. Experiment results on an on-ramp traffic control simulation show that DWC-QPSO can be well applied in the study of on-ramp traffic PI controller and the comparison results illustrate that DWC-QPSO outperforms other evolutionary algorithms with enhancement in both adaptability and stability.
The development of controller and navigation algorithm for underwater wall crawler
Energy Technology Data Exchange (ETDEWEB)
Cho, Hyung Suck; Kim, Kyung Hoon; Kim, Min Young [Korea Advanced Institute of Science and Technology, Taejon (Korea)
1999-01-01
In this project, the control system of a underwater robotic vehicle(URV) for underwater wall inspection in the nuclear reactor pool or the related facilities has been developed. The following 4-sub projects have been studied for this project: (1) Development of the controller and motor driver for the URV (2) Development of the control algorithm for the tracking control of the URV (3) Development of the localization system (4) Underwater experiments of the developed system. First, the dynamic characteristic of thruster with the DC servo-motor was analyzed experimentally. Second the controller board using the INTEL 80C196 was designed and constructed, and the software for the communication and motor control is developed. Third the PWM motor-driver was developed. Fourth the localization system using the laser scanner and inclinometer was developed and tested in the pool. Fifth the dynamics of the URV was studied and the proper control algorithms for the URV was proposed. Lastly the validation of the integrated system was experimentally performed. (author). 27 refs., 51 figs., 8 tabs.
Comparison of PID Controller Tuning Methods with Genetic Algorithm for FOPTD System
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K. Mohamed Hussain
2014-02-01
Full Text Available Measurement of Level, Temperature, Pressure and Flow parameters are very vital in all process industries. A combination of a few transducers with a controller, that forms a closed loop system leads to a stable and effective process. This article deals with control of in the process tank and comparative analysis of various PID control techniques and Genetic Algorithm (GA technique. The model for such a Real-time process is identified as First Order Plus Dead Time (FOPTD process and validated. The need for improved performance of the process has led to the development of model based controllers. Well-designed conventional Proportional, Integral and Derivative (PID controllers are the most widely used controller in the chemical process industries because of their simplicity, robustness and successful practical applications. Many tuning methods have been proposed for PID controllers. Many tuning methods have been proposed for obtaining better PID controller parameter settings. The comparison of various tuning methods for First Order Plus Dead Time (FOPTD process are analysed using simulation software. Our purpose in this study is comparison of these tuning methods for single input single output (SISO systems using computer simulation.Also efficiency of various PID controller are investigated for different performance metrics such as Integral Square Error (ISE, Integral Absolute Error (IAE, Integral Time absolute Error (ITAE, and Mean square Error (MSE is presented and simulation is carried out. Work in this paper explores basic concepts, mathematics, and design aspect of PID controller. Comparison between the PID controller and Genetic Algorithm (GA will have been carried out to determine the best controller for the temperature system.
The influence of control algorithm on the annual energy consumption of automated climate systems
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Azivskaya S.S.
2012-03-01
Full Text Available In the paper the estimation of energy consumption of the automated ventilating systems and air conditionings (V and AC under condition of their regulation "on deviation" is reviewed.The analysis of processes descending in V and AC and maintained room is given. The outcomes of numerical calculation of a non-steady thermal mode of a room with the computer program designed by authors are adduced. Calculations were organized on different combinations of radiant and convective components of variable heat ingress.The optimal control algorithm of V and AC from the point of view of minimal general energy consumption during the heating system is found. The presentation is illustrated by a graphic stuff and by a numerical example of technical and economical estimation of optimal control algorithm using.