Admission Control Algorithm for Guaranteeing Real-Time Anycast Flow
Weijia Jia; Zhang Chuanlin
2002-01-01
In this paper, we study admission control algorithm for anycast flow with real-time constraints. With the given time requirement, when the result of this algorithm give succeed information, we find route for the anycast flow requesting. Therefore, what we need to do is testing if the corresponding path rj has enough bandwidth for coming anycast flow requirement at source S with end-to-end deadline D. This admission control is scalable in terms of the number of flows can be admitted through local information of the routes.
A Novel Admission Control Algorithm Based on Negotiation and Price
ZHANG Deng-yin; ZHANG Li; TANG Zhi-yun
2005-01-01
Admission control algorithm is a key component of a media server which supports Quality of Service(QoS).In this paper we present an admission control algorithm that exploits the elastic properties of the user requirements and the changing properties of system conditions.The characteristic of the algorithm can be expounded from these aspects:First,it provides multiple services to satisfy the different users' requirements regarding QoS and price.Second,it uses a worth function to select from media services with different QoS characteristics in the negotiation process.Finally,it employs a novel price policy to compute the charge for the service,which has a great effect on restricting the greediness of the users and therefore increase the overall user benefit.In the end of the paper,we compare the user benefit attained by our algorithm with that of other method.
A structural comparison of measurement-based admission control algorithms
GU Yi-ran; WANG Suo-ping; WU Hai-ya
2006-01-01
Measurement-based admission control (MBAC)algorithm is designed for the relaxed real-time service. In contrast to traditional connection admission control mechanisms,the most attractive feature of MBAC algorithm is that it does not require a prior traffic model and that is very difficult for the user to come up with a tight traffic model before establishing a flow.Other advantages of MBAC include that it can achieve higher network utilization and offer quality service to users. In this article, the study of the equations in the MBAC shows that they can all be expressed in the same form. Based on the same form,some MBAC algorithms can achieve same performance only if they satisfy some conditions.
A COMBINED ADMISSION CONTROL ALGORITHM WITH DA PROTOCOL FOR SATELLITE ATM NETWORKS
Lu Rong; Cao Zhigang
2006-01-01
Admission control is an important strategy for Quality of Service (QoS) provisioning in Asynchronous Transfer Mode (ATM) networks. Based on a control-theory model of resources on-Demand Allocation (DA) protocol, the paper studies the effect of the protocol on the statistical characteristics of network traffic,and proposes a combined connection admission control algorithm with the DA protocol to achieve full utilization of link resources in satellite communication systems. The proposed algorithm is based on the cross-layer-design approach. Theoretical analysis and system simulation results show that the proposed algorithm can admit more connections within certain admission thresholds than one that does not take into account the DA protocol. Thus, the proposed algorithm can increase admission ratio of traffic sources for satellite ATM networks and improve satellite link utilization.
Algorithms for Deterministic Call Admission Control of Pre-stored VBR Video Streams
Christos Tryfonas
2009-08-01
Full Text Available We examine the problem of accepting a new request for a pre-stored VBR video stream that has been smoothed using any of the smoothing algorithms found in the literature. The output of these algorithms is a piecewise constant-rate schedule for a Variable Bit-Rate (VBR stream. The schedule guarantees that the decoder buffer does not overflow or underflow. The problem addressed in this paper is the determination of the minimal time displacement of each new requested VBR stream so that it can be accommodated by the network and/or the video server without overbooking the committed traffic. We prove that this call-admission control problem for multiple requested VBR streams is NP-complete and inapproximable within a constant factor, by reducing it from the VERTEX COLOR problem. We also present a deterministic morphology-sensitive algorithm that calculates the minimal time displacement of a VBR stream request. The complexity of the proposed algorithm along with the experimental results we provide indicate that the proposed algorithm is suitable for real-time determination of the time displacement parameter during the call admission phase.
An Efficient Admission Control Algorithm for Load Balancing In Hierarchical Mobile IPv6 Networks
Harini, Prof P
2009-01-01
In hierarchical Mobile IPv6 networks, Mobility Anchor Point (MAP) may become a single point of bottleneck as it handles more and more mobile nodes (MNs). A number of schemes have been proposed to achieve load balancing among different MAPs. However, signaling reduction is still imperfect because these schemes also avoid the effect of the number of CNs. Also only the balancing of MN is performed, but not the balancing of the actual traffic load, since CN of each MN may be different. This paper proposes an efficient admission control algorithm along with a replacement mechanism for HMIPv6 networks. The admission control algorithm is based on the number of serving CNs and achieves actual load balancing among MAPs. Moreover, a replacement mechanism is introduced to decrease the new MN blocking probability and the handoff MN dropping probability. By simulation results, we show that, the handoff delay and packet loss are reduced in our scheme, when compared with the standard HMIPv6 based handoff.
Call Admission Control Algorithm for pre-stored VBR video streams
Tryfonas, Christos; Mehler, Andrew; Skiena, Steven
2008-01-01
We examine the problem of accepting a new request for a pre-stored VBR video stream that has been smoothed using any of the smoothing algorithms found in the literature. The output of these algorithms is a piecewise constant-rate schedule for a Variable Bit-Rate (VBR) stream. The schedule guarantees that the decoder buffer does not overflow or underflow. The problem addressed in this paper is the determination of the minimal time displacement of each new requested VBR stream so that it can be accomodated by the network and/or the video server without overbooking the committed traffic. We prove that this call-admission control problem for multiple requested VBR streams is NP-complete and inapproximable within a constant factor, by reducing it from the VERTEX COLOR problem. We also present a deterministic morphology-sensitive algorithm that calculates the minimal time displacement of a VBR stream request. The complexity of the proposed algorithm make it suitable for real-time determination of the time displacem...
GUIZhibo; ZHOULichao
2005-01-01
The advantage of Measurement-based admission control algorithms (MBACs) is that they are able to improve network utilization for the controlled-load service. Most researchers have focused primarily on designs of the Admission control equations (ACEs) of MBACs using a variety of principled and ad hoc motivations. In this paper, six typical MBACs, namely MS, HB, TP, TO, TE and MC algorithms, are discussed. First, we have proven analytically that the ACEs of TE and MC have the same structural form as the ACEs of the other four MBACs above. Second, through formal analysis we have theoretically proven that the ACEs of TE and MC, even though they are derived and motivated in quite different ways, are equivalent to the other four MBACs by tuning the adjustable parameters of MBACs. Finally, we have used also simulations to confirm our work.
XUEGuangtao; SHIHua; YOUJinyuan; YAOWensheng
2003-01-01
Mobile peer-to-peer media streaming systems are expected to become as popular as the peer-to-peer file sharing systems. In this paper, we study two key problems arising from mobile peer-to-peer media streaming: the stability of interconnection between supplying peers and requesting peers in mobile peer-to-peer streaming system; and fast capacity amplification of the entire mobile peer-to-peer streaming system. We use the Stable group algorithm to characterize user mobility in mobile ad hoc networks. Based on the stable group, we then propose a distributed Stable-group differentiated admission control algorithm (SGDACp2p), which leads to fast amplifying the system's total streaming capacity using its self-growing. At last, the extensive simulation results are presented to compare between the SGDACp2p and traditional methods to prove the superiority of the algorithm.
The admission control algorithm based on the heterogeneous network environment%基于异构网络环境中的接纳控制算法
黄存东; 王胜
2012-01-01
Admission control system which can effectively deal with network congestion can provide dependable Qos for VoIP application. Taking the advantages and universality of Random Early Detection （RED） in implementing fair queue management for VolP application, we proposed a delay analyzing and computing method of RED queues in this paper and achieved a RED--based admission control algorithm whose effectiveness is proved through simulation.%接纳控制机制可以有效控制网络拥塞程度,为VoIP应用提供服务质量保证。RED算法可以为VoIP应用提供公平的队列管理机制,鉴于RED队列的优越性和普遍性,提出了RED队列的延迟分析计算方法,并基于该计算方法设计实现了基于RED的接纳控制算法,仿真结果表明该算法是有效的。
LTE-A中基于准入控制的切换决策算法%Handoff Decision Algorithm Based on Admission Control in LTE-A
王华; 李鲁群; 王力
2011-01-01
在E-UTRAN架构下,提出一种基于目标小区准入控制的切换决策算法.通过eNB之间的X2接口来交互网络的负载信息、资源信息和服务速率等,以此获得对目标小区准入控制的预测.构建曼哈顿模型场景,仿真结果证明,该切换算法有较高的切换成功率和较小的切换时延;并可将用户终端切换到负载比较轻的小区,使相邻小区的负载得到均衡,提高了无线资源的利用率.%This paper provides a handoff decision algorithm based on admission control of target cell in the E-UTRAN architecture.In order to predict the admission control of target cell, it uses the X2 interface between eNBs to exchange the load information load network, resource information, and services rate of network.It constructs the Manhattan model.Simulation results indicate that the algorithm has higher successful handoff rate and smaller delay of handoff.It can switch the user terminal to the cell with lighter load, to make sure balancing the neighboring load and improving utilization of wireless resources.
Advanced Fuzzy Logic Based Admission Control for UMTS System
P. Kejik
2010-12-01
Full Text Available The capacity of CDMA (Code Division Multiple Access systems is interference limited. Therefore radio resources management (RRM functions are 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 (Universal Mobile Telecommunication System. A UMTS system model and four fuzzy logic based admission control algorithms are presented in this paper. Two new versions of fuzzy logic based admission control algorithms are presented there. All algorithms are mutually compared via simulations. Simulations show that the novel advanced fuzzy algorithm outperforms the other simulated algorithms (in terms of blocking probability, dropping probability and the number of active UEs in cell.
A NEW ADMISSION CONTROL APPROACH BASED ON PREDICTION
Lu Kaining; Jin Zhigang; Zou Jun
2002-01-01
Admission control plays an important role in providing QoS to network users. Motivated by the measurement-based admission control algorithm, this letter proposed a new admission control approach for integrated service packet network based on traffic prediction. In the letter, FARIMA(p, d, q) models in the admission control algorithm is deployed. A method to simplify the FARIMA model fitting procedure and hence to reduce the time of traffic modeling and prediction is suggested. The feasibility-study experiments show that FARIMA models which have less number of parameters can be used to model and predict actual traffic on quite a large time scale. Simulation results validate the promising approach.
A scalable admission control scheme based on time label
杨松岸; 杨华; 杨宇航
2004-01-01
Resource reservation protocols allow communicating hosts to reserve resources such as bandwidth to offer guaranteed service. However, current resource reservation architectures do not scale well for a large number of flows. In this paper, we present a simple reservation protocol and a scalable admission control algorithm, which can provide QoS guarantees to individual flows without per-flow management in the network core. By mapping each flow to a definite time, this scheme addresses the problems that limit the effectiveness of current endpoint admission control schemes. The overall admission control process is described. Analysis is used to explain the reasonability of our scheme and simulation validates its performance.
An Intelligent Call Admission Control Decision Mechanism for Wireless Networks
S., Ramesh Babu H; S, Satyanarayana P
2010-01-01
The Call admission control (CAC) is one of the Radio Resource Management (RRM) techniques plays instrumental role in ensuring the desired Quality of Service (QoS) to the users working on different applications which have diversified nature of QoS requirements. This paper proposes a fuzzy neural approach for call admission control in a multi class traffic based Next Generation Wireless Networks (NGWN). The proposed Fuzzy Neural Call Admission Control (FNCAC) scheme is an integrated CAC module that combines the linguistic control capabilities of the fuzzy logic controller and the learning capabilities of the neural networks .The model is based on Recurrent Radial Basis Function Networks (RRBFN) which have better learning and adaptability that can be used to develop the intelligent system to handle the incoming traffic in the heterogeneous network environment. The proposed FNCAC can achieve reduced call blocking probability keeping the resource utilisation at an optimal level. In the proposed algorithm we have c...
Call Admission Control in Mobile Cellular Networks
Ghosh, Sanchita
2013-01-01
Call Admission Control (CAC) and Dynamic Channel Assignments (DCA) are important decision-making problems in mobile cellular communication systems. Current research in mobile communication considers them as two independent problems, although the former greatly depends on the resulting free channels obtained as the outcome of the latter. This book provides a solution to the CAC problem, considering DCA as an integral part of decision-making for call admission. Further, current technical resources ignore movement issues of mobile stations and fluctuation in network load (incoming calls) in the control strategy used for call admission. In addition, the present techniques on call admission offers solution globally for the entire network, instead of considering the cells independently. CAC here has been formulated by two alternative approaches. The first approach aimed at handling the uncertainty in the CAC problem by employing fuzzy comparators. The second approach is concerned with formulation of CAC ...
Admission Control of VL in AFDX Under HRT Constraints
ZHOU Qiang; QU Zhenliang; LIN Hengqing
2011-01-01
Avionics full duplex switched ethernet (AFDX) is a switched interconnection technology developed to provide reliable data exchange with strong data transmission time guarantees in internal communication of the spacecraft or aircraft. Virtual link (VL) is an important concept of AFDX to meet quality of service (QoS) requirements in terms of end-to-end message deadlines. A VL admission control algorithm in AFDX network under hard real-time (HRT) constraints is studied. Based on the scheduling principle of AFDX protocol, a packet scheduling scheme under HRT constraints is proposed, and after that an efficient VL admission control algorithm is presented. Analytical proof that the algorithm can effectively determine whether VL should be admitted is given. Finally simulative examples are presented to promote the conclusion.
A scalable admission control scheme based on time label
杨松岸; 杨华; 杨宇航
2004-01-01
Resource reservation protocols allow communicating hosts to reserve resources such as bandwidth to offer guaranteed service. However,current resource reservation architectures do not scale well for a large number of flows. In this paper,we present a simple reservation protocol and a scalable admission control algorithm,which can provide QoS guarantees to individual flows without per-flow management in the network core. By mapping each flow to a definite time,this scheme addresses the problems that limit the effectiveness of current endpoint admission control schemes. The overall admission control process is described. Analysis is used to explain the reasonability of our scheme and simulation validates its performance.
徐晓希; 朱新宁; 徐春秀
2009-01-01
针对IEEE 802.16 OFDMA系统,提出了一种考虑运营收益并且动态调整预留信道的呼叫接纳控制算法.该算法将一个连接申请潜在的运营收益值作为接入优先级函数的因子,从而提高系统的运营收益;其次,算法根据系统内资源的使用情况动态调整预留信道,在降低系统掉话率的同时,也尽可能地将呼叫阻塞率保持在较低水平.将所提算法与传统接纳控制方法进行了仿真比较,结果表明该算法能够有效控制系统掉话率和阻塞率,达到用户使用满意度要求,同时增大系统运营收益.%This paper proposed a call admission control algorithm in IEEE 802.16 OFDMA systems, which took the revenue of the service providers into consideration and adjusted the threshold of reserved guard channel dynamically. First, introduced the revenue generated by accepting a connection in the admission priority function to produce high revenue of the system. Se-cond, the proposed algorithm adjusted the reserved channel according to the state of system dynamically so as to reduce the call dropping probability (CDP) and the call blocking probability (CBP) simultaneously. The simulation results show that the proposed algorithm can decrease CDP and CBP effectively to achieve high users' satisfaction degree, while increase the revenue of the network at the same time.
Self-optimisation of admission control and handover parameters in LTE
Sas, B.; Spaey, K.; Balan, I.; Zetterberg, K.; Litjens, R.
2011-01-01
In mobile cellular networks the handover (HO) algorithm is responsible for determining when calls of users that are moving from one cell to another are handed over from the former to the latter. The admission control (AC) algorithm, which is the algorithm that decides whether new (fresh or HO) calls
Development of a validation algorithm for 'present on admission' flagging
Cheng Diana
2009-12-01
Full Text Available Abstract Background The use of routine hospital data for understanding patterns of adverse outcomes has been limited in the past by the fact that pre-existing and post-admission conditions have been indistinguishable. The use of a 'Present on Admission' (or POA indicator to distinguish pre-existing or co-morbid conditions from those arising during the episode of care has been advocated in the US for many years as a tool to support quality assurance activities and improve the accuracy of risk adjustment methodologies. The USA, Australia and Canada now all assign a flag to indicate the timing of onset of diagnoses. For quality improvement purposes, it is the 'not-POA' diagnoses (that is, those acquired in hospital that are of interest. Methods Our objective was to develop an algorithm for assessing the validity of assignment of 'not-POA' flags. We undertook expert review of the International Classification of Diseases, 10th Revision, Australian Modification (ICD-10-AM to identify conditions that could not be plausibly hospital-acquired. The resulting computer algorithm was tested against all diagnoses flagged as complications in the Victorian (Australia Admitted Episodes Dataset, 2005/06. Measures reported include rates of appropriate assignment of the new Australian 'Condition Onset' flag by ICD chapter, and patterns of invalid flagging. Results Of 18,418 diagnosis codes reviewed, 93.4% (n = 17,195 reflected agreement on status for flagging by at least 2 of 3 reviewers (including 64.4% unanimous agreement; Fleiss' Kappa: 0.61. In tests of the new algorithm, 96.14% of all hospital-acquired diagnosis codes flagged were found to be valid in the Victorian records analysed. A lower proportion of individual codes was judged to be acceptably flagged (76.2%, but this reflected a high proportion of codes used Conclusion An indicator variable about the timing of occurrence of diagnoses can greatly expand the use of routinely coded data for hospital quality
TCP-Call Admission Control Interaction in Multiplatform Space Architectures
Georgios Theodoridis
2007-06-01
Full Text Available The implementation of efficient call admission control (CAC algorithms is useful to prevent congestion and guarantee target quality of service (QoS. When TCP protocol is adopted, some inefficiencies can arise due to the peculiar evolution of the congestion window. The development of cross-layer techniques can greatly help to improve efficiency and flexibility for wireless networks. In this frame, the present paper addresses the introduction of TCP feedback into the CAC procedures in different nonterrestrial wireless architectures. CAC performance improvement is shown for different space-based architectures, including both satellites and high altitude platform (HAP systems.
The admissible portfolio selection problem with transaction costs and an improved PSO algorithm
Chen, Wei; Zhang, Wei-Guo
2010-05-01
In this paper, we discuss the portfolio selection problem with transaction costs under the assumption that there exist admissible errors on expected returns and risks of assets. We propose a new admissible efficient portfolio selection model and design an improved particle swarm optimization (PSO) algorithm because traditional optimization algorithms fail to work efficiently for our proposed problem. Finally, we offer a numerical example to illustrate the proposed effective approaches and compare the admissible portfolio efficient frontiers under different constraints.
Power Control Technique for Efficient Call Admission Control in Advanced Wirless Networks
Ch. Sreenivasa Rao
2012-06-01
Full Text Available In 4G networks, call admission control techniques have been proposed to provide Quality of Service (QoS in a network by restricting the access to network resources. Power control is essential in call admission control in order to provide fair access to all users, improve battery lifetime and system performance. But the existing call admission control algorithms rarely consider the power controlling techniques in the handoff process for different traffic classes. In this paper, we propose to develop a power controlled call admission control scheme for handoff in the advanced wireless networks. The incoming call measures the initial interference on it and then the base station starts transmitting the packets to the new call. The new call is rejected when the interference reaches a threshold value.Whenever an existing call meets the power constraint, the transmit power is decremented based on thetraffic class and incoming call obtains this information by monitoring the interference received on it. Theconvergence of the power control algorithm is checked and the power levels of all incoming calls areadjusted. From our simulation results we prove that this power control technique provides efficienthandoff in the 4G networks by increasing the throughput and reducing the delay of the existing users.
28 CFR 541.47 - Admission to control unit.
2010-07-01
... the inmate's confinement in a control unit; (b) Notice of the type of personal property which is... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Admission to control unit. 541.47 Section... INMATE DISCIPLINE AND SPECIAL HOUSING UNITS Control Unit Programs § 541.47 Admission to control...
Admission Control and Interference Management in Dynamic Spectrum Access Networks
Jorge Martinez-Bauset
2010-01-01
Full Text Available We study two important aspects to make dynamic spectrum access work in practice: the admission policy of secondary users (SUs to achieve a certain degree of quality of service and the management of the interference caused by SUs to primary users (PUs. In order to limit the forced termination probability of SUs, we evaluate the Fractional Guard Channel reservation scheme to give priority to spectrum handovers over new arrivals. We show that, contrary to what has been proposed, the throughput of SUs cannot be maximized by configuring the reservation parameter. We also study the interference caused by SUs to PUs. We propose and evaluate different mechanisms to reduce the interference, which are based on simple spectrum access algorithms for both PUs and SUs and channel repacking algorithms for SUs. Numerical results show that the reduction can be of one order of magnitude or more with respect to the random access case. Finally, we propose an adaptive admission control scheme that is able to limit simultaneously the forced termination probability of SUs and what we define as the probability of interference. Our scheme does not require any configuration parameters beyond the probability objectives. Besides, it is simple to implement and it can operate with any arrival process and distribution of the session duration.
A self-learning call admission control scheme for CDMA cellular networks.
Liu, Derong; Zhang, Yi; Zhang, Huaguang
2005-09-01
In the present paper, a call admission control scheme that can learn from the network environment and user behavior is developed for code division multiple access (CDMA) cellular networks that handle both voice and data services. The idea is built upon a novel learning control architecture with only a single module instead of two or three modules in adaptive critic designs (ACDs). The use of adaptive critic approach for call admission control in wireless cellular networks is new. The call admission controller can perform learning in real-time as well as in offline environments and the controller improves its performance as it gains more experience. Another important contribution in the present work is the choice of utility function for the present self-learning control approach which makes the present learning process much more efficient than existing learning control methods. The performance of our algorithm will be shown through computer simulation and compared with existing algorithms.
Intelligent Joint Admission Control for Next Generation Wireless Networks
Abdulqader M. Mohsen
2012-04-01
Full Text Available The Heterogeneous Wireless Network (HWN integrates different wireless networks into one common network. The integrated networks often overlap coverage in the same wireless service areas, leading to the availability of a great variety of innovative services based on user demands in a cost-efficient manner. Joint Admission Control (JAC handles all new or handoff service requests in the HWN. It checks whether the incoming service request to the selected Radio Access Network (RAN by the initial access network selection or the vertical handover module can be admitted and allocated the suitable resources. In this paper, a decision support system is developed to address the JAC problem in the modern HWN networks. This system combines fuzzy logic and the PROMETHEE II multiple criteria decision making system algorithm, to the problem of JAC. This combination decreases the influence of the dissimilar, imprecise, and contradictory measurements for the JAC criteria coming from different sources. A performance analysis is done and the results are compared with traditional algorithms for JAC. These results demonstrate a significant improvement with our developed algorithm.
Power Admission Control with Predictive Thermal Management in Smart Buildings
Yao, Jianguo; Costanzo, Giuseppe Tommaso; Zhu, Guchuan
2015-01-01
This paper presents a control scheme for thermal management in smart buildings based on predictive power admission control. This approach combines model predictive control with budget-schedulability analysis in order to reduce peak power consumption as well as ensure thermal comfort. First...
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.
Wu Naixing; Liao Jianxin; Zhu Xiaomin
2006-01-01
Based on the demand of the admission control of softswitch-based clustered media server, this paper proposed a new dynamic quota-based admission control algorithm that has a sub-negotiation process. The strongpoint of quota-based algorithm had been inherited in the algorithm and at the same time some new ideas had also been introduced into it. Simulations of the algorithm had been conducted on the Petri net model and the results show that this algorithm has excellent performance. In order to find the optimal resource quota setting in real time, the paper proposed two approximation analysis methods. It can be seen from analysis results that these two methods can be used to get sub-optimal quota values quickly and effectively. These two approximation analysis methods will play important roles in implementation of the algorithm in system.
Intelligent Joint Admission Control for Next Generation Wireless Networks
Mohsen, Abdulqader M.; Al-Akwaa, Fadhl M.; Mohammed M. Alkhawlani
2012-01-01
The Heterogeneous Wireless Network (HWN) integrates different wireless networks into one common network. The integrated networks often overlap coverage in the same wireless service areas, leading to the availability of a great variety of innovative services based on user demands in a cost-efficient manner. Joint Admission Control (JAC) handles all new or handoff service requests in the HWN. It checks whether the incoming service request to the selected Radio Access Network (RAN) by the initia...
Admission control with long-range dependence traffic input
RAO Yun-hua; ZOU Xue-cheng
2005-01-01
The admission control scheme is investigated for a FIFO self-similar queuing system with Quality of Service (QoS) performance guarantees. Since the self-similar queuing system performance analysis is often carried out under the condition of infinite buffer, it is difficult to deduce the upper boundary of buffer overflow probability. To overcome this shortcoming, a simple overflow condition is proposed, which defines a buffer overflow occurrence whenever the arrival rate exceeds the service rate. The analytic formula for the buffer overflow probability upper boundary is easily obtained under this condition. The required bandwidth upper boundary with long-range dependence input and determined overflow probability is then derived from this formula. Based on the above analytic formulas, the upper boundaries of the admission control regions for homogeneous and heterogeneous long-range dependence traffic sources are separately obtained. Finally, an effective admission control scheme for long-range dependence input is proposed. Simulation studies with real traffic have confirmed the validity of these results.
Routing and admission control in general topology networks with poisson arrivals
Kamath, A.; Palmon, O.; Plotkin, S. [Stanford Univ., CA (United States)
1996-12-31
Emerging high speed networks will carry traffic for services such as video-on-demand and video teleconferencing - that require resource reservation along the path on which the traffic is sent. High bandwidth-delay product of these networks prevents circuit rerouting, i.e. once it is routed on a certain path, the bandwidth a circuit taken by this circuit remains unavailable for the duration (holding time) of this circuit. As a result, such networks will need effective routing and admission control strategies. Recently developed online routing and admission control strategies have logarithmic competitive ratios with respect to the admission ratio (the fraction of admitted circuits). Such guarantees on performance are rather weak in the most interesting case where the rejection ratio of the optimum algorithm is very small or even 0. Unfortunately, these guarantees can not be improved in the context of the considered models, making it impossible to use these models to identify algorithms that are going to perform well in practice.
Vertical Handoff and Admission Control Strategy in 4G Wireless Network Using Centrality Graph Theory
A. Ferdinand Christopher
2014-06-01
Full Text Available Vertical Handoff (VHO is a crucial mechanism for the architecture of the Fourth Generation (4G Heterogeneous Wireless Networks (HWN, because the users of 4G-HWN are capable of switching to any network in a seamless manner. These algorithms need to be practical and true to a wide range of applications hence utilization of an application layer parameter is important to decide the handoff and admission control. As a noticeable number of OSN users increased among smart phones, this study proposes a deployment of social context incorporated with vertical handoff and admission control algorithms called VHO-AC for the 4G-HWN environment. Admission of a node is decided based on the Graph Centrality Theory, which is contributing their measures to design an application layer parameter called Social Centrality Measure (SCM. The simulation results show that social network traffic flowing out of 2G and 3G base stations is much reduced than the existing SCVH method.
New degradation call admission control for increasing WCDMA system capacity
Liu Ningqing; Lu Zhi; Gu Xuemai
2006-01-01
Propose a new degradation call admission control(DCAC)scheme, which can be used in wideband code division multiple access communication system. So-called degradation is that non-real time call has the characteristic of variable bit rate, so decreasing its bit rate can reduce the load of the system, consequently the system can admit new call which should be blocked when the system is close to full load, therefore new call's access probability increases. This paper brings forward design project and does system simulation, simulation proves that DCAC can effectively decrease calls' blocking probability and increase the total number of the on-line users.
Adaptive call admission control and resource allocation in multi server wireless/cellular network
Jain, Madhu; Mittal, Ragini
2016-11-01
The ever increasing demand of the subscribers has put pressure on the capacity of wireless networks around the world. To utilize the scare resources, in the present paper we propose an optimal allocation scheme for an integrated wireless/cellular model with handoff priority and handoff guarantee services. The suggested algorithm optimally allocates the resources in each cell and dynamically adjust threshold to control the admission. To give the priority to handoff calls over the new calls, the provision of guard channels and subrating scheme is taken into consideration. The handoff voice call may balk and renege from the system while waiting in the buffer. An iterative algorithm is implemented to generate the arrival rate of the handoff calls in each cell. Various performance indices are established in term of steady state probabilities. The sensitivity analysis has also been carried out to examine the tractability of algorithms and to explore the effects of system descriptors on the performance indices.
A Priority and SDB based Admission Control in IEEE 802.16 Systems
Xiu-ying Sun
2010-09-01
Full Text Available In IEEE 802.16 systems, the algorithm of admission control (AC is very important in guaranteeing the Quality of Service (QoS and managing service flows. However, the IEEE 802.16 standards do not specify any related strategies or algorithms on AC. In order to improve the system performance and satisfy the QoS of stations to the max, we propose a new AC strategy, which includes a weighted blocking rate based priority strategy and a satisfaction-degree based bandwidth-borrowing strategy named SDB in this paper. The simulation results show that the proposed strategy improves the overall performance of system in terms of weighted blocking rate. Furthermore, our strategy enhances the QoS in comparison with the strategy adopting conventional bandwidth-borrowing algorithm.
A QoS Provisioning Recurrent Neural Network based Call Admission Control for beyond 3G Networks
Ramesh Babu H. S.
2010-03-01
Full Text Available The Call admission control (CAC is one of the Radio Resource Management (RRM techniques that plays influential role in ensuring the desired Quality of Service (QoS to the users and applications in next generation networks. This paper proposes a fuzzy neural approach for making the call admission control decision in multi class traffic based Next Generation Wireless Networks (NGWN. The proposed Fuzzy Neural call admission control (FNCAC scheme is an integrated CAC module that combines the linguistic control capabilities of the fuzzy logic controller and the learning capabilities of the neural networks. The model is based on recurrent radial basis function networks which have better learning and adaptability that can be used to develop intelligent system to handle the incoming traffic in an heterogeneous network environment. The simulation results are optimistic and indicates that the proposed FNCAC algorithm performs better than the other two methods and the call blocking probability is minimal when compared to other two methods.
A QoS Provisioning Recurrent Neural Network based Call Admission Control for beyond 3G 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 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 compa...
Madhu Jain
2013-01-01
Full Text Available Wireless/mobile communication systems are becoming increasingly popular in recent years. As the wireless resources are scarce, it is important to allocate resources efficiently and carefully, in order to achieve maximum output. The call admission control schemes play a significant role in providing the desired quality of service (QoS by judiciously assigning the radio channels that are available in a micro cell. In this paper, we present two call admission control (CAC schemes for wireless mobile network, (i Prioritized call admission control (PCAC scheme (S1 and (ii Prioritized call admission control scheme with releasing function (S2. Both schemes support integrated traffic i.e. data and voice for both new and handoff attempts. Guard channel concept is used to give the priority to the handoff attempts. To admit more handoff attempts in the cellular system, buffering process is used for the handoff attempts. The concept of balking and reneging is also incorporated for both the schemes. The calls arrive in poisson fashion whereas channel holding time and cell residence times are exponentially distributed. The arrival rate of handoff attempts is computed by using iterative algorithm. Various performance metrics such as blocking probability of new call, blocking probability of handoff data/voice attempts, time out probability of handoff data/voice attempts, force termination probability of handoff data/voice attempts, waiting time of handoff data/voice attempts, carried load, etc. are determined. The sensitivity analysis has also been carried out to facilitate the insights of controllable parameters for real time systems
Adaptive Call Admission Control Based on Reward-Penalty Model in Wireless/Mobile Network
Jian-Hui Huang; De-Pei Qian; Sheng-Ling Wang
2007-01-01
A dynamic threshold-based Call Admission Control (CAC) scheme used in wireless/mobile network for multi- class services is proposed. In the scheme, each class's CAC thresholds are solved through establishing a reward-penalty model which strives to maximize network's revenue. In order to lower Handoff Dropping Probability (HDP), the scheme joints packet and connection levels Quality of Service constraints, designing a bandwidth degradation algorithm to accept handoff calls by degrading existing calls' bandwidth during network congestion. Analyses show that the CAC thresholds change adaptively with the average call arrival rate. The performance comparison shows that the proposed scheme outperforms the Mobile IP Reservation scheme.
Optimizing Voip Using A Cross Layer Call Admission Control Scheme
Mumtaz AL-Mukhtar
2013-07-01
Full Text Available Deployingwireless campus network becomes popular in many world universities for the services that areprovided.However, it suffers from different issues such as low VoIP network capacity, network congestioneffect on VoIP QoS and WLAN multi rate issue due to linkadaptation technique. In this paper a cross layercall admission control (CCAC scheme is proposed to reduce the effects of these problems on VoWLANbased on monitoring RTCPRR(RealTime Control Protocol ReceiverReportthat provides the QoS levelfor VoIP and monitoring the MAC layer for any change in the data rate. If the QoS level degrades due toone of the aforementioned reasons, a considerable change in the packet size or the codec type will be thesolution. A wireless campus network issimulatedusing OPNET 14.5 modeler and many scenarios aremodeled to improve this proposed scheme.
Granja, C; Almada-Lobo, B; Janela, F; Seabra, J; Mendes, A
2014-12-01
As patient's length of stay in waiting lists increases, governments are looking for strategies to control the problem. Agreements were created with private providers to diminish the workload in the public sector. However, the growth of the private sector is not following the demand for care. Given this context, new management strategies have to be considered in order to minimize patient length of stay in waiting lists while reducing the costs and increasing (or at least maintaining) the quality of care. Appointment scheduling systems are today known to be proficient in the optimization of health care services. Their utilization is focused on increasing the usage of human resources, medical equipment and reducing the patient waiting times. In this paper, a simulation-based optimization approach to the Patient Admission Scheduling Problem is presented. Modeling tools and simulation techniques are used in the optimization of a diagnostic imaging department. The proposed techniques have demonstrated to be effective in the evaluation of diagnostic imaging workflows. A simulated annealing algorithm was used to optimize the patient admission sequence towards minimizing the total completion and total waiting of patients. The obtained results showed average reductions of 5% on the total completion and 38% on the patients' total waiting time. Copyright © 2014 Elsevier Inc. All rights reserved.
Lin, Di; Labeau, Fabrice; Yao, Yuanzhe; Vasilakos, Athanasios V; Tang, Yu
2016-07-01
Wireless technologies and vehicle-mounted or wearable medical sensors are pervasive to support ubiquitous healthcare applications. However, a critical issue of using wireless communications under a healthcare scenario rests at the electromagnetic interference (EMI) caused by radio frequency transmission. A high level of EMI may lead to a critical malfunction of medical sensors, and in such a scenario, a few users who are not transmitting emergency data could be required to reduce their transmit power or even temporarily disconnect from the network in order to guarantee the normal operation of medical sensors as well as the transmission of emergency data. In this paper, we propose a joint power and admission control algorithm to schedule the users' transmission of medical data. The objective of this algorithm is to minimize the number of users who are forced to disconnect from the network while keeping the EMI on medical sensors at an acceptable level. We show that a fixed point of proposed algorithm always exists, and at the fixed point, our proposed algorithm can minimize the number of low-priority users who are required to disconnect from the network. Numerical results illustrate that the proposed algorithm can achieve robust performance against the variations of mobile hospital environments.
Warfarin Management Pathway: A clear and safe algorithm, from admission to discharge.
Hart-George, Alice
2014-01-01
Warfarin is the most commonly prescribed anticoagulant in the UK and the one most frequently associated with both fatal medication errors and litigation claims [1]. Its life-threatening interactions and side effects are a concern for all doctors. Identifying and implementing solutions to achieve safer prescribing and monitoring is imperative to improve patient safety. The National Patient Safety Agency (NPSA) has outlined the major risks associated with anticoagulant therapy and sought to establish safer practice [1]. The monitoring of safety indicators has been highlighted as a solution. This quality improvement project (QIP) introduces a management algorithm for oral anticoagulant therapy in hospital patients, validated through a completed audit cycle. It was completed at one district general hospital (DGH) in England and involved all inpatient wards. Doctors and pharmacists were interviewed to assess their knowledge of the correct pathways for management of patients on warfarin. The number of errors on hospital warfarin charts was audited over three weeks. These results, coupled with senior haematological advice led to the production of an algorithm illustrating the gold-standard pathway for warfarin management from admission to discharge. It was emailed to all doctors in the Trust and a laminated copy attached to hospital Pneumatic Tube System (PTS) machines. The warfarin charts were re-audited over the following three weeks. The results showed a marked decrease in errors and incomplete anticoagulation referrals as well as a reduction in doctors' anxiety around prescribing warfarin.
Call Admission Control performance model for Beyond 3G Wireless Networks
Ramesh Babu H.S
2009-12-01
Full Text Available 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 wireless network environment. In the proposed algorithm we have considered three classes of traffic having different QoS requirements and we have considered the heterogeneous network environment which includes the RATs that can effectively handle applications like voice calls, Web browsing and file transfer applications which are with varied QoS parameters. The paper presents the call blocking probabilities for all the three types of traffic both for fixed and varied traffic scenario.Keywords: Radio Access Technologies; Call admission control; Call blocking probability; Markov model; Heterogeneous wireless Networks.
Combined Admission Control and Scheduling for QoS Differentiation in LTE Uplink
Anas, Mohmmad; Rosa, Claudio; Calabrese, Francesco Davide
2008-01-01
Long term evolution (LTE) architecture shall support end-to-end quality of service (QoS). For the QoS support and service differentiation it is important that the admission control and packet scheduling functionalities are QoS-aware. In this paper a combined admission control and a decoupled time...
Joint Resource Allocation and Admission Control Mechanism for an OFDMA-Based System
Meucci, Filippo; Mihovska, Albena D.; Anggorojati, Bayu;
2008-01-01
This paper describes a Call Admission Control (CAC) mechanism that adapts the type of admitted users based on a proposed resource allocation strategy that responds to changes in the channel conditions. The admission control decides to admit new services according to the load of the cell and based...
QoS awared power and admission controls based on non-cooperative game theory in wireless networks
2008-01-01
In order to better accommodate heterogeneous quality of service (QoS) in wireless networks, an algorithm called QeS-aware power and admission controls (QAPAC) is proposed. The system is modeled as u non- cooperative game where the users adjust their transmit powers to maximize the utility, thus restraining the interferences. By using adaptive utility functions and tunable pricing parameters according to QoS levels, this algorithm can well meet different QoS reqniremcnts and improve system capacity compared with those that ignore the QoS differ- ences.
QoS awared power and admission controls based on non-cooperative game theory in wireless networks
无
2008-01-01
In order to better accommodate heterogeneous quality of service (QoS) in wireless networks, an algorithm called QoS-aware power and admission controls (QAPAC) is proposed. The system is modeled as a non-cooperative game where the users adjust their transmit powers to maximize the utility, thus restraining the interferences. By using adaptive utility functions and tunable pricing parameters according to QoS levels, this algorithm can well meet different QoS requirements and improve system capacity compared w...
Subcubic Control Flow Analysis Algorithms
Midtgaard, Jan; Van Horn, David
We give the first direct subcubic algorithm for performing control flow analysis of higher-order functional programs. Despite the long held belief that inclusion-based flow analysis could not surpass the ``cubic bottleneck, '' we apply known set compression techniques to obtain an algorithm...... that runs in time O(n^3/log n) on a unit cost random-access memory model machine. Moreover, we refine the initial flow analysis into two more precise analyses incorporating notions of reachability. We give subcubic algorithms for these more precise analyses and relate them to an existing analysis from...
Voice Communications over 802.11 Ad Hoc Networks: Modeling, Optimization and Call Admission Control
Xu, Changchun; Xu, Yanyi; Liu, Gan; Liu, Kezhong
Supporting quality-of-service (QoS) of multimedia communications over IEEE 802.11 based ad hoc networks is a challenging task. This paper develops a simple 3-D Markov chain model for queuing analysis of IEEE 802.11 MAC layer. The model is applied for performance analysis of voice communications over IEEE 802.11 single-hop ad hoc networks. By using the model, we finish the performance optimization of IEEE MAC layer and obtain the maximum number of voice calls in IEEE 802.11 ad hoc networks as well as the statistical performance bounds. Furthermore, we design a fully distributed call admission control (CAC) algorithm which can provide strict statistical QoS guarantee for voice communications over IEEE 802.11 ad hoc networks. Extensive simulations indicate the accuracy of the analytical model and the CAC scheme.
An Interference-Aware Admission Control Design for Wireless Mesh Networks
Manikantan Shila Devu
2010-01-01
Full Text Available In this paper, we present IAC, an interference aware admission control algorithm for use in wireless mesh networks. The core concept of IAC is to use a low overhead dual threshold based approach to share the bandwidth information with its neighbors in the interfering range. As a result, IAC guarantees that the shared wireless bandwidth is not overutilized and the quality of all existing flows are preserved. Moreover, IAC takes into account the intraflow interference effect to estimate the bandwidth consumption of the flow in a multihop path. We have further proposed two approaches of bandwidth allocation, FCFS and MCU, and demonstrated that proper tuning of thresholds can lead to high performance of both schemes. Simulation results illustrate that IAC effectively limits the overutilization of channel resources which in turn results in high throughput, low delay and low packet loss rate for all admitted flows.
A Survey of PCN-Based Admission Control and Flow Termination
Menth, Michael; Lehrieder, Frank; Briscoe, Bob; Eardley, Philip; Moncaster, Tony; Babiarz, Jozef; Charny, Anna; Zhang, Xinyang (Joy); Taylor, Tom; Chan, Kwok-Ho; Satoh, Daisuke; Geib, Ruediger; Karagiannis, Georgios
2010-01-01
Pre-congestion notification (PCN) provides feedback about load conditions in a network to its boundary nodes. The PCN working group of the IETF discusses the use of PCN to implement admission control (AC) and flow termination (FT) for prioritized realtime traffic in a DiffServ domain. Admission cont
A Survey of PCN-Based Admission Control and Flow Termination
Menth, Michael; Lehrieder, Frank; Briscoe, Bob; Eardley, Philip; Moncaster, Tony; Babiarz, Jozef; Charny, Anna; Zhang, Xinyang (Joy); Taylor, Tom; Chan, Kwok-Ho; Satoh, Daisuke; Geib, Ruediger; Karagiannis, Georgios
2010-01-01
Pre-congestion notification (PCN) provides feedback about load conditions in a network to its boundary nodes. The PCN working group of the IETF discusses the use of PCN to implement admission control (AC) and flow termination (FT) for prioritized realtime traffic in a DiffServ domain. Admission cont
Adaptive-feedback control algorithm.
Huang, Debin
2006-06-01
This paper is motivated by giving the detailed proofs and some interesting remarks on the results the author obtained in a series of papers [Phys. Rev. Lett. 93, 214101 (2004); Phys. Rev. E 71, 037203 (2005); 69, 067201 (2004)], where an adaptive-feedback algorithm was proposed to effectively stabilize and synchronize chaotic systems. This note proves in detail the strictness of this algorithm from the viewpoint of mathematics, and gives some interesting remarks for its potential applications to chaos control & synchronization. In addition, a significant comment on synchronization-based parameter estimation is given, which shows some techniques proposed in literature less strict and ineffective in some cases.
A Novel Effective Bandwidth Based Call Admission Control for Multimedia CDMA Systems
PAN Su; FENG Guang-zheng; ZHU Qi
2004-01-01
A novel Call Admission Control (CAC) scheme is proposed for multimedia CDMA systems. The effective bandwidth of real time calls is reserved in the CAC with the consideration of active factors. The admission of non-real time calls is controlled by the system according to the residual effective bandwidth left from real time calls. Simulation results have shown that the novel CAC has greatly enlarged the admission region for real time calls and make the transmission delay of non-real time calls under an acceptable level.
Location-based admission control for differentiated services in 3G cellular networks
Núñez-Queija, R.; Tan, H.-P.
2006-01-01
Third generation wireless systems can simultaneously accommodate flow transmissions of users with widely heterogeneous applications. As resources are limited (particularly in the air interface), admission control is necessary to ensure that all active users are accommodated with sufficient capacity
Patient-controlled hospital admission for patients with severe mental disorders
Thomsen, Christoffer Torgaard; Benros, Michael Eriksen; Hastrup, Lene Halling
2016-01-01
studies assessing the outcomes of patient-controlled hospital admission found trends towards reduction in the use of coercive measures and length of hospital stay; however, these studies have methodological shortcomings and small sample sizes. Larger studies are needed to estimate the effect of patient-controlled......INTRODUCTION: Patient-controlled hospital admission for individuals with severe mental disorders is a novel approach in mental healthcare. Patients can admit themselves to a hospital unit for a short stay without being assessed by a psychiatrist or contacting the emergency department. Previous...... hospital admission on the use of coercion and of healthcare services. DESIGN AND METHODS: We aim to recruit at least 315 patients who are offered a contract for patient-controlled hospital admissions in eight different hospitals in Denmark. Patients will be followed-up for at least 1 year to compare...
Huang, Qian; Huang, Yue-Cai; Ko, King-Tim;
2011-01-01
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...
Multi-Stage Admission Control for Load Balancing in Next Generation Systems
Mihovska, Albena D.; Anggorojati, Bayu; Luo, Jijun;
2008-01-01
This paper describes a load-dependent multi-stage admission control suitable for next generation systems. The concept uses decision polling in entities located at different levels of the architecture hierarchy and based on the load to activate a sequence of actions related to the admission...... of a 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...... load. Each admission request will issue a flag whose colour will reflect the load level in this entity and will determine the correct sequence of the required admission control actions....
Evolutionary algorithms for hard quantum control
Zahedinejad, Ehsan; Schirmer, Sophie; Sanders, Barry C.
2014-09-01
Although quantum control typically relies on greedy (local) optimization, traps (irregular critical points) in the control landscape can make optimization hard by foiling local search strategies. We demonstrate the failure of greedy algorithms as well as the (nongreedy) genetic-algorithm method to realize two fast quantum computing gates: a qutrit phase gate and a controlled-not gate. We show that our evolutionary algorithm circumvents the trap to deliver effective quantum control in both instances. Even when greedy algorithms succeed, our evolutionary algorithm can deliver a superior control procedure, for example, reducing the need for high time resolution.
SERVICE-AWARE BASED FUZZY ADMISSION CONTROL SCHEME IN MULTI-SERVICE NETWORKS
Qiu Gongan; Zhang Shunyi; Liu Shidong
2007-01-01
Multi-service aggregated transmission is the direction of IP network. Providing different Quality of Service (QoS) assurance for different services has become a crucial problem in future network.Admission control is a vital function for multi-service IP network. This paper proposes a novel fuzzy admission control scheme based on coarse granularity service-aware technique. Different service has discriminative sensitivity to the same QoS characteristic parameter in general. The traffic class can be perceived by the service request parameter and the proposed QoS function. And requirements of different applications can be met by maintaining the life parameter. From simulation results, the proposed scheme shows a better QoS provisioning than those traditional fuzzy logic based methods under the same admission probability.
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.
Salman Ali AlQahtani
2017-01-01
In this paper, we introduce the user’s privileges and traffic maximum delay tolerance as additional dimensions in the call admission control processes to efficiently control the utilization of LTE-A network resources. Based on this idea, we propose an efficient call admission control scheme named “delay aware and user categorizing-based CAC with adaptive resource reservation (DA–UC-ARR”, where the user priority is adjusted dynamically based on the current network conditions and the users’ categorizations and traffic delay tolerances, to increase the network’s resource utilization and at the same time to maximize the operators’ revenue. In this proposed scheme, the users are classified into Golden users and Silver users, and the type of service per user is classified as real time (RT and non-real time (NRT services. We compare the performance of the proposed scheme with the corresponding results of previous schemes, referred to as the adaptive resource reservation-based call admission control (ARR-CAC (Andrews et al., 2010; AlQahtani, 2014, where user categorization and delay were not taken into consideration in the call admission control process. Simulation results indicate the superiority of the proposed scheme because it is able to achieve a better balance between system utilization, users’ privileges provided by network operators and QoS provisioning compared to the ARR-CAC scheme.
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…
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.
Fast Algorithm of Multivariable Generalized Predictive Control
Jin,Yuanyu; Pang,Zhonghua; Cui,Hong
2005-01-01
To avoid the shortcoming of the traditional (previous)generalized predictive control (GPC) algorithms, too large amounts of computation, a fast algorithm of multivariable generalized predictive control is presented in which only the current control actions are computed exactly on line and the rest (the future control actions) are approximately done off line. The algorithm is simple and can be used in the arbitary-dimension input arbitary-dimension output (ADIADO) linear systems. Because it dose not need solving Diophantine equation and reduces the dimension of the inverse matrix, it decreases largely the computational burden. Finally, simulation results show that the presented algorithm is effective and practicable.
HUMAN-SIMULATING VEHICLE STEERING CONTROL ALGORITHM
XU Youchun; LI Keqiang; CHANG Ming; CHEN Jun
2006-01-01
A new vehicle steering control algorithm is presented. Unlike the traditional methods do,the algorithm uses a sigmoid function to describe the principle of the human driver's steering strategy.Based on this function, a human simulating vehicle steering model, human-simulating steering control(HS) algorithm is designed. In order to improve the adaptability to different environments, a parameter adaptive adjustment algorithm is presented. This algorithm can online modify the value of the key parameters of the HS real time. HS controller is used on a vehicle equipped with computer vision system and computer controlled steering actuator system, the result from the automatic vehicle steering experiment shows that the HS algorithm gives good performance at different speed, even at the maximum speed of 172 km/h.
Phan, V. V. (Vinh V.)
2005-01-01
Abstract Efficient management of rather limited resources, including radio spectrum and mobile-terminal battery power, has been the fundamental design challenge of wireless networks and one of the most widespread research problems over the years. MAC (Medium Access Control) for packet access and CAC (Call Admission Control) for connection-oriented service domains are commonly used as effective tools to manage radio resources, capacity and performance of wireless networks while providing ad...
Li Pan
2016-03-01
Full Text Available Virtualization technologies make it possible for cloud providers to consolidate multiple IaaS provisions into a single server in the form of virtual machines (VMs. Additionally, in order to fulfill the divergent service requirements from multiple users, a cloud provider needs to offer several types of VM instances, which are associated with varying configurations and performance, as well as different prices. In such a heterogeneous virtual machine placement process, one significant problem faced by a cloud provider is how to optimally accept and place multiple VM service requests into its cloud data centers to achieve revenue maximization. To address this issue, in this paper, we first formulate such a revenue maximization problem during VM admission control as a multiple-dimensional knapsack problem, which is known to be NP-hard to solve. Then, we propose to use a cross-entropy-based optimization approach to address this revenue maximization problem, by obtaining a near-optimal eligible set for the provider to accept into its data centers, from the waiting VM service requests in the system. Finally, through extensive experiments and measurements in a simulated environment with the settings of VM instance classes derived from real-world cloud systems, we show that our proposed cross-entropy-based admission control optimization algorithm is efficient and effective in maximizing cloud providers’ revenue in a public cloud computing environment.
Gao Ke-Ke
2016-01-01
Full Text Available Full three-dimensional unsteady numerical investigation on an axial air turbine in 50% partial admission is conducted. The partial admission turbines are under different unsteady loading and unloading process, as well as flow parameters, respectively. The loss coefficient and static pressure distributions at the key position are presented in detail to analyze the nonuniformity originated from partial admission. The results show that the nonuniformity decreases along flow direction and the efficiency of control stage also decreases but with the uniformity improved downstream of the rotors with increasing admitting numbers in equal partial admission degree. The reasons for efficiency decreasing are reasonably explained with windage and sector end losses presented by static entropy distributions. The periodic changes of unsteady forces in amplitude and direction are also compared and transformed in the frequency domain by FFT method. The largest circumferential exciting force factor which is remarkably larger than the corresponding axial exciting force factor decreases by 13.2% with the increase of admitting arc number. Compared with the common distribution of two symmetric admitting arcs, the maximum exciting force factor of triangle admitting arc distribution drops 11.3% with the mere efficiency decrease of 1.32%. The multiple admitting arc turbines are more conducive to be applied to submarines which concerns more about exciting force other than efficiency. Efficiency and unsteady forces are both worth being taken into consideration in the practical applications.
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%.
da Costa, David W; Bouwense, Stefan A; Schepers, Nicolien J; Besselink, Marc G; van Santvoort, Hjalmar C; van Brunschot, Sandra; Bakker, Olaf J; Bollen, Thomas L; Dejong, Cornelis H; van Goor, Harry; Boermeester, Marja A; Bruno, Marco J; van Eijck, Casper H; Timmer, Robin; Weusten, Bas L; Consten, Esther C; Brink, Menno A; Spanier, B W Marcel; Bilgen, Ernst Jan Spillenaar; Nieuwenhuijs, Vincent B; Hofker, H Sijbrand; Rosman, Camiel; Voorburg, Annet M; Bosscha, Koop; van Duijvendijk, Peter; Gerritsen, Jos J; Heisterkamp, Joos; de Hingh, Ignace H; Witteman, Ben J; Kruyt, Philip M; Scheepers, Joris J; Molenaar, I Quintus; Schaapherder, Alexander F; Manusama, Eric R; van der Waaij, Laurens A; van Unen, Jacco; Dijkgraaf, Marcel G; van Ramshorst, Bert; Gooszen, Hein G; Boerma, Djamila
2015-09-26
In patients with mild gallstone pancreatitis, cholecystectomy during the same hospital admission might reduce the risk of recurrent gallstone-related complications, compared with the more commonly used strategy of interval cholecystectomy. However, evidence to support same-admission cholecystectomy is poor, and concerns exist about an increased risk of cholecystectomy-related complications with this approach. In this study, we aimed to compare same-admission and interval cholecystectomy, with the hypothesis that same-admission cholecystectomy would reduce the risk of recurrent gallstone-related complications without increasing the difficulty of surgery. For this multicentre, parallel-group, assessor-masked, randomised controlled superiority trial, inpatients recovering from mild gallstone pancreatitis at 23 hospitals in the Netherlands (with hospital discharge foreseen within 48 h) were assessed for eligibility. Adult patients (aged ≥18 years) were eligible for randomisation if they had a serum C-reactive protein concentration less than 100 mg/L, no need for opioid analgesics, and could tolerate a normal oral diet. Patients with American Society of Anesthesiologists (ASA) class III physical status who were older than 75 years of age, all ASA class IV patients, those with chronic pancreatitis, and those with ongoing alcohol misuse were excluded. A central study coordinator randomly assigned eligible patients (1:1) by computer-based randomisation, with varying block sizes of two and four patients, to cholecystectomy within 3 days of randomisation (same-admission cholecystectomy) or to discharge and cholecystectomy 25-30 days after randomisation (interval cholecystectomy). Randomisation was stratified by centre and by whether or not endoscopic sphincterotomy had been done. Neither investigators nor participants were masked to group assignment. The primary endpoint was a composite of readmission for recurrent gallstone-related complications (pancreatitis, cholangitis
A NOVEL CALL ADMISSION CONTROL SCHEME IN CELLULAR/WLAN INTEGRATION AND PERFORMANCE ANALYSIS
Xia Weiwei; Shen Lianfeng
2009-01-01
In order to achieve the Quality of Service (QoS) provisioning and efficient resource utilization in cellular network and Wireless Local Area Network (WLAN) integration, an Integrated Service-Based Call Admission Control (ISB-CAC) scheme is proposed in this paper. The integrated network is modeled by using multi-dimensional Markov chains. The numerical analysis is presented to evaluate the important performance measures such as the blocking probability of originating calls, the dropping probability, and the average transfer time, etc. The steady-state probabilities of the multi-dimensional Markov chains are obtained by using an iterative approach, and the CAC parameters are optimally designed. The analytical model is validated by the computer simulation. It is shown that compared with the conventional WLAN-First Call Admission Control (WF-CAC) scheme, the proposed ISB-CAC scheme not only provides better QoS for mobile users but also utilizes the bandwidth resources more efficiently.
Figuring Control in the Algorithmic Era
Markham, Annette; Bossen, Claus
in particular situations. These are intended as figurations that can help us think through various working patterns of control, including beliefs about control, affective elements of control, enactments of control through specific code operations such as algorithms, making sense of perceived or actual loss...
Intelligent control algorithm for ship dynamic positioning
Meng Wang
2014-12-01
Full Text Available Ship motion in the sea is a complex nonlinear kinematics. The hydrodynamic coefficients of ship model are very difficult to accurately determine. Establishing accurate mathematical model of ship motion is difficult because of changing random factors in the marine environment. Aiming at seeking a method of control to realize ship positioning, intelligent control algorithms are adopt utilizing operator's experience. Fuzzy controller and the neural network controller are respectively designed. Through simulations and experiments, intelligent control algorithm can deal with the complex nonlinear motion, and has good robustness. The ship dynamic positioning system with neural network control has high positioning accuracy and performance.
TFRC—IVS Flow Control Algorithm
HEKaijian; LINYaping; YANGAng
2003-01-01
This paper investigates the TCP (Trans-mission Control Protocol) friendliness of multicast video-conferencing systems. Through the analysis and simulation experiments it is shown that the slow response to network state changes and the fixed rate adjustment process lead to TCP unfriendliness in the bandwidth sharing. Therefore,this paper proposes a new TCP friendly flow control al-gorithm called TFRC-IVS flow control algorithm for the current best-effort Internet. TFRC-IVS (TCP-Friendly Rate Control--INRIA Videoconferencing System) algo-rithm utilizes TCP friendly control function derived from complex TCP model to calculate TCP friendly sending rate.Simulation results show that TFRC-IVS flow control algorithm improves the smoothness of transmission rates and converges quickly to the stable sending rate. In addi-tion, the TCP friendly control function in TFRC-IVS flow control algorithm ensures the TCP friendliness of video flows and fair bandwidth allocation with TCP flows, which the traditional static rate adjustment algorithm lacks.
Quadratic Stabilization of LPV System by an LTI Controller Based on ILMI Algorithm
Wei Xie
2007-01-01
Full Text Available A linear time-invariant (LTI output feedback controller is designed for a linear parameter-varying (LPV control system to achieve quadratic stability. The LPV system includes immeasurable dependent parameters that are assumed to vary in a polytopic space. To solve this control problem, a heuristic algorithm is proposed in the form of an iterative linear matrix inequality (ILMI formulation. Furthermore, an effective method of setting an initial value of the ILMI algorithm is also proposed to increase the probability of getting an admissible solution for the controller design problem.
Decisive Routing and Admission Control According to Quality of Service Constraints
2009-03-01
in pn sn1 tn1 sn2 tn2 sny tny ⎞ ⎟⎟⎟⎟⎟⎟⎠ Where the each row in the matrix corresponds to the following i1...n = input file size of...Preemptive Congestion Control Code Snippet The Decisive Routing and Admission Control According to Quality of Service Constraints code snippet of reaction to...simulation snippet of reaction to forecasted state of the network. The Kalman filter queue has reached a stated level of 45% of its capacity and
Pinning impulsive control algorithms for complex network.
Sun, Wen; Lü, Jinhu; Chen, Shihua; Yu, Xinghuo
2014-03-01
In this paper, we further investigate the synchronization of complex dynamical network via pinning control in which a selection of nodes are controlled at discrete times. Different from most existing work, the pinning control algorithms utilize only the impulsive signals at discrete time instants, which may greatly improve the communication channel efficiency and reduce control cost. Two classes of algorithms are designed, one for strongly connected complex network and another for non-strongly connected complex network. It is suggested that in the strongly connected network with suitable coupling strength, a single controller at any one of the network's nodes can always pin the network to its homogeneous solution. In the non-strongly connected case, the location and minimum number of nodes needed to pin the network are determined by the Frobenius normal form of the coupling matrix. In addition, the coupling matrix is not necessarily symmetric or irreducible. Illustrative examples are then given to validate the proposed pinning impulsive control algorithms.
Congestion Control Algorithm for Resilient Packet Ring
孔红伟; 葛宁; 阮方; 冯重熙
2003-01-01
A congestion control algorithm is proposed for resilient packet ring (RPR) in this paper. In thisalgorithm, nonlinear explicit rate feedback control is used to ensure fast convergence and smooth equilibriumbehavior. The algorithm combines explicit rate control with a deficit round robin (DRR) scheduler, which notonly ensures fairness, but also avoids the implementation difficulties of explicit rate control algorithms. Thealgorithm has good features of fairness, fast convergence, smooth equilibrium, Iow queue depth, and easyimplementation. It is insensitive to the loss of congestion control packets and can adapt to a wide range of linkrates and network scales. It has solved the unbalanced traffic problem of spatial reuse protocol (SRP). Thealgorithm can be implemented on the multi-access control layer of RPR nodes to ensure fair and efficient accessof the best-effort traffic.
Control algorithms for autonomous robot navigation
Jorgensen, C.C.
1985-09-20
This paper examines control algorithm requirements for autonomous robot navigation outside laboratory environments. Three aspects of navigation are considered: navigation control in explored terrain, environment interactions with robot sensors, and navigation control in unanticipated situations. Major navigation methods are presented and relevance of traditional human learning theory is discussed. A new navigation technique linking graph theory and incidental learning is introduced.
Model based development of engine control algorithms
Dekker, H.J.; Sturm, W.L.
1996-01-01
Model based development of engine control systems has several advantages. The development time and costs are strongly reduced because much of the development and optimization work is carried out by simulating both engine and control system. After optimizing the control algorithm it can be executed b
Effect of air pollution control on mortality and hospital admissions in Ireland.
Dockery, Douglas W; Rich, David Q; Goodman, Patrick G; Clancy, Luke; Ohman-Strickland, Pamela; George, Prethibha; Kotlov, Tania
2013-07-01
and 1998 bans, adjusting for influenza epidemics, weekly mean temperature, and local admissions for digestive diagnoses. Mean BS concentrations fell in all affected population centers post-ban compared with the pre-ban period, with decreases ranging from 4 to 35 microg/m3 (corresponding to reductions of 45% to 70%, respectively), but we observed no clear pattern in SO2 measured as total gaseous acidity associated with the bans. In comparisons with the pre-ban periods, no significant reduction was found in total death rates associated with the 1990 (1% reduction), 1995 (4% reduction), or 1998 (0% reduction) bans, nor for cardiovascular mortality (0%, 4%, and 1% reductions for the 1990, 1995, and 1998 bans, respectively). Respiratory mortality was reduced in association with the bans (17%, 9%, and 3%, respectively). We found a 4% decrease in hospital admissions for cardiovascular disease associated with the 1995 ban and a 3% decrease with the 1998 ban. Admissions for respiratory disease were not consistently lower after the bans; admissions for pneumonia, chronic obstructive pulmonary disease (COPD), and asthma were reduced. However, underreporting of hospital admissions data and lack of control and comparison series tempered our confidence in these results. The successive coal bans resulted in immediate and sustained decreases in particulate concentrations in each city or town; with the largest decreases in winter and during the heating season. The bans were associated with reductions in respiratory mortality but no detectable improvement in cardiovascular mortality. The changes in hospital admissions for respiratory and cardiovascular disease were supportive of these findings but cannot be considered confirming. Detecting changes in public health indicators associated even with clear improvements in air quality, as in this case, remains difficult when there are simultaneous secular improvements in the same health indicators.
Admission Control Scheme for Multi-class Services in QoS-based Mobile Cellular Networks
YINZhiming; XIEJianying
2004-01-01
Call admission control (CAC) is one of the key schemes to guarantee Quality of service (QoS) in mobile cellular networks. In this paper, we propose an optimal CAC scheme based on Semi-Markov decision processes (SMDP) theory to support multi-class services for QoS wireless networks. Linear programming formulation is used to find the optimal solution, which maximizes the channel utilization while meeting the requirements of QoS constraints. The numerical results show that the performance of our scheme outperforms DCAC scheme.
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.
Singular formalism and admissible control of spacecraft with rotating flexible solar array
Lu Dongning
2014-02-01
Full Text Available This paper is concerned with the attitude control of a three-axis-stabilized spacecraft which consists of a central rigid body and a flexible sun-tracking solar array driven by a solar array drive assembly. Based on the linearization of the dynamics of the spacecraft and the modal identities about the flexible and rigid coupling matrices, the spacecraft attitude dynamics is reduced to a formally singular system with periodically varying parameters, which is quite different from a spacecraft with fixed appendages. In the framework of the singular control theory, the regularity and impulse-freeness of the singular system is analyzed and then admissible attitude controllers are designed by Lyapunov’s method. To improve the robustness against system uncertainties, an H∞ optimal control is designed by optimizing the H∞ norm of the system transfer function matrix. Comparative numerical experiments are performed to verify the theoretical results.
Singular formalism and admissible control of spacecraft with rotating flexible solar array
Lu Dongning; Liu Yiwu
2014-01-01
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 identi-ties 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 space-craft 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 H1 optimal control is designed by optimizing the H1 norm of the system transfer function matrix. Comparative numerical experiments are performed to verify the theoretical results.
Approximation algorithms for planning and control
Boddy, Mark; Dean, Thomas
1989-01-01
A control system operating in a complex environment will encounter a variety of different situations, with varying amounts of time available to respond to critical events. Ideally, such a control system will do the best possible with the time available. In other words, its responses should approximate those that would result from having unlimited time for computation, where the degree of the approximation depends on the amount of time it actually has. There exist approximation algorithms for a wide variety of problems. Unfortunately, the solution to any reasonably complex control problem will require solving several computationally intensive problems. Algorithms for successive approximation are a subclass of the class of anytime algorithms, algorithms that return answers for any amount of computation time, where the answers improve as more time is allotted. An architecture is described for allocating computation time to a set of anytime algorithms, based on expectations regarding the value of the answers they return. The architecture described is quite general, producing optimal schedules for a set of algorithms under widely varying conditions.
Design tool for wind turbine control algorithms
Van der Hooft, E.L.; Van Engelen, T.G.; Schaak, P.; Wiggelinkhuizen, E.J. [ECN Wind Energy, Petten (Netherlands)
2004-11-01
Advanced wind turbine control algorithms have become more important over the last years in order to deal with high requirements on reliability, cost of energy and extreme operating (offshore) conditions. An open source modular 'Design tool for wind turbine control algorithms' within the Matlab environment enables possibilities for wind turbine designers to develop industrial control algorithms and to utilize the benefits of more advanced control solutions. The design tool offers a proven design procedure, which takes the different design stages of a wind turbine into account. It supports initial design and evaluation of control algorithms, linking to aero-elastic codes and implementation in the turbine controller. In addition, the tool assists the designer to operate the design procedure, to avoid design failures and ordering of all the design data, models and versions. Currently, the incorporated design and evaluation models are focussed on design of classic 'rotor speed feedback control' for a variable speed and active pitch turbine and have been verified in practice. More advanced control design modules are within reach as a result of current developments on frequency domain analysis and synthesis of (linearised) turbine models.
Efficient evolutionary algorithms for optimal control
López Cruz, I.L.
2002-01-01
If optimal control problems are solved by means of gradient based local search methods, convergence to local solutions is likely. Recently, there has been an increasing interest in the use of global optimisation algorithms to solve optimal control problems, wh
Costa, D.W. da; Bouwense, S.A.; Schepers, N.J.; Besselink, M.G.; Santvoort, H.C. van; Brunschot, S. van; Bakker, O.J.; Bollen, T.L.; Dejong, C.H.; Goor, H. van; Boermeester, M.A.; Bruno, M.J.; Eijck, C.H. van; Timmer, R.; Weusten, B.L.; Consten, E.C.; Brink, M.A.; Spanier, B.W.; Bilgen, E.J.; Nieuwenhuijs, V.B.; Hofker, H.S.; Rosman, C.; Voorburg, A.M.; Bosscha, K.; Duijvendijk, P. van; Gerritsen, J.J.; Heisterkamp, J.; Hingh, I.H. de; Witteman, B.J.; Kruyt, P.M.; Scheepers, J.J.; Molenaar, I.Q.; Schaapherder, A.F.; Manusama, E.R.; Waaij, L.A. van der; Unen, J. van; Dijkgraaf, M.G.; Ramshorst, B. van; Gooszen, H.G.; Boerma, D.
2015-01-01
BACKGROUND: In patients with mild gallstone pancreatitis, cholecystectomy during the same hospital admission might reduce the risk of recurrent gallstone-related complications, compared with the more commonly used strategy of interval cholecystectomy. However, evidence to support same-admission
Da Costa, David W.; Bouwense, Stefan A.; Schepers, Nicolien J.; Besselink, Marc G.; van Santvoort, Hjalmar C.|info:eu-repo/dai/nl/304821721; Van Brunschot, Sandra; Bakker, Olaf J.|info:eu-repo/dai/nl/314099050; Bollen, Thomas L.; Dejong, Cornelis H.; Van Goor, Harry; Boermeester, Marja A.; Bruno, Marco J.; Van Eijck, Casper H.; Timmer, Robin; Weusten, Bas L.; Consten, Esther C.; Brink, Menno A.; Spanier, B. W Marcel; Bilgen, Ernst Jan Spillenaar; Nieuwenhuijs, Vincent B.; Hofker, H. Sijbrand; Rosman, Camiel; Voorburg, Annet M.; Bosscha, Koop; Van Duijvendijk, Peter; Gerritsen, Jos J.; Heisterkamp, Joos; De Hingh, Ignace H.; Witteman, Ben J.; Kruyt, Philip M.; Scheepers, Joris J.; Molenaar, I. Quintus|info:eu-repo/dai/nl/239093976; Schaapherder, Alexander F.; Manusama, Eric R.; Van Der Waaij, Laurens A.; Van Unen, Jacco; Dijkgraaf, Marcel G.; Van Ramshorst, Bert; Gooszen, Hein G.; Boerma, Djamila
2015-01-01
Background In patients with mild gallstone pancreatitis, cholecystectomy during the same hospital admission might reduce the risk of recurrent gallstone-related complications, compared with the more commonly used strategy of interval cholecystectomy. However, evidence to support same-admission
Output Feedback Based Admissible Control of Switched Linear Singular Systems%切换线性奇异系统输出反馈容许控制
孟斌; 张纪峰
2006-01-01
The admissibility analysis and robust admissible control problem of the uncertain discretetime switched linear singular (SLS) systems for arbitrary switching laws are investigated. Based on linear matrix inequalities, some sufficient conditions are given for: A) the existence of generalized common Lyapunov solution and the admissibility of the SLS systems for arbitrary switching laws,B) the existence of static output feedback control laws ensuring the admissibility of the closed-loop SLS systems for arbitrary switching laws and norm-bounded uncertainties.
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...
Performance of a Two-Level Call Admission Control Scheme for DS-CDMA Wireless Networks
Abraham O. Fapojuwo
2007-11-01
Full Text Available We propose a two-level call admission control (CAC scheme for direct sequence code division multiple access (DS-CDMA wireless networks supporting multimedia traffic and evaluate its performance. The first-level admission control assigns higher priority to real-time calls (also referred to as class 0 calls in gaining access to the system resources. The second level admits nonreal-time calls (or class 1 calls based on the resources remaining after meeting the resource needs for real-time calls. However, to ensure some minimum level of performance for nonreal-time calls, the scheme reserves some resources for such calls. The proposed two-level CAC scheme utilizes the delay-tolerant characteristic of non-real-time calls by incorporating a queue to temporarily store those that cannot be assigned resources at the time of initial access. We analyze and evaluate the call blocking, outage probability, throughput, and average queuing delay performance of the proposed two-level CAC scheme using Markov chain theory. The analytic results are validated by simulation results. The numerical results show that the proposed two-level CAC scheme provides better performance than the single-level CAC scheme. Based on these results, it is concluded that the proposed two-level CAC scheme serves as a good solution for supporting multimedia applications in DS-CDMA wireless communication systems.
Performance of a Two-Level Call Admission Control Scheme for DS-CDMA Wireless Networks
Fapojuwo Abraham O
2007-01-01
Full Text Available We propose a two-level call admission control (CAC scheme for direct sequence code division multiple access (DS-CDMA wireless networks supporting multimedia traffic and evaluate its performance. The first-level admission control assigns higher priority to real-time calls (also referred to as class 0 calls in gaining access to the system resources. The second level admits nonreal-time calls (or class 1 calls based on the resources remaining after meeting the resource needs for real-time calls. However, to ensure some minimum level of performance for nonreal-time calls, the scheme reserves some resources for such calls. The proposed two-level CAC scheme utilizes the delay-tolerant characteristic of non-real-time calls by incorporating a queue to temporarily store those that cannot be assigned resources at the time of initial access. We analyze and evaluate the call blocking, outage probability, throughput, and average queuing delay performance of the proposed two-level CAC scheme using Markov chain theory. The analytic results are validated by simulation results. The numerical results show that the proposed two-level CAC scheme provides better performance than the single-level CAC scheme. Based on these results, it is concluded that the proposed two-level CAC scheme serves as a good solution for supporting multimedia applications in DS-CDMA wireless communication systems.
Hybrid Genetic Algorithms with Fuzzy Logic Controller
无
2001-01-01
In this paper, a new implementation of genetic algorithms (GAs) is developed for the machine scheduling problem, which is abundant among the modern manufacturing systems. The performance measure of early and tardy completion of jobs is very natural as one's aim, which is usually to minimize simultaneously both earliness and tardiness of all jobs. As the problem is NP-hard and no effective algorithms exist, we propose a hybrid genetic algorithms approach to deal with it. We adjust the crossover and mutation probabilities by fuzzy logic controller whereas the hybrid genetic algorithm does not require preliminary experiments to determine probabilities for genetic operators. The experimental results show the effectiveness of the GAs method proposed in the paper.``
Mitigating Handoff Call Dropping in Wireless Cellular Networks: A Call Admission Control Technique
Ekpenyong, Moses Effiong; Udoh, Victoria Idia; Bassey, Udoma James
2016-06-01
Handoff management has been an important but challenging issue in the field of wireless communication. It seeks to maintain seamless connectivity of mobile users changing their points of attachment from one base station to another. This paper derives a call admission control model and establishes an optimal step-size coefficient (k) that regulates the admission probability of handoff calls. An operational CDMA network carrier was investigated through the analysis of empirical data collected over a period of 1 month, to verify the performance of the network. Our findings revealed that approximately 23 % of calls in the existing system were lost, while 40 % of the calls (on the average) were successfully admitted. A simulation of the proposed model was then carried out under ideal network conditions to study the relationship between the various network parameters and validate our claim. Simulation results showed that increasing the step-size coefficient degrades the network performance. Even at optimum step-size (k), the network could still be compromised in the presence of severe network crises, but our model was able to recover from these problems and still functions normally.
Novel Stochastic Model for Call Admission Control in Broadband Wireless Multimedia Networks
LIUGan; ZHUGuangxi; RUANYoulin; HUZhenping; WUWeimin; WANGDesheng
2005-01-01
As the increasing demand of the capacity of cellular networks, the cell sizes have become smaller than ever, which increases the probability of handoff one may experience during a service. To ensure the calls， QoS and high channel utilization, an effective call admission control is needed urgently. The well-known Guard channel method (GCM) which works with static fashion cannotadapt to the changes in traffic pattern, whereas, SDCA mechanism proposed by S. Wu can overcome that shortcoming due to its dynamic nature. Unfortunately, it is only suitable for single-service. In this paper, we establish a novel stochastic model to study the actual system so as to avoid coping with the complex multiple dimensions stochastic problem. Two wonderful features of the model make it competent for this role. On one hand, it can turnthe multiple steps of state transition into single step ofstate transition, which is a necessary condition for ideal birth-death processes. On the other hand, it can providea simple method to compute the approximation of the call dropping probabilities for multiple services， which facilitate our estimation for the acceptance ratio vector subject to QoS requirement. As a result, we get a multi-services dynamic call admission scheme to adapt for multiple types of services in mobile wireless networks. Numerical results show that our scheme steadily satisfies the constraint on call dropping probability of multi-services while maintaining a high channel throughput.
Chemical optimization algorithm for fuzzy controller design
Astudillo, Leslie; Castillo, Oscar
2014-01-01
In this book, a novel optimization method inspired by a paradigm from nature is introduced. The chemical reactions are used as a paradigm to propose an optimization method that simulates these natural processes. The proposed algorithm is described in detail and then a set of typical complex benchmark functions is used to evaluate the performance of the algorithm. Simulation results show that the proposed optimization algorithm can outperform other methods in a set of benchmark functions. This chemical reaction optimization paradigm is also applied to solve the tracking problem for the dynamic model of a unicycle mobile robot by integrating a kinematic and a torque controller based on fuzzy logic theory. Computer simulations are presented confirming that this optimization paradigm is able to outperform other optimization techniques applied to this particular robot application
AN Enhanced SINR-Based Call Admission Control in 3G Networks
Moses Ekpenyong
2011-11-01
Full Text Available This paper presents the signal-to-interference plus noise ratio (SINR-based call admission control (CAC as an effective technique that guarantees signal quality for admitted users. We propose a CAC model that admits users as long as the SINR exceeds a threshold (th SINR . To reduce blocking, we ensure that the threshold level is maintained at a lower bound (lb thSINR −, convenient to keep the blocking probability ( Pb below a maximum value ( Pb−max. We simulate the CAC model with the Java programming language and evaluate the performance of the model. Simulation results show that our CAC scheme produce the expected performance that improves the network quality.
FUZZY-LOGIC BASED CALL ADMISSION CONTROL FOR A HETEROGENEOUS RADIO ENVIRONMENT
Ramkumar, Venkata; Mihovska, Albena D.; Prasad, Neeli R.;
Dette dokument foreslår et nyt opkald Admission Control (CAC) algoritme, der finder forskellige typer af applikationer med forskellige QoS parametre, som en bruger og giver de nødvendige QoS til nyankomne brugere uden en forringelse af de QoS at der allerede er optaget dem. Den foreslåede CAC er...... evalueret for en heterogen radio access-teknologier (rotter) scenario. Den QoS parametre varierer afhængigt af den type af ansøgninger, og aftalen mellem udbyderen og brugeren. Den foreslåede CAC er baseret på en fuzzy logik mekanisme, der består af to etaper, i første omgang den bedste celle i hver RAT er...
Computational Controls Workstation: Algorithms and hardware
Venugopal, R.; Kumar, M.
1993-01-01
The Computational Controls Workstation provides an integrated environment for the modeling, simulation, and analysis of Space Station dynamics and control. Using highly efficient computational algorithms combined with a fast parallel processing architecture, the workstation makes real-time simulation of flexible body models of the Space Station possible. A consistent, user-friendly interface and state-of-the-art post-processing options are combined with powerful analysis tools and model databases to provide users with a complete environment for Space Station dynamics and control analysis. The software tools available include a solid modeler, graphical data entry tool, O(n) algorithm-based multi-flexible body simulation, and 2D/3D post-processors. This paper describes the architecture of the workstation while a companion paper describes performance and user perspectives.
Search algorithms, hidden labour and information control
Paško Bilić
2016-06-01
Full Text Available The paper examines some of the processes of the closely knit relationship between Google’s ideologies of neutrality and objectivity and global market dominance. Neutrality construction comprises an important element sustaining the company’s economic position and is reflected in constant updates, estimates and changes to utility and relevance of search results. Providing a purely technical solution to these issues proves to be increasingly difficult without a human hand in steering algorithmic solutions. Search relevance fluctuates and shifts through continuous tinkering and tweaking of the search algorithm. The company also uses third parties to hire human raters for performing quality assessments of algorithmic updates and adaptations in linguistically and culturally diverse global markets. The adaptation process contradicts the technical foundations of the company and calculations based on the initial Page Rank algorithm. Annual market reports, Google’s Search Quality Rating Guidelines, and reports from media specialising in search engine optimisation business are analysed. The Search Quality Rating Guidelines document provides a rare glimpse into the internal architecture of search algorithms and the notions of utility and relevance which are presented and structured as neutral and objective. Intertwined layers of ideology, hidden labour of human raters, advertising revenues, market dominance and control are discussed throughout the paper.
Search algorithms, hidden labour and information control
Paško Bilić
2016-06-01
Full Text Available The paper examines some of the processes of the closely knit relationship between Google’s ideologies of neutrality and objectivity and global market dominance. Neutrality construction comprises an important element sustaining the company’s economic position and is reflected in constant updates, estimates and changes to utility and relevance of search results. Providing a purely technical solution to these issues proves to be increasingly difficult without a human hand in steering algorithmic solutions. Search relevance fluctuates and shifts through continuous tinkering and tweaking of the search algorithm. The company also uses third parties to hire human raters for performing quality assessments of algorithmic updates and adaptations in linguistically and culturally diverse global markets. The adaptation process contradicts the technical foundations of the company and calculations based on the initial Page Rank algorithm. Annual market reports, Google’s Search Quality Rating Guidelines, and reports from media specialising in search engine optimisation business are analysed. The Search Quality Rating Guidelines document provides a rare glimpse into the internal architecture of search algorithms and the notions of utility and relevance which are presented and structured as neutral and objective. Intertwined layers of ideology, hidden labour of human raters, advertising revenues, market dominance and control are discussed throughout the paper.
OPTIMAL CONTROL ALGORITHMS FOR SECOND ORDER SYSTEMS
Danilo Pelusi
2013-01-01
Full Text Available Proportional Integral Derivative (PID controllers are widely used in industrial processes for their simplicity and robustness. The main application problems are the tuning of PID parameters to obtain good settling time, rise time and overshoot. The challenge is to improve the timing parameters to achieve optimal control performances. Remarkable findings are obtained through the use of Artificial Intelligence techniques as Fuzzy Logic, Genetic Algorithms and Neural Networks. The combination of these theories can give good results in terms of settling time, rise time and overshoot. In this study, suitable controllers able of improving timing performance of second order plants are proposed. The results show that the PID controller has good overshoot values and shows optimal robustness. The genetic-fuzzy controller gives a good value of settling time and a very good overshoot value. The neural-fuzzy controller gives the best timing parameters improving the control performances of the others two approaches. Further improvements are achieved designing a real-time optimization algorithm which works on a genetic-neuro-fuzzy controller.
Optimization Algorithms for Nuclear Reactor Power Control
Kim, Yeong Min; Oh, Won Jong; Oh, Seung Jin; Chun, Won Gee; Lee, Yoon Joon [Jeju National University, Jeju (Korea, Republic of)
2010-10-15
One of the control techniques that could replace the present conventional PID controllers in nuclear plants is the linear quadratic regulator (LQR) method. The most attractive feature of the LQR method is that it can provide the systematic environments for the control design. However, the LQR approach heavily depends on the selection of cost function and the determination of the suitable weighting matrices of cost function is not an easy task, particularly when the system order is high. The purpose of this paper is to develop an efficient and reliable algorithm that could optimize the weighting matrices of the LQR system
CAOYanbo; ZHOUBin; LIChengshu
2004-01-01
In this paper, we research an admission control scheme of integrated voice and data CDMA/TDD (Code division multiple access/Time division duplex) system considering asymmetric traffic and power limit. A new user can access the system only if the outage probabilities it experiences on the uplink and downlink time slots are below a threshold value. Based on the power limit the results show the voice and data blocking probabilities under different cell coverage~ arrival rates and various uplink/downlink time slot allocation patterns. Furthermore, multicode and multislot schemes are also evaluated under the presented admission control scheme.
The effect of gun control laws on hospital admissions for children in the United States.
Tashiro, Jun; Lane, Rebecca S; Blass, Lawrence W; Perez, Eduardo A; Sola, Juan E
2016-10-01
Gun control laws vary greatly between states within the United States. We hypothesized that states with strict gun laws have lower mortality and resource utilization rates from pediatric firearms-related injury admissions. Kids' Inpatient Database (1997-2012) was searched for accidental (E922), self-inflicted (E955), assault (E965), legal intervention-related (E970), or undetermined circumstance (E985) firearm injuries. Patients were younger than 20 years and admitted for their injuries. Case incidence trends were examined for the study period. Propensity score-matched analyses were performed using 38 covariates to compare outcomes between states with strict or lenient gun control laws. Overall, 38,424 cases were identified, with an overall mortality of 7%. Firearm injuries were most commonly assault (64%), followed by accidental (25%), undetermined circumstance (7%), or self-inflicted (3%). A small minority involved military-grade weapons (0.2%). Most cases occurred in lenient gun control states (48%), followed by strict (47%) and neutral (6%).On 1:1 propensity score-matched analysis, in-hospital mortality by case was higher in lenient (7.5%) versus strict (6.5%) states, p = 0.013. Lenient states had a proportionally higher rate of accidental (31%) and self-inflicted injury (4%) versus strict states (17% and 1.6%, respectively), p gun control contributes not only to worse outcomes per case, but also to a more significant and detrimental impact on public health. Epidemiologic study, level III.
A Novel Evolutionary-Fuzzy Control Algorithm for Complex Systems
王攀; 徐承志; 冯珊; 徐爱华
2002-01-01
This paper presents an adaptive fuzzy control scheme based on modified genetic algorithm. In the control scheme, genetic algorithm is used to optimze the nonlinear quantization functions of the controller and some key parameters of the adaptive control algorithm. Simulation results show that this control scheme has satisfactory performance in MIMO systems, chaotic systems and delay systems.
Adaptive Control Algorithm of the Synchronous Generator
Shevchenko Victor
2017-01-01
Full Text Available The article discusses the the problem of controlling a synchronous generator, namely, maintaining the stability of the control object in the conditions of occurrence of noise and disturbances in the regulatory process. The model of a synchronous generator is represented by a system of differential equations of Park-Gorev, where state variables are computed relative to synchronously rotating d, q-axis. Management of synchronous generator is proposed to organize on the basis of the position-path control using algorithms to adapt with the reference model. Basic control law directed on the stabilizing indicators the frequency generated by the current and the required power level, which is achieved by controlling the mechanical torque on the shaft of the turbine and the value of the excitation voltage of the synchronous generator. Modification of the classic adaptation algorithm using the reference model, allowing to minimize the error of the reference regulation and the model under investigation within the prescribed limits, produced by means of the introduction of additional variables controller adaptation in the model. Сarried out the mathematical modeling of control provided influence on the studied model of continuous nonlinear and unmeasured the disturbance. Simulation results confirm the high level accuracy of tracking and adaptation investigated model with respect to the reference, and the present value of the loop error depends on parameters performance of regulator.
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
2013-10-17
To test the effectiveness of telemonitoring integrated into existing clinical services such that intervention and control groups have access to the same clinical care. Researcher blind, multicentre, randomised controlled trial. UK primary care (Lothian, Scotland). 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 to provide informed consent or complete the study, or who had other significant social or clinical problems. Participants were recruited between 21 May 2009 and 28 March 2011, and centrally randomised to receive telemonitoring or conventional self monitoring. Using a touch screen, telemonitoring participants recorded a daily questionnaire about symptoms and treatment use, and monitored oxygen saturation using linked instruments. Algorithms, based on the symptom score, generated alerts if readings were omitted or breached thresholds. Both groups received similar care from existing clinical services. The primary outcome was time to hospital admission due to COPD exacerbation up to one year after randomisation. Other outcomes included number and duration of admissions, and validated questionnaire assessments of health related quality of life (using St George's respiratory questionnaire (SGRQ)), anxiety or depression (or both), self efficacy, knowledge, and adherence to treatment. Analysis was intention to treat. Of 256 patients completing the study, 128 patients were randomised to telemonitoring and 128 to usual care; baseline characteristics of each group were similar. The number of days to admission did not differ significantly between groups (adjusted hazard ratio 0.98, 95% confidence interval 0.66 to 1.44). Over one year, the mean number of COPD admissions was similar in both groups (telemonitoring 1.2 admissions per person (standard deviation 1.9) v control 1.1 (1.6); P=0.59). Mean duration of COPD admissions over
The importance of safety, agency and control during involuntary mental health admissions.
Wyder, Marianne; Bland, Robert; Crompton, David
2016-08-01
Constructs such as personal recovery, patient engagement and consumer involvement are central in mental health care delivery. These approaches emphasise the importance of empowerment and choice. Under some circumstances Involuntary Treatment Orders (ITO) allow a person to be treated for a mental illness without their consent. This study explores the tensions between the principles of empowerment and control and involuntary treatment. Twenty-five involuntary inpatients of a major teaching hospital were interviewed about their experiences of being placed under an ITO. The interviews were analysed thematically. Being able to have some sense of agency and re-asserting personal control are critical components of an involuntary mental health admission. Participants wanted information about their treatment, the ITO process and their environment. They also spoke about the importance of a space where they felt safe from themselves and others to make sense of the experience. This study suggests that for coercive treatment to aid, rather than disrupt recovery, treatment services need to focus on: the provision of rights; the creation of a sense of safety; establishing supportive relationships; carrying hope and finding ways to foster a strong sense of agency and empowerment.
Study on the Class-Based Admission Control Scheme for DiffServ in MPLS Networks
李震宇; 张中兆
2003-01-01
Differentiated services (DiffServ) and MPLS are two major building blocks for providing multi-class services over IP networks. In order to respond to the need for relatively simple, coarse methods of providing different levels of service for Internet traffic, to support various types of applications and specific business requirements, the MPLS network infrastructure and the DiffServ traffic model will work together. Meanwhile, in today's environment of multiple service networks, it is necessary for the node in the networks to perform the control mechanism to guarantee various QoS. In this paper, we propose a class-based admission control scheme that is suitable for DiffServ in MPLS networks. This scheme can achieve twofold objects: reliable QoS provisioning and high resource utilization. We evaluate the proposed scheme by numerical analysis of its performance in terms of throughput, delay, and reject probability. By performing simulation, we can ensure that the proposed scheme can work efficiently to provide strict QoS guarantees.
Simulation research on control algorithm of differential pressure casting process
Chai Yan; Jie Wanqi; Yang Bo
2009-01-01
To improve the precision of the filling pressure curve of differential pressure casting controlled with PID controller,the model of differential pressure casting process is established and two pressure-difference control systems using PID algorithm and Dahlin algorithm are separately designed in MATLAB. The scheduled pressure curves controlled with PID algorithm and Dahlin algorithm,respectively,are comparatively simulated in MATLAB.The simulated pressure curves obtained show that the control precision with Dahlin algorithm is higher than that with PID algorithm in the differential pressure casting process,and it was further verified by production practice.
Briscoe, B.; Eardley, P.; Songhurst, D.; Le Faucheur, F.; Charny, A.; Liatsos, V.; Babiarz, J.; Chan, K.; Dudley, S.; Karagiannis, G.; Bader, A.; Westberg, L.; Briscoe, B.; Eardley, P.; Songhurst, D.; Le Faucheur, F.; Charny, A.; Liatsos, V.; Babiarz, J.; Chan, K.; Dudley, S.; Karagiannis, G.; Bader, A.; Westberg, L.
2006-01-01
This document describes a deployment model for pre-congestion notification (PCN) operating in a large DiffServ-based region of the Internet. PCN-based admission control protects the quality of service of existing flows in normal circumstances, whilst if necessary (eg after a large failure) pre-empti
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
BCI Control of Heuristic Search Algorithms
Cavazza, Marc; Aranyi, Gabor; Charles, Fred
2017-01-01
The ability to develop Brain-Computer Interfaces (BCI) to Intelligent Systems would offer new perspectives in terms of human supervision of complex Artificial Intelligence (AI) systems, as well as supporting new types of applications. In this article, we introduce a basic mechanism for the control of heuristic search through fNIRS-based BCI. The rationale is that heuristic search is not only a basic AI mechanism but also one still at the heart of many different AI systems. We investigate how users’ mental disposition can be harnessed to influence the performance of heuristic search algorithm through a mechanism of precision-complexity exchange. From a system perspective, we use weighted variants of the A* algorithm which have an ability to provide faster, albeit suboptimal solutions. We use recent results in affective BCI to capture a BCI signal, which is indicative of a compatible mental disposition in the user. It has been established that Prefrontal Cortex (PFC) asymmetry is strongly correlated to motivational dispositions and results anticipation, such as approach or even risk-taking, and that this asymmetry is amenable to Neurofeedback (NF) control. Since PFC asymmetry is accessible through fNIRS, we designed a BCI paradigm in which users vary their PFC asymmetry through NF during heuristic search tasks, resulting in faster solutions. This is achieved through mapping the PFC asymmetry value onto the dynamic weighting parameter of the weighted A* (WA*) algorithm. We illustrate this approach through two different experiments, one based on solving 8-puzzle configurations, and the other on path planning. In both experiments, subjects were able to speed up the computation of a solution through a reduction of search space in WA*. Our results establish the ability of subjects to intervene in heuristic search progression, with effects which are commensurate to their control of PFC asymmetry: this opens the way to new mechanisms for the implementation of hybrid
Nonlinear model predictive control theory and algorithms
Grüne, Lars
2017-01-01
This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...
Shunfu Jin
2013-01-01
Full Text Available In cognitive radio networks, if all the secondary user (SU packets join the system without any restrictions, the average latency of the SU packets will be greater, especially when the traffic load of the system is higher. For this, we propose an adaptive admission control scheme with a system access probability for the SU packets in this paper. We suppose the system access probability is inversely proportional to the total number of packets in the system and introduce an Adaptive Factor to adjust the system access probability. Accordingly, we build a discrete-time preemptive queueing model with adjustable joining rate. In order to obtain the steady-state distribution of the queueing model exactly, we construct a two-dimensional Markov chain. Moreover, we derive the formulas for the blocking rate, the throughput, and the average latency of the SU packets. Afterwards, we provide numerical results to investigate the influence of the Adaptive Factor on different performance measures. We also give the individually optimal strategy and the socially optimal strategy from the standpoints of the SU packets. Finally, we provide a pricing mechanism to coordinate the two optimal strategies.
A BATCH ARRIVAL RETRIAL QUEUE WITH STARTING FAILURES, FEEDBACK AND ADMISSION CONTROL
Jinting WANG; Peng-Feng ZHOU
2010-01-01
This paper is concerned with the analysis of a feedback M[X]/G/1 retrial queue with starting failures and general retrial times.In a batch,each individual customer is subject to a control admission policy upon arrival.If the server is idle,one of the customers admitted to the system may start its service and the rest joins the retrial group,whereas all the admitted customers go to the retrial group when the server is unavailable upon arrival.An arriving customer(primary or retrial)must turn-on the server,which takes negligible time.If the server is started successfully(with a certain probability),the customer gets service immediately.Otherwise,the repair for the server commences immediately and the customer must leave for the orbit and make a retrial at a later time.It is assumed that the customers who find the server unavailable are queued in the orbit in accordance with an FCFS discipline and only the customer at the head of the queue is allowed for access to the server.The Markov chain underlying the considered queueing system is studied and the necessary and sufficient condition for the system to be stable is presented.Explicit formulae for the stationary distribution and some performance measures of the system in steady-state are obtained.Finally,some numerical examples are presented to illustrate the influence of the parameters on several performance characteristics.
MODELING MULTI-TRAFFIC ADMISSION CONTROL IN OFDMA SYSTEM USING COLORED PETRI NET
Yao Yuanyuan; Lu Yanhui; Yang Shouyi
2012-01-01
Call Admission Control (CAC) is one of the key traffic management mechanisms that must be deployed in order to meet the strict requirements for dependability imposed on the services provided by modern wireless networks.In this paper,we develop an executable top-down hierarchical Colored Petri Net (CPN) model for multi-traffic CAC in Orthogonal Frequency Division Multiple Access (OFDMA) system.By theoretic analysis and CPN simulation,it is demonstrated that the CPN model is isomorphic to Markov Chain (MC) assuming that each data stream follows Poisson distribution and the corresponding arrival time interval is an exponential random variable,and it breaks through MC's explicit limitation,which includes MC's memoryless property and proneness to state space explosion in evaluating CAC process.Moreover,we present four CAC schemes based on CPN model taking into account call-level and packet-level Quality of Service (QoS).The simulation results show that CPN offers significant advantages over MC in modeling CAC strategies and evaluating their performance with less computational complexity in addition to its flexibility and adaptability to different scenarios.
MPPT algorithm for voltage controlled PV inverters
Kerekes, Tamas; Teodorescu, Remus; Liserre, Marco;
2008-01-01
This paper presents a novel concept for an MPPT that can be used in case of a voltage controlled grid connected PV inverters. In case of single-phase systems, the 100 Hz ripple in the AC power is also present on the DC side. Depending on the DC link capacitor, this power fluctuation can be used t...... to track the MPP of the PV array, using the information that at MPP the power oscillations are very small. In this way the algorithm can detect the fact that the current working point is at the MPP, for the current atmospheric conditions....
Telephony Over IP: A QoS Measurement-Based End to End Control Algorithm
Luigi Alcuri
2004-12-01
Full Text Available This paper presents a method for admitting voice calls in Telephony over IP (ToIP scenarios. This method, called QoS-Weighted CAC, aims to guarantee Quality of Service to telephony applications. We use a measurement-based call admission control algorithm, which detects network congested links through a feedback on overall link utilization. This feedback is based on the measures of packet delivery latencies related to voice over IP connections at the edges of the transport network. In this way we introduce a close loop control method, which is able to auto-adapt the quality margin on the basis of network load and specific service level requirements. Moreover we evaluate the difference in performance achieved by different Queue management configurations to guarantee Quality of Service to telephony applications, in which our goal was to evaluate the weight of edge router queue configuration in complex and real-like telephony over IP scenario. We want to compare many well-know queue scheduling algorithms, such as SFQ, WRR, RR, WIRR, and Priority. This comparison aims to locate queue schedulers in a more general control scheme context where different elements such as DiffServ marking and Admission control algorithms contribute to the overall Quality of Service required by real-time voice conversations. By means of software simulations we want to compare this solution with other call admission methods already described in scientific literature in order to locate this proposed method in a more general control scheme context. On the basis of the results we try to evidence the possible advantages of this QoS-Weighted solution in comparison with other similar CAC solutions ( in particular Measured Sum, Bandwidth Equivalent with Hoeffding Bounds, and Simple Measure CAC, on the planes of complexity, stability, management, tune-ability to service level requirements, and compatibility with actual network implementation.
Performance evaluation of sensor allocation algorithm based on covariance control
无
2005-01-01
The covariance control capability of sensor allocation algorithms based on covariance control strategy is an important index to evaluate the performance of these algorithms. Owing to lack of standard performance metric indices to evaluate covariance control capability, sensor allocation ratio, etc, there are no guides to follow in the design procedure of sensor allocation algorithm in practical applications. To meet these demands, three quantified performance metric indices are presented, which are average covariance misadjustment quantity (ACMQ), average sensor allocation ratio (ASAR) and matrix metric influence factor (MMIF), where ACMQ, ASAR and MMIF quantify the covariance control capability, the usage of sensor resources and the robustness of sensor allocation algorithm, respectively. Meanwhile, a covariance adaptive sensor allocation algorithm based on a new objective function is proposed to improve the covariance control capability of the algorithm based on information gain. The experiment results show that the proposed algorithm have the advantage over the preceding sensor allocation algorithm in covariance control capability and robustness.
Genetic Algorithm based Decentralized PI Type Controller: Load Frequency Control
Dwivedi, Atul; Ray, Goshaidas; Sharma, Arun Kumar
2016-12-01
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.
基于接纳控制的智能电网需求响应%Demand response based on admission control in smart grid
马锴; 姚婷; 关新平
2015-01-01
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.%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。
Jinxing Lin
2010-01-01
Full Text Available This paper is concerned with the problems of exponential admissibility and dynamic output feedback (DOF control for a class of continuous-time switched singular systems with interval time-varying delay. A full-order, dynamic, synchronously switched DOF controller is considered. First, by using the average dwell time approach, a delay-range-dependent exponential admissibility criterion for the unforced switched singular time-delay system is established in terms of linear matrix inequalities (LMIs. Then, based on this criterion, a sufficient condition on the existence of a desired DOF controller, which guarantees that the closed-loop system is regular, impulse free and exponentially stable, is proposed by employing the LMI technique. Finally, some illustrative examples are given to show the effectiveness of the proposed approach.
Maintenance of Process Control Algorithms based on Dynamic Program Slicing
Hansen, Ole Fink; Andersen, Nils Axel; Ravn, Ole
2010-01-01
Today’s industrial control systems gradually lose performance after installation and must be regularly maintained by means of adjusting parameters and modifying the control algorithm, in order to regain high performance. Industrial control algorithms are complex software systems, and it is partic......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...... the 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...
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.
Efficient algorithms for the laboratory discovery of optimal quantum controls.
Turinici, Gabriel; Le Bris, Claude; Rabitz, Herschel
2004-01-01
The laboratory closed-loop optimal control of quantum phenomena, expressed as minimizing a suitable cost functional, is currently implemented through an optimization algorithm coupled to the experimental apparatus. In practice, the most commonly used search algorithms are variants of genetic algorithms. As an alternative choice, a direct search deterministic algorithm is proposed in this paper. For the simple simulations studied here, it outperforms the existing approaches. An additional algorithm is introduced in order to reveal some properties of the cost functional landscape.
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.
AAO Starbugs: software control and associated algorithms
Lorente, Nuria P. F.; Vuong, Minh V.; Shortridge, Keith; Farrell, Tony J.; Smedley, Scott; Hong, Sungwook E.; Bacigalupo, Carlos; Goodwin, Michael; Kuehn, Kyler; Satorre, Christophe
2016-08-01
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.
Thomsen, Christoffer Torgaard; Benros, Michael Eriksen; Hastrup, Lene Halling; Andersen, Per Kragh; Giacco, Domenico; Nordentoft, Merete
2016-01-01
Introduction Patient-controlled hospital admission for individuals with severe mental disorders is a novel approach in mental healthcare. Patients can admit themselves to a hospital unit for a short stay without being assessed by a psychiatrist or contacting the emergency department. Previous studies assessing the outcomes of patient-controlled hospital admission found trends towards reduction in the use of coercive measures and length of hospital stay; however, these studies have methodological shortcomings and small sample sizes. Larger studies are needed to estimate the effect of patient-controlled hospital admission on the use of coercion and of healthcare services. Design and methods We aim to recruit at least 315 patients who are offered a contract for patient-controlled hospital admissions in eight different hospitals in Denmark. Patients will be followed-up for at least 1 year to compare the use of coercive measures and of healthcare services, the use of medications and suicidal behaviour. Descriptive statistics will be used to investigate hospitalisations, global assessment of functioning (GAF) and patient satisfaction with treatment. To minimise selection bias, we will match individuals using patient-controlled hospital admission and controls with a 1:5 ratio via a propensity score based on the following factors: sex, age group, primary diagnosis, substance abuse as secondary diagnosis, coercion, number of psychiatric bed days, psychiatric history, urbanity and suicidal behaviour. Additionally, a historical control study will be undertaken in which patients serve as their own control group prior to index date. Ethics and dissemination The study has been approved by The Danish Health and Medicines Authority (j.nr.: 3-3013-934/1/) and by The Danish Data Protection Agency (j.nr.: 2012-58-0004). The study was categorised as a register study by The Danish Health Research Ethics Committee and therefore no further approval was needed (j.nr.: H-2-2014-FSP70
Multiobjective Genetic Algorithm applied to dengue control.
Florentino, Helenice O; Cantane, Daniela R; Santos, Fernando L P; Bannwart, Bettina F
2014-12-01
Dengue fever is an infectious disease caused by a virus of the Flaviridae family and transmitted to the person by a mosquito of the genus Aedes aegypti. This disease has been a global public health problem because a single mosquito can infect up to 300 people and between 50 and 100 million people are infected annually on all continents. Thus, dengue fever is currently a subject of research, whether in the search for vaccines and treatments for the disease or efficient and economical forms of mosquito control. The current study aims to study techniques of multiobjective optimization to assist in solving problems involving the control of the mosquito that transmits dengue fever. The population dynamics of the mosquito is studied in order to understand the epidemic phenomenon and suggest strategies of multiobjective programming for mosquito control. A Multiobjective Genetic Algorithm (MGA_DENGUE) is proposed to solve the optimization model treated here and we discuss the computational results obtained from the application of this technique.
Hoover, Eric; Millman, Sierra
2007-01-01
Marilee Jones's career had been a remarkable success. She joined Massachusetts Institute of Technology's (MIT's) admissions office in 1979, landing a job in Cambridge at a time when boys ruled the sandbox of the admissions profession. Her job was to help MIT recruit more women, who then made up less than one-fifth of the institute's students. She…
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...
Clonal Selection Algorithm Based Iterative Learning Control with Random Disturbance
Yuanyuan Ju
2013-01-01
Full Text Available Clonal selection algorithm is improved and proposed as a method to solve optimization problems in iterative learning control. And a clonal selection algorithm based optimal iterative learning control algorithm with random disturbance is proposed. In the algorithm, at the same time, the size of the search space is decreased and the convergence speed of the algorithm is increased. In addition a model modifying device is used in the algorithm to cope with the uncertainty in the plant model. In addition a model is used in the algorithm cope with the uncertainty in the plant model. Simulations show that the convergence speed is satisfactory regardless of whether or not the plant model is precise nonlinear plants. The simulation test verify the controlled system with random disturbance can reached to stability by using improved iterative learning control law but not the traditional control law.
Wei, Qinglai; Liu, Derong; Lin, Qiao
2016-08-03
In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.
Analysis of algorithms for intensive care unit blood glucose control.
Bequette, B Wayne
2007-11-01
Intensive care unit (ICU) blood glucose control algorithms were reviewed and analyzed in the context of linear systems theory and classical feedback control algorithms. Closed-loop performance was illustrated by applying the algorithms in simulation studies using an in silico model of an ICU patient. Steady-state and dynamic input-output analysis was used to provide insight about controller design and potential closed-loop performance. The proportional-integral-derivative, columnar insulin dosing (CID, Glucommander-like), and glucose regulation for intensive care patients (GRIP) algorithms were shown to have similar features and performance. The CID strategy is a time-varying proportional-only controller (no integral action), whereas the GRIP algorithm is a nonlinear controller with integral action. A minor modification to the GRIP algorithm was suggested to improve the closed-loop performance. Recommendations were made to guide control theorists on important ICU control topics worthy of further study.
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.
Admissions Testing & Institutional Admissions Processes
Hossler, Don; Kalsbeek, David
2009-01-01
The array of admissions models and the underlying, and sometimes conflicting goals people have for college admissions, create the dynamics and the tensions that define the contemporary context for enrollment management. The senior enrollment officer must ask, for example, how does an institution try to assure transparency, equality of access,…
Hullick, Carolyn; Conway, Jane; Higgins, Isabel; Hewitt, Jacqueline; Dilworth, Sophie; Holliday, Elizabeth; Attia, John
2016-05-12
Older people living in Residential Aged Care Facilities (RACF) are a vulnerable, frail and complex population. They are more likely than people who reside in the community to become acutely unwell, present to the Emergency Department (ED) and require admission to hospital. For many, hospitalisation carries with it risks. Importantly, evidence suggests that some admissions are avoidable. A new collaborative model of care, the Aged Care Emergency Service (ACE), was developed to provide clinical support to nurses in the RACFs, allowing residents to be managed in place and avoid transfer to the ED. This paper examines the effects of the ACE service on RACF residents' transfer to hospital using a controlled pre-post design. Four intervention RACFs were matched with eight control RACFs based on number of total beds, dementia specific beds, and ratio of high to low care beds in Newcastle, Australia, between March and November 2011. The intervention consisted of a clinical care manual to support care along with a nurse led telephone triage line, education, establishing goals of care prior to ED transfer, case management when in the ED, along with the development of collaborative relationships between stakeholders. Outcomes included ED presentations, length of stay, hospital admission and 28-day readmission pre- and post-intervention. Generalised estimating equations were used to estimate mean differences in outcomes between intervention and controls RACFs, pre- and post-intervention means, and their interaction, accounting for repeated measures and adjusting for matching factors. Residents had a mean age of 86 years. ED presentations ranged between 16 and 211 visits/100 RACF beds/year across all RACFs. There was no overall reduction in ED presentations (OR = 1.17, p = 0.56) with the ACE intervention. However, when compared to the controls, the intervention group reduced their ED length of stay by 45 min (p = 0.0575), and was 40 % less likely to be admitted
Force-Control Algorithm for Surface Sampling
Acikmese, Behcet; Quadrelli, Marco B.; Phan, Linh
2008-01-01
A G-FCON algorithm is designed for small-body surface sampling. It has a linearization component and a feedback component to enhance performance. The algorithm regulates the contact force between the tip of a robotic arm attached to a spacecraft and a surface during sampling.
LEARNING ALGORITHM OF STAGE CONTROL NBP NETWORK
Yan Lixiang; Qin Zheng
2003-01-01
This letter analyzes the reasons why the known Neural Back Promulgation (NBP)network learning algorithm has slower speed and greater sample error. Based on the analysis and experiment, the training group descending Enhanced Combination Algorithm (ECA) is proposed.The analysis of the generalized property and sample error shows that the ECA can heighten the study speed and reduce individual error.
ZHAIXuping; BIGuangguo; XUPingping
2005-01-01
In high-rate short-range wireless networks,CAC (Call admission control) scheme plays an important role in quality of service provisioning for adaptive multimedia services. Three functions, namely bandwidth satisfaction function, revenue rate function and bandwidth reallocation cost function, are firstly introduced. Based on these functions, an efficient CAC scheme, the Rev-RT-BRA (Reservation-based and Revenue test with Bandwidth reallocation) CAC scheme is proposed. The main idea is that it reserves some bandwidth for service classes with higher admission priority. The performance of the Rev-RT-BRA CAC scheme is analyzed by solving a multidimension Markov process. Both the numerical and simulation results are given. The advantages of the proposedRev-RT-BRA CAC scheme are as follows. (1) It maximizes the overall bandwidth satisfaction function at any system state. (2) It solves the unfairness problem in admitting multiple classes of services with different bandwidth requirenlents. (3) The required admission priority level can be guaranteed for various classes of services.
Distributed Random Access Algorithm: Scheduling and Congesion Control
Jiang, Libin; Shin, Jinwoo; Walrand, Jean
2009-01-01
This paper provides proofs of the rate stability, Harris recurrence, and epsilon-optimality of CSMA algorithms where the backoff parameter of each node is based on its backlog. These algorithms require only local information and are easy to implement. The setup is a network of wireless nodes with a fixed conflict graph that identifies pairs of nodes whose simultaneous transmissions conflict. The paper studies two algorithms. The first algorithm schedules transmissions to keep up with given arrival rates of packets. The second algorithm controls the arrivals in addition to the scheduling and attempts to maximize the sum of the utilities of the flows of packets at the different nodes. For the first algorithm, the paper proves rate stability for strictly feasible arrival rates and also Harris recurrence of the queues. For the second algorithm, the paper proves the epsilon-optimality. Both algorithms operate with strictly local information in the case of decreasing step sizes, and operate with the additional info...
Model-Free Adaptive Control Algorithm with Data Dropout Compensation
Xuhui Bu; Fashan Yu; Zhongsheng Hou; Hongwei Zhang
2012-01-01
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 effe...
Advanced CHP Control Algorithms: Scope Specification
Katipamula, Srinivas; Brambley, Michael R.
2006-04-28
The primary objective of this multiyear project is to develop algorithms for combined heat and power systems to ensure optimal performance, increase reliability, and lead to the goal of clean, efficient, reliable and affordable next generation energy systems.
Optimal Pid Controller Design Using Adaptive Vurpso Algorithm
Zirkohi, Majid Moradi
2015-04-01
The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.
Research on intelligent algorithm of electro - hydraulic servo control system
Wang, Yannian; Zhao, Yuhui; Liu, Chengtao
2017-09-01
In order to adapt the nonlinear characteristics of the electro-hydraulic servo control system and the influence of complex interference in the industrial field, using a fuzzy PID switching learning algorithm is proposed and a fuzzy PID switching learning controller is designed and applied in the electro-hydraulic servo controller. The designed controller not only combines the advantages of the fuzzy control and PID control, but also introduces the learning algorithm into the switching function, which makes the learning of the three parameters in the switching function can avoid the instability of the system during the switching between the fuzzy control and PID control algorithms. It also makes the switch between these two control algorithm more smoother than that of the conventional fuzzy PID.
Towards Automatic Controller Design using Multi-Objective Evolutionary Algorithms
Pedersen, Gerulf
of evolutionary computation, a choice was made to use multi-objective algorithms for the purpose of aiding in automatic controller design. More specifically, the choice was made to use the Non-dominated Sorting Genetic Algorithm II (NSGAII), which is one of the most potent algorithms currently in use......, as the 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...
Fuzzy Control of Chaotic System with Genetic Algorithm
FANG Jian-an; GUO Zhao-xia; SHAO Shi-huang
2002-01-01
A novel approach to control the unpredictable behavior of chaotic systems is presented. The control algorithm is based on fuzzy logic control technique combined with genetic algorithm. The use of fuzzy logic allows for the implementation of human "rule-of-thumb" approach to decision making by employing linguistic variables. An improved Genetic Algorithm (GA) is used to learn to optimally select the fuzzy membership functions of the linguistic labels in the condition portion of each rule,and to automatically generate fuzzy control actions under each condition. Simulation results show that such an approach for the control of chaotic systems is both effective and robust.
The research on algorithms for optoelectronic tracking servo control systems
Zhu, Qi-Hai; Zhao, Chang-Ming; Zhu, Zheng; Li, Kun
2016-10-01
The photoelectric servo control system based on PC controllers is mainly used to control the speed and position of the load. This paper analyzed the mathematical modeling and the system identification of the servo system. In the aspect of the control algorithm, the IP regulator, the fuzzy PID, the Active Disturbance Rejection Control (ADRC) and the adaptive algorithms were compared and analyzed. The PI-P control algorithm was proposed in this paper, which not only has the advantages of the PI regulator that can be quickly saturated, but also overcomes the shortcomings of the IP regulator. The control system has a good starting performance and the anti-load ability in a wide range. Experimental results show that the system has good performance under the guarantee of the PI-P control algorithm.
Two-Level Cross-Talked Admission Control Mechanism for QoS Guarantee in 802.11e EDCA
NIU Zhisheng; LIU Jing
2008-01-01
This paper describes a two-level cross-talked admission control mechanism that guarantees qual-ity of service (QoS) requirements for multimedia applications over wireless local area networks (WLANs). An enhanced distributed channel access analytical model is used to compute the maximum number of admitted users according to the QoS requirements and the packet arrival characters. Then, some channel resources are reserved for handoff calls based on the maximum number of admitted users and the call-level traffic model. The channel utilization ratio is also measured to reflect the current system traffic load. The maximum number of admitted users and the channel utilization ratio are used for admission control for applications with QoS requirements in the call level and for rate control of best effort applications in the packet level using the p-nonacknowledgement scheme. Thus, the QoS requirements are statistically guaranteed while the system is efficiently utilized. Simulations validate the effectiveness of this mechanism to guarantee the QoS and bandwidth utilization.
Topology control based on quantum genetic algorithm in sensor networks
SUN Lijuan; GUO Jian; LU Kai; WANG Ruchuan
2007-01-01
Nowadays,two trends appear in the application of sensor networks in which both multi-service and quality of service (QoS)are supported.In terms of the goal of low energy consumption and high connectivity,the control on topology is crucial.The algorithm of topology control based on quantum genetic algorithm in sensor networks is proposed.An advantage of the quantum genetic algorithm over the conventional genetic algorithm is demonstrated in simulation experiments.The goals of high connectivity and low consumption of energy are reached.
Model-Free Adaptive Control Algorithm with Data Dropout Compensation
Xuhui Bu
2012-01-01
Full Text Available The convergence of model-free adaptive control (MFAC algorithm can be guaranteed when the system is subject to measurement data dropout. The system output convergent speed gets slower as dropout rate increases. This paper proposes a MFAC algorithm with data compensation. The missing data is first estimated using the dynamical linearization method, and then the estimated value is introduced to update control input. The convergence analysis of the proposed MFAC algorithm is given, and the effectiveness is also validated by simulations. It is shown that the proposed algorithm can compensate the effect of the data dropout, and the better output performance can be obtained.
Rate control algorithm based on frame complexity estimation for MVC
Yan, Tao; An, Ping; Shen, Liquan; Zhang, Zhaoyang
2010-07-01
Rate control has not been well studied for multi-view video coding (MVC). In this paper, we propose an efficient rate control algorithm for MVC by improving the quadratic rate-distortion (R-D) model, which reasonably allocate bit-rate among views based on correlation analysis. The proposed algorithm consists of four levels for rate bits control more accurately, of which the frame layer allocates bits according to frame complexity and temporal activity. Extensive experiments show that the proposed algorithm can efficiently implement bit allocation and rate control according to coding parameters.
Genetic Algorithm Based Proportional Integral Controller Design for Induction Motor
Mohanasundaram Kuppusamy
2011-01-01
Full Text Available Problem statement: This study has expounded the application of evolutionary computation method namely Genetic Algorithm (GA for estimation of feedback controller parameters for induction motor. GA offers certain advantages such as simple computational steps, derivative free optimization, reduced number of iterations and assured near global optima. The development of the method is well documented and computed and measured results are presented. Approach: The design of PI controller parameter for three phase induction motor drives was done using Genetic Algorithm. The objective function of motor current reduction, using PI controller, at starting is formulated as an optimization problem and solved with Genetic Algorithm. Results: The results showed the selected values of PI controller parameter using genetic algorithm approach, with objective of induction motor starting current reduction. Conclusions/Recommendation: The results proved the robustness and easy implementation of genetic algorithm selection of PI parameters for induction motor starting.
The evaluation of the OSGLR algorithm for restructurable controls
Bonnice, W. F.; Wagner, E.; Hall, S. R.; Motyka, P.
1986-01-01
The detection and isolation of commercial aircraft control surface and actuator failures using the orthogonal series generalized likelihood ratio (OSGLR) test was evaluated. The OSGLR algorithm was chosen as the most promising algorithm based on a preliminary evaluation of three failure detection and isolation (FDI) algorithms (the detection filter, the generalized likelihood ratio test, and the OSGLR test) and a survey of the literature. One difficulty of analytic FDI techniques and the OSGLR algorithm in particular is their sensitivity to modeling errors. Therefore, methods of improving the robustness of the algorithm were examined with the incorporation of age-weighting into the algorithm being the most effective approach, significantly reducing the sensitivity of the algorithm to modeling errors. The steady-state implementation of the algorithm based on a single cruise linear model was evaluated using a nonlinear simulation of a C-130 aircraft. A number of off-nominal no-failure flight conditions including maneuvers, nonzero flap deflections, different turbulence levels and steady winds were tested. Based on the no-failure decision functions produced by off-nominal flight conditions, the failure detection performance at the nominal flight condition was determined. The extension of the algorithm to a wider flight envelope by scheduling the linear models used by the algorithm on dynamic pressure and flap deflection was also considered. Since simply scheduling the linear models over the entire flight envelope is unlikely to be adequate, scheduling of the steady-state implentation of the algorithm was briefly investigated.
Theory, Design, and Algorithms for Optimal Control of wireless Networks
2010-06-09
significantly outperform existing protocols (such as AODV ) in terms of total network cost Furthermore, we have shown that even when components of our...achieved through distributed control algorithms that jointly optimize power control, routing , and congestion factors. A second stochastic model approach...updates the network queue state, node-transmission powers amongst others, allowing for power control, scheduling, and routing algorithms to maximize
Mahmoodpoor, Ata; Hamishehkar, Hadi; Shadvar, Kamran; Beigmohammadi, Mohammadtaghi; Iranpour, Afshin; Sanaie, Sarvin
2016-01-01
Background and Aims: The association between hyperglycemia and mortality is believed to be influenced by the presence of diabetes mellitus (DM). In this study, we evaluated the effect of preexisting hyperglycemia on the association between acute blood glucose management and mortality in critically ill patients. The primary objective of the study was the relationship between HbA1c and mortality in critically ill patients. Secondary objectives of the study were relationship between Intensive Care Unit (ICU) admission blood glucose and glucose control during ICU stay with mortality in critically ill patients. Materials and Methods: Five hundred patients admitted to two ICUs were enrolled. Blood sugar and hemoglobin A1c (HbA1c) concentrations on ICU admission were measured. Age, sex, history of DM, comorbidities, Acute Physiology and Chronic Health Evaluation II score, sequential organ failure assessment score, hypoglycemic episodes, drug history, mortality, and development of acute kidney injury and liver failure were noted for all patients. Results: Without considering the history of diabetes, nonsurvivors had significantly higher HbA1c values compared to survivors (7.25 ± 1.87 vs. 6.05 ± 1.22, respectively, P < 0.001). Blood glucose levels in ICU admission showed a significant correlation with risk of death (P < 0.006, confidence interval [CI]: 1.004–1.02, relative risk [RR]: 1.01). Logistic regression analysis revealed that HbA1c increased the risk of death; with each increase in HbA1c level, the risk of death doubled. However, this relationship was not statistically significant (P: 0.161, CI: 0.933–1.58, RR: 1.2). Conclusions: Acute hyperglycemia significantly affects mortality in the critically ill patients; this relation is also influenced by chronic hyperglycemia. PMID:27076705
Ata Mahmoodpoor
2016-01-01
Full Text Available Background and Aims: The association between hyperglycemia and mortality is believed to be influenced by the presence of diabetes mellitus (DM. In this study, we evaluated the effect of preexisting hyperglycemia on the association between acute blood glucose management and mortality in critically ill patients. The primary objective of the study was the relationship between HbA1c and mortality in critically ill patients. Secondary objectives of the study were relationship between Intensive Care Unit (ICU admission blood glucose and glucose control during ICU stay with mortality in critically ill patients. Materials and Methods: Five hundred patients admitted to two ICUs were enrolled. Blood sugar and hemoglobin A1c (HbA1c concentrations on ICU admission were measured. Age, sex, history of DM, comorbidities, Acute Physiology and Chronic Health Evaluation II score, sequential organ failure assessment score, hypoglycemic episodes, drug history, mortality, and development of acute kidney injury and liver failure were noted for all patients. Results: Without considering the history of diabetes, nonsurvivors had significantly higher HbA1c values compared to survivors (7.25 ± 1.87 vs. 6.05 ± 1.22, respectively, P < 0.001. Blood glucose levels in ICU admission showed a significant correlation with risk of death (P < 0.006, confidence interval [CI]: 1.004–1.02, relative risk [RR]: 1.01. Logistic regression analysis revealed that HbA1c increased the risk of death; with each increase in HbA1c level, the risk of death doubled. However, this relationship was not statistically significant (P: 0.161, CI: 0.933–1.58, RR: 1.2. Conclusions: Acute hyperglycemia significantly affects mortality in the critically ill patients; this relation is also influenced by chronic hyperglycemia.
A Hamiltonian Algorithm for Singular Optimal LQ Control Systems
Delgado-Tellez, M
2012-01-01
A Hamiltonian algorithm, both theoretical and numerical, to obtain the reduced equations implementing Pontryagine's Maximum Principle for singular linear-quadratic optimal control problems is presented. This algorithm is inspired on the well-known Rabier-Rheinhboldt constraints algorithm used to solve differential-algebraic equations. Its geometrical content is exploited fully by implementing a Hamiltonian extension of it which is closer to Gotay-Nester presymplectic constraint algorithm used to solve singular Hamiltonian systems. Thus, given an optimal control problem whose optimal feedback is given in implicit form, a consistent set of equations is obtained describing the first order differential conditions of Pontryaguine's Maximum Principle. Such equations are shown to be Hamiltonian and the set of first class constraints corresponding to controls that are not determined, are obtained explicitly. The strength of the algorithm is shown by exhibiting a numerical implementation with partial feedback on the c...
Algorithm for predictive control implementation on fiber optic transmission lines
Andreev, Vladimir A.; Burdin, Vladimir A.; Voronkov, Andrey A.
2014-04-01
This paper presents the algorithm for predictive control implementation on fiber-optic transmission lines. In order to improve the maintenance of fiber optic communication lines, the algorithm prediction uptime optic communication cables have been worked out. It considers the results of scheduled preventive maintenance and database of various works on the track cable line during maintenance.
Distributed algorithm for controlling scaled-free polygonal formations
Garcia de Marina Peinado, Hector; Jayawardhana, Bayu; Cao, Ming
2017-01-01
This paper presents a distributed algorithm for controlling the deployment of a team of agents in order to form a broad class of polygons, including regular ones, where each agent occupies a corner of the polygon. The algorithm shares the properties from the popular distance- based rigid formation c
NOVEL POWER CONTROL GAME VIA PRICING ALGORITHM FOR COGNITIVE RADIOS
无
2008-01-01
To compensate the service providers who have paid billions of dollars to use spectrum and to satisfy secondary users’requirements in cognitive radios,a Non-cooperative Power Control Game and Pricing algorithm (NPGP) is proposed. Simulation results show that the proposed algorithm can regulate the secondary users’transmitter powers,optimally allocate radio resource and increase the total throughput effectively.
Visualizing Concurrency Control Algorithms for Real-Time Database Systems
Olusegun Folorunso
2008-11-01
Full Text Available This paper describes an approach to visualizing concurrency control (CC algorithms for real-time database systems (RTDBs. This approach is based on the principle of software visualization, which has been applied in related fields. The Model-View-controller (MVC architecture is used to alleviate the black box syndrome associated with the study of algorithm behaviour for RTDBs Concurrency Controls. We propose a Visualization "exploratory" tool that assists the RTDBS designer in understanding the actual behaviour of the concurrency control algorithms of choice and also in evaluating the performance quality of the algorithm. We demonstrate the feasibility of our approach using an optimistic concurrency control model as our case study. The developed tool substantiates the earlier simulation-based performance studies by exposing spikes at some points when visualized dynamically that are not observed using usual static graphs. Eventually this tool helps solve the problem of contradictory assumptions of CC in RTDBs.
Leendertse, A J; de Koning, G H P; Goudswaard, A N; Belitser, S V; Verhoef, M; de Gier, H J; Egberts, A C G; van den Bemt, P M L A
2013-10-01
Limited and conflicting evidence exists on the effect of a multicomponent pharmaceutical care intervention (i.e. medication review, involving collaboration between general practitioners (GPs), pharmacists and patients) on medication-related hospitalizations, survival, adverse drug events (ADEs) and quality of life. We aimed to investigate the effect of a multicomponent pharmaceutical care intervention on these outcomes. An open controlled multicentre study was conducted within primary care settings. Patients with a high risk on medication-related hospitalizations based on old age, use of five or more medicines, non-adherence and type of medication used were included. The intervention consisted of a patient interview, a review of the pharmacotherapy and the execution and follow-up evaluation of a pharmaceutical care plan. The patient's own pharmacist and GP carried out the intervention. The control group received usual care and was cared for by a GP other than the intervention GP. The primary outcome of the study was the frequency of hospital admissions related to medication within the study period of 12 months for each patient. Secondary outcomes were survival, quality of life and ADEs. 364 intervention and 310 control patients were included. Less medication-related hospital admissions were found in the intervention group (n = 6; 1·6%) than in the control group (n = 10; 3·2%) but the overall effect was not statistically significant (hazard ratio (HR) 0·50, 95% confidence interval (CI) 0·12-1·59). The secondary outcomes were not statistically significantly different either. The study was underpowered, which may explain the negative results. A post hoc analysis showed that the effect of the intervention was statistically significant for patients with five diseases or more: five diseases, HR 0·28 (95% bootstrap CI: 0·056-0·73) and eight diseases, HR 0·11 (95% CI: 0·013-0·34). A multicomponent pharmaceutical care intervention does not prevent medication
Study on Control Algorithm for Continuous Segments Trajectory Interpolation
SHI Chuan; YE Peiqing; LV Qiang
2006-01-01
In CNC machining, the complexity of the part contour causes a series of problems including the repeated start-stop of the motor, low machining efficiency, and poor machining quality. To relieve those problems, a new interpolation algorithm was put forward to realize the interpolation control of continuous sections trajectory. The relevant error analysis of the algorithm was also studied. The feasibility of the algorithm was proved by machining experiment using a laser machine to carve the interpolation trajectory in the CNC system GT100. This algorithm effectively improved the machining efficiency and the contour quality.
Development of Navigation Control Algorithm for AGV Using D* search Algorithm
Jeong Geun Kim
2013-06-01
Full Text Available In this paper, we present a navigation control algorithm for Automatic Guided Vehicles (AGV that move in industrial environments including static and moving obstacles using D* algorithm. This algorithm has ability to get paths planning in unknown, partially known and changing environments efficiently. To apply the D* search algorithm, the grid map represent the known environment is generated. By using the laser scanner LMS-151 and laser navigation sensor NAV-200, the grid map is updated according to the changing of environment and obstacles. When the AGV finds some new map information such as new unknown obstacles, it adds the information to its map and re-plans a new shortest path from its current coordinates to the given goal coordinates. It repeats the process until it reaches the goal coordinates. This algorithm is verified through simulation and experiment. The simulation and experimental results show that the algorithm can be used to move the AGV successfully to reach the goal position while it avoids unknown moving and static obstacles. [Keywords— navigation control algorithm; Automatic Guided Vehicles (AGV; D* search algorithm
Dynamic Algorithm for LQGPC Predictive Control
Hangstrup, M.; Ordys, A.W.; Grimble, M.J.
1998-01-01
In this paper the optimal control law is derived for a multi-variable state space Linear Quadratic Gaussian Predictive Controller (LQGPC). A dynamic performance index is utilized resulting in an optimal steady state controller. Knowledge of future reference values is incorporated into the control...
Pietrabissa, Antonio
2011-12-01
The admission control problem can be modelled as a Markov decision process (MDP) under the average cost criterion and formulated as a linear programming (LP) problem. The LP formulation is attractive in the present and future communication networks, which support an increasing number of classes of service, since it can be used to explicitly control class-level requirements, such as class blocking probabilities. On the other hand, the LP formulation suffers from scalability problems as the number C of classes increases. This article proposes a new LP formulation, which, even if it does not introduce any approximation, is much more scalable: the problem size reduction with respect to the standard LP formulation is O((C + 1)2/2 C ). Theoretical and numerical simulation results prove the effectiveness of the proposed approach.
Robust reactor power control system design by genetic algorithm
Lee, Yoon Joon; Cho, Kyung Ho; Kim, Sin [Cheju National University, Cheju (Korea, Republic of)
1997-12-31
The H{sub {infinity}} robust controller for the reactor power control system is designed by use of the mixed weight sensitivity. The system is configured into the typical two-port model with which the weight functions are augmented. Since the solution depends on the weighting functions and the problem is of nonconvex, the genetic algorithm is used to determine the weighting functions. The cost function applied in the genetic algorithm permits the direct control of the power tracking performances. In addition, the actual operating constraints such as rod velocity and acceleration can be treated as design parameters. Compared with the conventional approach, the controller designed by the genetic algorithm results in the better performances with the realistic constraints. Also, it is found that the genetic algorithm could be used as an effective tool in the robust design. 4 refs., 6 figs. (Author)
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.
Decentralized Control of Dynamic Routing with a Neural Network Algorithm
无
2000-01-01
A state-dependent routing algorithm based on the neural network model, which takes advantage of other dynamic routing algorithm for circuit-switched network, is given in [1]. But, the Algorithm in [1] is a centralized control model with complex O (N7), therefore, is difficult to realize by hardware. A simplified algorithm is put forward in this paper, in which routing can be controlled decentralizedly, and its complexity is reduced to O (10N3). Computer simulations are made in a fully connected test network with eight nodes. The results show that the centralized control model has very effective performance that can match RTNR, and the centralized control model is not as good as the centralized one but better than DAR-1.
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-...
Basic Research on Adaptive Model Algorithmic Control
1985-12-01
Control Conference. Richalet, J., A. Rault, J.L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial...pp.977-982. Richalet, J., A. Rault, J. L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial processes
Randomized Algorithms for Systems and Control: Theory and Applications
2008-05-01
IEIIT-CNR Randomized Algorithms for Systems and Control: Theory and Applications NATO LS Glasgow, Pamplona , Cleveland @RT 2008 Roberto Tempo IEIIT...Glasgow, Pamplona , Cleveland @RT 2008 roberto.tempo@polito.it IEIIT-CNR References R. Tempo, G. Calafiore and F. Dabbene, “Randomized Algorithms for...Analysis and Control of Uncertain Systems,” Springer-Verlag, London, 2005 R Tempo and H Ishii “Monte Carlo and Las Vegas NATO LS Glasgow, Pamplona , Cleveland
van Leeuwen, Y; Rombouts, E K; Kruithof, C J; van der Meer, F J M; Rosendaal, F R
2007-01-01
BACKGROUND: Efforts to improve dosing quality in oral anticoagulant control include the use of computer algorithms. As current algorithms are simplistic and give dosage proposals in a small fraction of patients, we developed an algorithm based on principles of system and control engineering that giv
Comparative Analysis of PSO Algorithms for PID Controller Tuning
ŠTIMAC Goranka; BRAUT Sanjin; ŽIGULIĆRoberto
2014-01-01
The active magnetic bearing(AMB) suspends the rotating shaft and maintains it in levitated position by applying controlled electromagnetic forces on the rotor in radial and axial directions. Although the development of various control methods is rapid, PID control strategy is still the most widely used control strategy in many applications, including AMBs. In order to tune PID controller, a particle swarm optimization(PSO) method is applied. Therefore, a comparative analysis of particle swarm optimization(PSO) algorithms is carried out, where two PSO algorithms, namely (1) PSO with linearly decreasing inertia weight(LDW-PSO), and (2) PSO algorithm with constriction factor approach(CFA-PSO), are independently tested for different PID structures. The computer simulations are carried out with the aim of minimizing the objective function defined as the integral of time multiplied by the absolute value of error(ITAE). In order to validate the performance of the analyzed PSO algorithms, one-axis and two-axis radial rotor/active magnetic bearing systems are examined. The results show that PSO algorithms are effective and easily implemented methods, providing stable convergence and good computational efficiency of different PID structures for the rotor/AMB systems. Moreover, the PSO algorithms prove to be easily used for controller tuning in case of both SISO and MIMO system, which consider the system delay and the interference among the horizontal and vertical rotor axes.
Comparative analysis of PSO algorithms for PID controller tuning
Štimac, Goranka; Braut, Sanjin; Žigulić, Roberto
2014-09-01
The active magnetic bearing(AMB) suspends the rotating shaft and maintains it in levitated position by applying controlled electromagnetic forces on the rotor in radial and axial directions. Although the development of various control methods is rapid, PID control strategy is still the most widely used control strategy in many applications, including AMBs. In order to tune PID controller, a particle swarm optimization(PSO) method is applied. Therefore, a comparative analysis of particle swarm optimization(PSO) algorithms is carried out, where two PSO algorithms, namely (1) PSO with linearly decreasing inertia weight(LDW-PSO), and (2) PSO algorithm with constriction factor approach(CFA-PSO), are independently tested for different PID structures. The computer simulations are carried out with the aim of minimizing the objective function defined as the integral of time multiplied by the absolute value of error(ITAE). In order to validate the performance of the analyzed PSO algorithms, one-axis and two-axis radial rotor/active magnetic bearing systems are examined. The results show that PSO algorithms are effective and easily implemented methods, providing stable convergence and good computational efficiency of different PID structures for the rotor/AMB systems. Moreover, the PSO algorithms prove to be easily used for controller tuning in case of both SISO and MIMO system, which consider the system delay and the interference among the horizontal and vertical rotor axes.
A Novel Parameter Tuning Algorithm for AQM-PI Controllers
Ma XiaoYan
2012-01-01
Full Text Available AQM is recognized as an active queue management mechanism to solve network congestion. As an easily implemented algorithm, PI controllers can effectively control the queue length of router. Based on indepth analysis of classical design methodologies towards PI controllers, this paper explicitly introduces a novel PI parameter tuning algorithm, which takes advantage of the relationship between PI parameters and control systems’ damping ratios and employs recursive bisection searching approaches to achieve an optimum damping ratio in terms of both steady-state and accuracy; performances of controlled queue length, thereby obtaining the best parameters of PI controllers. An experimental study is carried out to demonstrate the effectiveness of the proposed algorithm.
Anglada, Eva; Garmendia, Iñaki
2015-03-01
The design of the thermal control system of space vehicles, needed to maintain the equipment components into their admissible range of temperatures, is usually developed by means of thermal mathematical models. These thermal mathematical models need to be correlated with the equipment real behavior registered during the thermal test campaign, in order to adapt them to the real state of the vehicle "as built". The correlation of this type of mathematical models is a very complex task, usually based on manual procedures, which requires a big effort in time and cost. For this reason, the development of methodologies able to perform this correlation automatically, would be a key aspect in the improvement of the space vehicles thermal control design and validation. The implementation, study and validation of a genetic algorithm able to perform this type of correlation in an automatized way are presented in this paper. The study and validation of the algorithm have been performed based on a simplified model of a real space instrument. The algorithm is able to correlate thermal mathematical models in steady state and transient analyses, and it is also able to perform the simultaneous correlation of several cases, as for example hot and cold cases.
Fast Algorithms for Hybrid Control System Design
2007-11-02
Controls for Petri Nets with Unobservable Transitions", Proceedings of the 1997 American Control Conference, pp. 2354- 2358, Albuquerque, New Mexico , June...Automation Conference, April 20-25, 1997, 1997, Albuquerque New Mexico . - Invited Speaker at special session on "Intelligent Control Systems" at the 3rd...0 (11) Moreover, if either (hence, both) of these statements hold, then one controller that renders iVa (Ji(P, K)) < 7 is ffiven by A + B2J- aYaC2
Hybrid Active Noise Control using Adjoint LMS Algorithms
Nam, Hyun Do; Hong, Sik Ki [Dankook University (Korea, Republic of)
1998-07-01
A multi-channel hybrid active noise control(MCHANC) is derived by combining hybrid active noise control techniques and adjoint LMS algorithms, and this algorithm is applied to an active noise control system in a three dimensional enclosure. A MCHANC system uses feed forward and feedback filters simultaneously to cancel noises in an enclosure. The adjoint LMs algorithm, in which the error is filtered through an adjoint filter of the secondary channel, is also used to reduce the computational burden of adaptive filters. The overall attenuation performance and convergence characteristics of MCHANC algorithm is better than both multiple-channel feed forward algorithms and multiple-channel feedback algorithms. In a large enclosure, the acoustic reverberation can be very long, which means a very high order feed forward filter must be used to cancel the reverberation noises. Strong reverberation noises are generally narrow band and low frequency, which can be effectively predicted and canceled by a feedback adaptive filters. So lower order feed forward filter taps can be used in MCHANC algorithm which combines advantages of fast convergence and small excess mean square error. In this paper, computer simulations and real time implementations is carried out on a TMS320C31 processor to evaluate the performance of the MCHANC systems. (author). 11 refs., 11 figs., 1 tab.
Constraint Algorithm for Extremals in Optimal Control Problems
Barbero-Linan, Maria
2007-01-01
A characterization of different kinds of extremals of optimal control problems is given if we take an open control set. A well known constraint algorithm for implicit differential equations is adapted to the study of such problems. Some necessary conditions of Pontryagin's Maximum Principle determine the primary constraint submanifold for the algorithm. Some examples in the control literature, such as subRiemannian geometry and control-affine systems, are revisited to give, in a clear geometric way, a subset where the abnormal, normal and strict abnormal extremals stand.
Genetic Algorithm based PID controller for Frequency Regulation Ancillary services
Sandeep Bhongade
2010-12-01
Full Text Available In this paper, the parameters of Proportional, Integral and Derivative (PID controller for Automatic Generation Control (AGC suitable in restructured power system is tuned according to Generic Algorithms (GAs based performance indices. The key idea of the proposed method is to use the fitness function based on Area Control Error (ACE. The functioning of the proposed Genetic Algorithm based PID (GAPID controller has been demonstrated on a 75-bus Indian power system network and the results have been compared with those obtained by using Least Square Minimization method.
Wind turbine pitch control using ICPSO-PID algorithm
Xu, Chang; Tian, Qiangqiang; Shen, Wen Zhong
2013-01-01
of improved cooperative particle swarm optimization (ICPSO) and PID, subsequently, it was used to tune the pitch controller parameters; thus the difficulty in PID tuning was removed when a wind speed was above the rated speed. It was indicated that the proposed optimization algorithm can tune the pitch...... with ICPSO-PID algorithm has a smaller overshoot, a shorter tuning time and better robustness. The design method proposed in the paper can be applied in a practical electro-hydraulic pitch control system for WTG......., 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...
Boumediene ALLAOUA; Laoufi, Abdellah; Brahim GASBAOUI; Nasri, Abdelfatah; Abdessalam ABDERRAHMANI
2008-01-01
In this paper, an intelligent controller of the DC (Direct current) Motor drive is designed using fuzzy logic-genetic algorithms optimization. First, a controller is designed according to fuzzy rules such that the systems are fundamentally robust. To obtain the globally optimal values, parameters of the fuzzy controller are improved by genetic algorithms optimization model. Computer MATLAB work space demonstrate that the fuzzy controller associated to the genetic algorithms approach became ve...
Impulse position control algorithms for nonlinear systems
Sesekin, A. N., E-mail: sesekin@list.ru [Ural Federal University, 19 S. Mira, Ekaterinburg, 620002 (Russian Federation); Institute of Mathematics and Mechanics, Ural Division of Russian Academy of Sciences, 16 S. Kovalevskaya, Ekaterinburg, 620990 (Russian Federation); Nepp, A. N., E-mail: anepp@urfu.ru [Ural Federal University, 19 S. Mira, Ekaterinburg, 620002 (Russian Federation)
2015-11-30
The article is devoted to the formalization and description of impulse-sliding regime in nonlinear dynamical systems that arise in the application of impulse position controls of a special kind. The concept of trajectory impulse-sliding regime formalized as some limiting network element Euler polygons generated by a discrete approximation of the impulse position control This paper differs from the previously published papers in that it uses a definition of solutions of systems with impulse controls, it based on the closure of the set of smooth solutions in the space of functions of bounded variation. The need for the study of such regimes is the fact that they often arise when parry disturbances acting on technical or economic control system.
Impulse position control algorithms for nonlinear systems
Sesekin, A. N.; Nepp, A. N.
2015-11-01
The article is devoted to the formalization and description of impulse-sliding regime in nonlinear dynamical systems that arise in the application of impulse position controls of a special kind. The concept of trajectory impulse-sliding regime formalized as some limiting network element Euler polygons generated by a discrete approximation of the impulse position control This paper differs from the previously published papers in that it uses a definition of solutions of systems with impulse controls, it based on the closure of the set of smooth solutions in the space of functions of bounded variation. The need for the study of such regimes is the fact that they often arise when parry disturbances acting on technical or economic control system.
van der Lee, J H; Svrcek, W Y; Young, B R
2008-01-01
Model Predictive Control is a valuable tool for the process control engineer in a wide variety of applications. Because of this the structure of an MPC can vary dramatically from application to application. There have been a number of works dedicated to MPC tuning for specific cases. Since MPCs can differ significantly, this means that these tuning methods become inapplicable and a trial and error tuning approach must be used. This can be quite time consuming and can result in non-optimum tuning. In an attempt to resolve this, a generalized automated tuning algorithm for MPCs was developed. This approach is numerically based and combines a genetic algorithm with multi-objective fuzzy decision-making. The key advantages to this approach are that genetic algorithms are not problem specific and only need to be adapted to account for the number and ranges of tuning parameters for a given MPC. As well, multi-objective fuzzy decision-making can handle qualitative statements of what optimum control is, in addition to being able to use multiple inputs to determine tuning parameters that best match the desired results. This is particularly useful for multi-input, multi-output (MIMO) cases where the definition of "optimum" control is subject to the opinion of the control engineer tuning the system. A case study will be presented in order to illustrate the use of the tuning algorithm. This will include how different definitions of "optimum" control can arise, and how they are accounted for in the multi-objective decision making algorithm. The resulting tuning parameters from each of the definition sets will be compared, and in doing so show that the tuning parameters vary in order to meet each definition of optimum control, thus showing the generalized automated tuning algorithm approach for tuning MPCs is feasible.
Searching for the majority: algorithms of voluntary control.
Jin Fan
Full Text Available Voluntary control of information processing is crucial to allocate resources and prioritize the processes that are most important under a given situation; the algorithms underlying such control, however, are often not clear. We investigated possible algorithms of control for the performance of the majority function, in which participants searched for and identified one of two alternative categories (left or right pointing arrows as composing the majority in each stimulus set. We manipulated the amount (set size of 1, 3, and 5 and content (ratio of left and right pointing arrows within a set of the inputs to test competing hypotheses regarding mental operations for information processing. Using a novel measure based on computational load, we found that reaction time was best predicted by a grouping search algorithm as compared to alternative algorithms (i.e., exhaustive or self-terminating search. The grouping search algorithm involves sampling and resampling of the inputs before a decision is reached. These findings highlight the importance of investigating the implications of voluntary control via algorithms of mental operations.
Mkuzangwe, NNP
2015-08-01
Full Text Available This work implements two anomaly detection algorithms for detecting Transmission Control Protocol Synchronized (TCP SYN) flooding attack. The two algorithms are an adaptive threshold algorithm and a cumulative sum (CUSUM) based algorithm...
An Improved Force Feedback Control Algorithm for Active Tendons
Ligang Cai
2012-08-01
Full Text Available An active tendon, consisting of a displacement actuator and a co-located force sensor, has been adopted by many studies to suppress the vibration of large space flexible structures. The damping, provided by the force feedback control algorithm in these studies, is small and can increase, especially for tendons with low axial stiffness. This study introduces an improved force feedback algorithm, which is based on the idea of velocity feedback. The algorithm provides a large damping ratio for space flexible structures and does not require a structure model. The effectiveness of the algorithm is demonstrated on a structure similar to JPL-MPI. The results show that large damping can be achieved for the vibration control of large space structures.
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.
Manipulator Neural Network Control Based on Fuzzy Genetic Algorithm
无
2001-01-01
The three-layer forward neural networks are used to establish the inverse kinem a tics models of robot manipulators. The fuzzy genetic algorithm based on the line ar scaling of the fitness value is presented to update the weights of neural net works. To increase the search speed of the algorithm, the crossover probability and the mutation probability are adjusted through fuzzy control and the fitness is modified by the linear scaling method in FGA. Simulations show that the propo sed method improves considerably the precision of the inverse kinematics solutio ns for robot manipulators and guarantees a rapid global convergence and overcome s the drawbacks of SGA and the BP algorithm.
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.
Efficient evolutionary algorithms for optimal control
López Cruz, I.L.
2002-01-01
If optimal control problems are solved by means of gradient based local search methods, convergence to local solutions is likely. Recently, there has been an increasing interest in the use
OPTIMAL-TUNING OF PID CONTROLLER GAINS USING GENETIC ALGORITHMS
Ömer GÜNDOĞDU
2005-01-01
Full Text Available This paper presents a method of optimum parameter tuning of a PID controller to be used in driving an inertial load by a dc motor thorough a gearbox. Specifically, the method uses genetic algorithms to determine the optimum controller parameters by minimizing the sum of the integral of the squared error and the squared controller output deviated from its steady state value. The paper suggests the use of Ziegler-Nichols settings to form the intervals for the controller parameters in which the population to be formed. The results obtained from the genetic algorithms are compared with the ones from Ziegler-Nichols in both figures and tabular form. Comparatively better results are obtained in the genetic algorithm case.
An ellipsoid algorithm for probabilistic robust controller design
Kanev, S.K.; de Schutter, B.; Verhaegen, M.H.G.
2003-01-01
In this paper, a new iterative approach to probabilistic robust controller design is presented, which is applicable to any robust controller/filter design problem that can be represented as an LMI feasibility problem. Recently, a probabilistic Subgradient Iteration algorithm was proposed for solving
On flexible CAD of adaptive control and identification algorithms
Christensen, Anders; Ravn, Ole
1988-01-01
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...
A Decomposition Algorithm for Optimal Control of Distributed Energy System
Sokoler, Leo Emil; Edlund, Kristian; Standardi, Laura
2013-01-01
In economic model predictive control of distributed energy systems, the constrained optimal control problem can be expressed as a linear program with a block-angular structure. In this paper, we present an efficient Dantzig-Wolfe decomposition algorithm specifically tailored to problems...
Formal Verification of Congestion Control Algorithm in VANETs
Mohamad Yusof Darus
2013-04-01
Full Text Available A Vehicular Ad-Hoc Networks (VANETs is the technology that uses moving cars as nodes in a network to create a mobile network. VANETs turn every participating car into a wireless router, allowing cars of each other to connect and create a network with a wide range. VANETs are developed for enhancing the driving safety and comfort of automotive users. The VANETs can provide wide variety of service such as Intelligent Transportation System (ITS e.g. safety applications. Many of safety applications built in VANETs are required real-time communication with high reliability. One of the main challenges is to avoid degradation of communication channels in dense traffic network. Many of studies suggested that appropriate congestion control algorithms are essential to provide efficient operation of the network. However, most of congestion control algorithms are not really applicable to event-driven safety messages. In this paper we propose congestion control algorithm as solution to prevent congestion in VANETs environment. We propose a complete validation method and analyse the performance of our congestion control algorithms for event-driven safety messages in difference congested scenarios. The effectiveness of the proposed congestion control algorithm is evaluated through the simulation using Veins simulator.
Application of PI Control Algorithm to Discrete Manufacturing Systems
Guo Caifen; Wang Zongrong
2006-01-01
PI (proportional-integral) control algorithm is applied to control WIP (work-in-progress) in a discrete manufacturing system,where the cascade control of PI controllers is presented. It is in the frequency domain that the PI controller is designed with constraints on sensitivity options to ensure the stability and robustness of its parameters. A case is evaluated on a motorcycle engine crankcase production system, whose simulation results confirm that demand fluctuations can be compensated by PI controllers under a normal demand. PI controllers also possess low sensitivity to the distribution of production times.
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.
Parameter Optimization of Linear Quadratic Controller Based on Genetic Algorithm
LI Jimin; SHANG Chaoxuan; ZOU Minghu
2007-01-01
The selection of weighting matrix in design of the linear quadratic optimal controller is an important topic in the control theory. In this paper, an approach based on genetic algorithm is presented for selecting the weighting matrix for the optimal controller. Genetic algorithm is adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this algorithm, the fitness function is used to evaluate individuals and reproductive success varies with fitness. In the design of the linear quadratic optimal controller, the fitness function has relation to the anticipated step response of the system. Not only can the controller designed by this approach meet the demand of the performance indexes of linear quadratic controller, but also satisfy the anticipated step response of close-loop system. The method possesses a higher calculating efficiency and provides technical support for the optimal controller in engineering application. The simulation of a three-order single-input single-output (SISO) system has demonstrated the feasibility and validity of the approach.
TCP-ATCA: Improved Transmission Control Algorithm in Satellite Network
Liu Feng; Liu Hengna; Zhao Han
2008-01-01
An adaptive transmission control algorithm based on TCP (TCP-ATCA) is proposed to reduce the effects of long propagation de- lay and high link error rate of the satellite network on the performances. The flow control and the error recovery are differentiated by combined dynamic random early detection-explicit congestion notification (DRED-ECN) algorithm, and, moreover, the pertaining con- gestion control methods are used in TCP-ATCA to improve the throughput. By introducing the entire recovery algorithm, the unneces- sary congestion window decrease is reduced, and the throughput and fairness are improved. Simulation results show that, compared with TCP-Reno, TCP-ATCA provides a better throughput performance when the link capacity is higher (≥ 600 packet/s), and roughly the same when it is lower. At the same time, TCP-ATCA also increases fairness and reduces transmission delay.
Nonlinear system identification and control using state transition algorithm
Yang, Chunhua; Gui, Weihua
2012-01-01
This paper presents a novel optimization method named state transition algorithm (STA) to solve the problem of identification and control for nonlinear system. In the proposed algorithm, a solution to optimization problem is considered as a state, and the updating of a solution equates to the process of state transition, which makes the STA easy to understand and convenient to be implemented. First, the STA is applied to identify the optimal parameters of the estimated system with previously known structure. With the accurate estimated model, an off-line PID controller is then designed optimally by using the STA as well. Experimental results demonstrate the validity of the methodology, and comparison to STA with other optimization algorithms confirms that STA is a promising alternative method for system identification and control due to its stronger search ability, faster convergence speed and more stable performance.
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.
Singular formalism and admissible control of spacecraft with rotating flexible solar array
Lu Dongning; Liu Yiwu
2014-01-01
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 w...
A Traffic Prediction Algorithm for Street Lighting Control Efficiency
POPA Valentin
2013-01-01
Full Text Available This paper presents the development of a traffic prediction algorithm that can be integrated in a street lighting monitoring and control system. The prediction algorithm must enable the reduction of energy costs and improve energy efficiency by decreasing the light intensity depending on the traffic level. The algorithm analyses and processes the information received at the command center based on the traffic level at different moments. The data is collected by means of the Doppler vehicle detection sensors integrated within the system. Thus, two methods are used for the implementation of the algorithm: a neural network and a k-NN (k-Nearest Neighbor prediction algorithm. For 500 training cycles, the mean square error of the neural network is 9.766 and for 500.000 training cycles the error amounts to 0.877. In case of the k-NN algorithm the error increases from 8.24 for k=5 to 12.27 for a number of 50 neighbors. In terms of a root means square error parameter, the use of a neural network ensures the highest performance level and can be integrated in a street lighting control system.
Study of sequential optimal control algorithm smart isolation structure based on Simulink-S function
Liu, Xiaohuan; Liu, Yanhui
2017-01-01
The study of this paper focuses on smart isolation structure, a method for realizing structural vibration control by using Simulink simulation is proposed according to the proposed sequential optimal control algorithm. In the Simulink simulation environment, A smart isolation structure is used to compare the control effect of three algorithms, i.e., classical optimal control algorithm, linear quadratic gaussian control algorithm and sequential optimal control algorithm under the condition of sensor contaminated with noise. Simulation results show that this method can be applied to the simulation of sequential optimal control algorithm and the proposed sequential optimal control algorithm has a good ability of resisting the noise and better control efficiency.
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.
Position Control of Switched Reluctance Motor Using Super Twisting Algorithm
Muhammad Rafiq Mufti
2016-01-01
Full Text Available The inherent problem of chattering in traditional sliding mode control is harmful for practical application of control system. This paper pays a considerable attention to a chattering-free control method, that is, higher-order sliding mode (super twisting algorithm. The design of a position controller for switched reluctance motor is presented and its stability is assured using Lyapunov stability theorem. In order to highlight the advantages of higher-order sliding mode controller (HOSMC, a classical first-order sliding mode controller (FOSMC is also applied to the same system and compared. The simulation results reflect the effectiveness of the proposed technique.
Control optimization, stabilization and computer algorithms for aircraft applications
Athans, M. (Editor); Willsky, A. S. (Editor)
1982-01-01
The analysis and design of complex multivariable reliable control systems are considered. High performance and fault tolerant aircraft systems are the objectives. A preliminary feasibility study of the design of a lateral control system for a VTOL aircraft that is to land on a DD963 class destroyer under high sea state conditions is provided. Progress in the following areas is summarized: (1) VTOL control system design studies; (2) robust multivariable control system synthesis; (3) adaptive control systems; (4) failure detection algorithms; and (5) fault tolerant optimal control theory.
Cao,Jianzhong; Luo,Fei; Xu,Yuge; Huang,Jinqiu
2006-01-01
A new predictive control algorithm for Electromagnetic disturbance turntable measurement system is presented In this paper.This control algorithm has the advantages of quick reaction, high precision and strong robust. Simulation results show the effectiveness of the algorithm
Talukder, Mohammad Radwanur Rahman; Rutherford, Shannon; Chu, Cordia; Hieu Nguyen, Trung; Phung, Dung
2017-04-13
Drinking water in the Mekong Delta Region (MDR) is highly vulnerable to salinity intrusion and this problem is expected to increase with the projected climate change and sea level rise. Despite this, research on health effects of saline contaminated water is scarce in this region. This study examines the risk of hospital admission for hypertension in salinity-affected areas of the MDR. Cases and controls were obtained from national/provincial hospital admission records for 2013. The cases were adult patients whom hypertension (ICD10-code: I10-I15) was primary diagnosis for admission. Of the 13 provinces in the MDR, we identified seven as 'salinity exposed' and the remaining as 'non-exposed' areas. A multi-level logistic regression model was used to examine the association between salinity exposure and hypertension outcome. Of the total 573 650 hospital admissions, 22 382 (~3.9%) were hypertensive cases. The multi-level logistic model combining both individual and ecological factors showed a 9% increase in risk (95% CI: 3-14%) of hypertension admission among individuals in exposed areas compared to those in non-exposed areas. In order to develop and promote appropriate adaptation strategies, further research is recommended to identify the salt exposure pathways and consumption behaviours in the salinity exposed areas.
On flexible CAD of adaptive control and identification algorithms
Christensen, Anders; Ravn, Ole
1988-01-01
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 total redesign of the system within each sample. The necessary design parameters are evaluated and a decision vector is defined, from which the identification algorithm can be generated by the program. Using the decision vector, a decision-node tree structure is built up, where the nodes define...
A Review of Virtual Sensing Algorithms for Active Noise Control
Danielle Moreau
2008-11-01
Full Text Available Traditional local active noise control systems minimise the measured acoustic pressure to generate a zone of quiet at the physical error sensor location. The resulting zone of quiet is generally limited in size and this requires the physical error sensor be placed at the desired location of attenuation, which is often inconvenient. To overcome this, a number of virtual sensing algorithms have been developed for active noise control. Using the physical error signal, the control signal and knowledge of the system, these virtual sensing algorithms estimate the error signal at a location that is remote from the physical error sensor, referred to as the virtual location. Instead of minimising the physical error signal, the estimated error signal is minimised with the active noise control system to generate a zone of quiet at the virtual location. This paper will review a number of virtual sensing algorithms developed for active noise control. Additionally, the performance of these virtual sensing algorithms in numerical simulations and in experiments is discussed and compared.
Application of genetic algorithms to tuning fuzzy control systems
Espy, Todd; Vombrack, Endre; Aldridge, Jack
1993-01-01
Real number genetic algorithms (GA) were applied for tuning fuzzy membership functions of three controller applications. The first application is our 'Fuzzy Pong' demonstration, a controller that controls a very responsive system. The performance of the automatically tuned membership functions exceeded that of manually tuned membership functions both when the algorithm started with randomly generated functions and with the best manually-tuned functions. The second GA tunes input membership functions to achieve a specified control surface. The third application is a practical one, a motor controller for a printed circuit manufacturing system. The GA alters the positions and overlaps of the membership functions to accomplish the tuning. The applications, the real number GA approach, the fitness function and population parameters, and the performance improvements achieved are discussed. Directions for further research in tuning input and output membership functions and in tuning fuzzy rules are described.
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
An Hourglass Control Algorithm for Lagrangian Smooth Particle Hydrodynamics
Ganzenmüller, Georg C
2014-01-01
This paper presents a stabilization scheme which addresses the rank-deficiency problem in meshless collocation methods for solid mechanics. Specifically, Smooth-Particle Hydrodynamics (SPH) in the Total Lagrangian formalism is considered. This method is rank-deficient in the sense that the SPH approximation of the deformation gradient is not unique with respect to the positions of the integration points. The non-uniqueness can result in the formation of zero-energy modes. If undetected, these modes can grow and completely dominate the solution. Here, an algorithm is introduced, which effectively suppresses these modes in a fashion similar to hour-glass control mechanisms in Finite-Element methods. Simulations utilizing this control algorithm result exhibit much improved stability, accuracy, and error convergence properties. In contrast to an alternative method which eliminates zero-energy modes, namely the use of additional integration points, the here presented algorithm is easy to implement and computationa...
Application study of complex control algorithm for regenerative furnace temperature
Lusheng GE
2004-01-01
Altemative switch combustion mode of air and gas is adopted on the two sides of the regenerative furnace, its temperature is in uncontrolled state in the switching process and the switch period is generally 3 ～ 5 min. Thus, the conventional bi-cross limited combustion control method is no longer applicable to the object. This paper makes use of neutral network algorithm to adjust the static operating point. On this basis, fuzzy control strategy is used for the furnace temperature control. The actual application result shows that the control strategy is effective to solve the problem of the combustion control for regenerative furnace.
System control fuzzy neural sewage pumping stations using genetic algorithms
Владлен Николаевич Кузнецов
2015-06-01
Full Text Available It is considered the system of management of sewage pumping station with regulators based on a neuron network with fuzzy logic. Linguistic rules for the controller based on fuzzy logic, maintaining the level of effluent in the receiving tank within the prescribed limits are developed. The use of genetic algorithms for neuron network training is shown.
Efficient differential evolution algorithms for multimodal optmal control problems
Lopez Cruz, I.L.; Willigenburg, van L.G.; Straten, van G.
2003-01-01
Many methods for solving optimal control problems, whether direct or indirect, rely upon gradient information and therefore may converge to a local optimum. Global optimisation methods like Evolutionary algorithms, overcome this problem. In this work it is investigated how well novel and easy to und
Design of PID Controller Simulator based on Genetic Algorithm
Fahri VATANSEVER
2013-08-01
Full Text Available PID (Proportional Integral and Derivative controllers take an important place in the field of system controlling. Various methods such as Ziegler-Nichols, Cohen-Coon, Chien Hrones Reswick (CHR and Wang-Juang-Chan are available for the design of such controllers benefiting from the system time and frequency domain data. These controllers are in compliance with system properties under certain criteria suitable to the system. Genetic algorithms have become widely used in control system applications in parallel to the advances in the field of computer and artificial intelligence. In this study, PID controller designs have been carried out by means of classical methods and genetic algorithms and comparative results have been analyzed. For this purpose, a graphical user interface program which can be used for educational purpose has been developed. For the definite (entered transfer functions, the suitable P, PI and PID controller coefficients have calculated by both classical methods and genetic algorithms and many parameters and responses of the systems have been compared and presented numerically and graphically
Mohammad Marefati
2016-06-01
Full Text Available In this article, an optimized PID controller for a fuel cell is introduced. It should be noted that we did not compute the PID controller’s coefficients based on trial-and-error method; instead, imperialist competitive algorithms have been considered. At first, the problem will be formulated as an optimization problem and solved by the mentioned algorithm, and optimized results will be obtained for PID coefficients. Then one of the important kinds of fuel cells, called proton exchange membrane fuel cell, is introduced. In order to control the voltage of this fuel cell during the changes in the charges, an optimal controller is introduced, based on the imperialist competitive algorithm. In order to apply this algorithm, the problem is written as an optimization problem which includes objectives and constraints. To achieve the most desirable controller, this algorithm is used for problem solving. Simulations confirm the better performance of proposed PID controller.
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.
Recursive estimation algorithms for power controls of wireless communication networks
Gang George YIN; Chin-An TAN; Le Yi WANG; Chengzhong XU
2008-01-01
Power control problems for wireless communication networks are investigated in direct-sequence codedivision multiple-access(DS/CDMA)channels.It is shown that the underlying problem can be formulated as a constrained optimization problem in a stochastic framework.For effective solutions to this optimization problem in real time,recursive algorithms of stochastic approximation type are developed that can solve the problem with unknown system components.Under broad conditions,convergence of the algorithms is established by using weak convergence methods.
Control of the lighting system using a genetic algorithm
Čongradac Velimir D.
2012-01-01
Full Text Available The manufacturing, distribution and use of electricity are of fundamental importance for the social life and they have the biggest influence on the environment associated with any human activity. The energy needed for building lighting makes up 20-40% of the total consumption. This paper displays the development of the mathematical model and genetic algorithm for the control of dimmable lighting on problems of regulating the level of internal lighting and increase of energetic efficiency using daylight. A series of experiments using the optimization algorithm on the realized model confirmed very high savings in electricity consumption.
Acceleration of quantum optimal control theory algorithms with mixing strategies.
Castro, Alberto; Gross, E K U
2009-05-01
We propose the use of mixing strategies to accelerate the convergence of the common iterative algorithms utilized in quantum optimal control theory (QOCT). We show how the nonlinear equations of QOCT can be viewed as a "fixed-point" nonlinear problem. The iterative algorithms for this class of problems may benefit from mixing strategies, as it happens, e.g., in the quest for the ground-state density in Kohn-Sham density-functional theory. We demonstrate, with some numerical examples, how the same mixing schemes utilized in this latter nonlinear problem may significantly accelerate the QOCT iterative procedures.
Simulation and Tuning of PID Controllers using Evolutionary Algorithms
K.R.S. Narayanan
2012-10-01
Full Text Available 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 strategies have gained importance over other strategies because of their consistent performance over wide range of process models and their flexibility. The level control systems on Deaerator, Feed Water Heaters, and Condenser Hot well are critical to the proper operation of the units in Nuclear Power plants. For Precise control of level, available tuning technologies based on conventional optimization methods are found to be inadequate as these conventional methods are having limitations. To overcome the limitations, alternate tuning techniques based on Genetic Algorithm are emerging. This paper analyses the manual tuning techniques and compares the same with Genetic Algorithm tuning methods for tuning PID controllers for level control system and testing of the quality of process control in the simulation environment of PFBR Operator Training Simulator(OTS.
Ichihara, Maria Yury T; Rodrigues, Laura C; Santos, Carlos A S T; Teixeira, Maria da Glória L C; Barreto, Mauricio L
2015-07-01
Rotavirus has been the leading cause of severe cases of acute diarrhoea (AD) among children worldwide; however, in the same areas, a large reduction in AD related to rotavirus has been observed after the introduction of the rotavirus vaccine. In Brazil, where there is a high rotavirus vaccine coverage, AD caused by pathogens other than rotavirus is still a frequent cause of outpatient visits and hospitalisations among children under 5 years. A hospital-based case-control study enrolled children aged 4 to 24 months admitted to 10 hospitals from all five Brazilian Regions. Cases (n=1178) were children admitted with diarrhoea who tested negative for rotavirus in a stool sample. Controls (n=2515) were children admitted without diarrhoea, frequency matched to cases by sex and age group. We estimated odds ratios using logistic regression, in a hierarchical approach according to a previously defined conceptual framework. Population-attributable fractions (PAF) were estimated for each variable, each block and for all significant variables in the latter model adjusted. The factors studied accounted for 41% of the non-rotavirus AD hospital admissions and the main risk factors included lack of adequate excreta disposal (PAF=12%), untreated drinking water (PAF=11%) and a history of previous hospitalization due to AD (PAF=21%). Low socio-economic conditions, no public water supply, crowding and low weight-for-age made smaller contributions. These findings further our knowledge of risk factors associated with severe AD in the post-rotavirus vaccination era. We recommend further increase in coverage of basic sanitation, improvements in water quality and further expansion of primary healthcare coverage to reduce the occurrence of non-rotavirus severe diarrhoea and subsequent hospitalization of Brazilian children. © The Author 2015. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e
An Improved ARED Algorithm for Congestion Control of Network Transmission
Jianyong Chen
2010-01-01
Full Text Available In order to achieve high throughput and low average delay in computer network, it is necessary to stabilize the queue length and avoid oscillation or chaos phenomenon. In this paper, based on Adaptive Random Early Detection (ARED, an improved algorithm is proposed, which dynamically changes the range of maximum drop probability pmax according to different network scenarios and adjusts pmax to limit average queue size qave in a steady range. Moreover, exponential averaging weight w is adjusted based on linear stability condition to stabilize qave. A number of simulations show that the improved ARED algorithm can effectively stabilize the queue length and perform better than other algorithms in terms of stability and chaos control.
Admissibility of Linear Systems in Banach Spaces
GUO Fa-ming
2005-01-01
In this paper, infinite-time p-admissibility of unbounded operators is introduced and the Co-semigroup characterization of the infinite-time p-admissibility of unbounded observation operators is given. Moreover, the analogous result for the infinite-time p-admissibility of unbounded control operators is presented.
Boumediene ALLAOUA
2008-12-01
Full Text Available In this paper, an intelligent controller of the DC (Direct current Motor drive is designed using fuzzy logic-genetic algorithms optimization. First, a controller is designed according to fuzzy rules such that the systems are fundamentally robust. To obtain the globally optimal values, parameters of the fuzzy controller are improved by genetic algorithms optimization model. Computer MATLAB work space demonstrate that the fuzzy controller associated to the genetic algorithms approach became very strong, gives a very good results and possesses good robustness.
GENETIC ALGORITHM BASED PARAMETER TUNING OF PID CONTROLLER FOR COMPOSITION CONTROL SYSTEM
Bhawna Tandon
2011-08-01
Full Text Available A Composition control system is discussed in this paper in which the PID controller is tuned using Genetic Algorithm & Ziegler-Nichols Tuning Criteria. Tuning methods for PID controllers are very importantfor the process industries. Traditional methods such as Ziegler-Nichols method often do not provide adequate tuning. Genetic Algorithm (GA as an intelligent approach has also been widely used to tune the parameters of PID. Genetic algorithms are used to create an objective function that can evaluate the optimum PID gains based on the controlled systems overall error.
Quantum control using genetic algorithms in quantum communication: superdense coding
Domínguez-Serna, Francisco; Rojas, Fernando
2015-06-01
We present a physical example model of how Quantum Control with genetic algorithms is applied to implement the quantum superdense code protocol. We studied a model consisting of two quantum dots with an electron with spin, including spin-orbit interaction. The electron and the spin get hybridized with the site acquiring two degrees of freedom, spin and charge. The system has tunneling and site energies as time dependent control parameters that are optimized by means of genetic algorithms to prepare a hybrid Bell-like state used as a transmission channel. This state is transformed to obtain any state of the four Bell basis as required by superdense protocol to transmit two bits of classical information. The control process protocol is equivalent to implement one of the quantum gates in the charge subsystem. Fidelities larger than 99.5% are achieved for the hybrid entangled state preparation and the superdense operations.
Attitude-Control Algorithm for Minimizing Maneuver Execution Errors
Acikmese, Behcet
2008-01-01
A G-RAC attitude-control algorithm is used to minimize maneuver execution error in a spacecraft with a flexible appendage when said spacecraft must induce translational momentum by firing (in open loop) large thrusters along a desired direction for a given period of time. The controller is dynamic with two integrators and requires measurement of only the angular position and velocity of the spacecraft. The global stability of the closed-loop system is guaranteed without having access to the states describing the dynamics of the appendage and with severe saturation in the available torque. Spacecraft apply open-loop thruster firings to induce a desired translational momentum with an extended appendage. This control algorithm will assist this maneuver by stabilizing the attitude dynamics around a desired orientation, and consequently minimize the maneuver execution errors.
Congestion control algorithm in large-delay uncertain networks
Fengjie YIN; Yuanwei JING; Yuanjiu GONG
2007-01-01
Based on Smith-fuzzy controller,a new active queue management(AQM)algorithm adaptable to the large-delay uncertain networks is presented.It can compensate the negative impact on the queue stability caused by the large delay,and it also maintains strong robustness under the condition of dynamic network fluid.Its stability is proven through Lyapunov method.Simulation results demonstrated that this method enables the queue length to converge at a preset value quickly and keeps the queue oscillation small.the simulation results also show that the scheme is very robust to disturbance under various network conditions and large delay and,in particular,the algorithm proposed outperforms the conventional PI control and fuzzy control when the network parameters and network delay change.
Robotics, vision and control fundamental algorithms in Matlab
Corke, Peter
2017-01-01
Robotic vision, the combination of robotics and computer vision, involves the application of computer algorithms to data acquired from sensors. The research community has developed a large body of such algorithms but for a newcomer to the field this can be quite daunting. For over 20 years the author has maintained two open-source MATLAB® Toolboxes, one for robotics and one for vision. They provide implementations of many important algorithms and allow users to work with real problems, not just trivial examples. This book makes the fundamental algorithms of robotics, vision and control accessible to all. It weaves together theory, algorithms and examples in a narrative that covers robotics and computer vision separately and together. Using the latest versions of the Toolboxes the author shows how complex problems can be decomposed and solved using just a few simple lines of code. The topics covered are guided by real problems observed by the author over many years as a practitioner of both robotics and compu...
Algorithmic aspects of topology control problems for ad hoc networks
Liu, R. (Rui); Lloyd, E. L. (Errol L.); Marathe, M. V. (Madhav V.); Ramanathan, R. (Ram); Ravi, S. S.
2002-01-01
Topology control problems are concerned with the assignment of power values to nodes of an ad hoc network so that the power assignment leads to a graph topology satisfying some specified properties. This paper considers such problems under several optimization objectives, including minimizing the maximum power and minimizing the total power. A general approach leading to a polynomial algorithm is presented for minimizing maximum power for a class of graph properties, called monotone properties. The difficulty of generalizing the approach to properties that are not monoione is pointed out. Problems involving the minimization of total power are known to be NP-complete even for simple graph properties. A general approach that leads to an approximation algorithm for minimizing the total power for some monotone properties is presented. Using this approach, a new approximation algorithm for the problem of minimizing the total power for obtaining a 2-node-connected graph is obtained. It is shown that this algorithm provides a constant performance guarantee. Experimental results from an implementation of the approximation algorithm are also presented.
Online Optimal Controller Design using Evolutionary Algorithm with Convergence Properties
Yousef Alipouri
2014-06-01
Full Text Available Many real-world applications require minimization of a cost function. This function is the criterion that figures out optimally. In the control engineering, this criterion is used in the design of optimal controllers. Cost function optimization has difficulties including calculating gradient function and lack of information about the system and the control loop. In this article, for the first time, gradient memetic evolutionary programming is proposed for minimization of non-convex cost functions that have been defined in control engineering. Moreover, stability and convergence of the proposed algorithm are proved. Besides, it is modified to be used in online optimization. To achieve this, the sign of the gradient function is utilized. For calculating the sign of the gradient, there is no need to know the cost-function’s shape. The gradient functions are estimated by the algorithm. The proposed algorithm is used to design a PI controller for nonlinear benchmark system CSTR (Continuous Stirred Tank Reactor by online and off-line approaches.
Design and implementation of adaptive inverse control algorithm for a micro-hand control system
Wan-Cheng Wang
2014-01-01
Full Text Available The Letter proposes an online tuned adaptive inverse position control algorithm for a micro-hand. First, the configuration of the micro-hand is discussed. Next, a kinematic analysis of the micro-hand is investigated and then the relationship between the rotor position of micro-permanent magnet synchronous motor and the tip of the micro-finger is derived. After that, an online tuned adaptive inverse control algorithm, which includes an adaptive inverse model and an adaptive inverse control, is designed. The online tuned adaptive inverse control algorithm has better performance than the proportional–integral control algorithm does. In addition, to avoid damaging the object during the grasping process, an online force control algorithm is proposed here as well. An embedded micro-computer, cRIO-9024, is used to realise the whole position control algorithm and the force control algorithm by using software. As a result, the hardware circuit is very simple. Experimental results show that the proposed system can provide fast transient responses, good load disturbance responses, good tracking responses and satisfactory grasping responses.
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.
Genetic Algorithm Optimisation of PID Controllers for a Multivariable Process
Wael Alharbi
2017-03-01
Full Text Available This project is about the design of PID controllers and the improvement of outputs in multivariable processes. The optimisation of PID controller for the Shell oil process is presented in this paper, using Genetic Algorithms (GAs. Genetic Algorithms (GAs are used to automatically tune PID controllers according to given specifications. They use an objective function, which is specially formulated and measures the performance of controller in terms of time-domain bounds on the responses of closed-loop process.A specific objective function is suggested that allows the designer for a single-input, single-output (SISO process to explicitly specify the process performance specifications associated with the given problem in terms of time-domain bounds, then experimentally evaluate the closed-loop responses. This is investigated using a simple two-term parametric PID controller tuning problem. The results are then analysed and compared with those obtained using a number of popular conventional controller tuning methods. The intention is to demonstrate that the proposed objective function is inherently capable of accurately quantifying complex performance specifications in the time domain. This is something that cannot normally be employed in conventional controller design or tuning methods.Finally, the recommended objective function will be used to examine the control problems of Multi-Input-Multi-Output (MIMO processes, and the results will be presented in order to determine the efficiency of the suggested control system.
The influence of different generations of computer algorithms on diabetes control.
Beyer, J; Schrezenmeir, J; Schulz, G; Strack, T; Küstner, E; Schulz, G
1990-01-01
With all control schedules, the management of diabetes is possible using Skyler's algorithm. In general, those control algorithms which do not allow the individual adaptation to changing conditions lead to overinsulinisation. So-called meal-related algorithms do usually minimise the fluctuations in blood sugar. The introduction of self-adapting algorithms, detecting peripheral insulin resistance, may further improve metabolic diabetes control.
Nonimmigrant Admissions - Annual Report
Department of Homeland Security — Nonimmigrants are foreign nationals granted temporary admission into the United States. The major purposes for which nonimmigrant admission may be authorized include...
Tuning of a neuro-fuzzy controller by genetic algorithm.
Seng, T L; Bin Khalid, M; Yusof, R
1999-01-01
Due to their powerful optimization property, genetic algorithms (GAs) are currently being investigated for the development of adaptive or self-tuning fuzzy logic control systems. This paper presents a neuro-fuzzy logic controller (NFLC) where all of its parameters can be tuned simultaneously by GA. The structure of the controller is based on the radial basis function neural network (RBF) with Gaussian membership functions. The NFLC tuned by GA can somewhat eliminate laborious design steps such as manual tuning of the membership functions and selection of the fuzzy rules. The GA implementation incorporates dynamic crossover and mutation probabilistic rates for faster convergence. A flexible position coding strategy of the NFLC parameters is also implemented to obtain near optimal solutions. The performance of the proposed controller is compared with a conventional fuzzy controller and a PID controller tuned by GA. Simulation results show that the proposed controller offers encouraging advantages and has better performance.
The algorithms for control of heating massive material
Karol Kostúr
2008-03-01
Full Text Available In numerous technological processes a change on the output follows change on the input pending specific time. This time is called dead time and if this time is too large, it causes problems in the control. This contribution is aimed at analyzing the algorithms of discreet regulation of the systems with dead time. Verified were classical PID regulator and a regulator using Dead Beat method. The control was also tried with Dead interval method. The regulators were tested by simulation and in the electrical laboratory furnace. The task was to control the temperature inside the material heated by furnace power.
An Improvement of MPEG-4 Rate Control Algorithm
LU Zhaohua; LI Hua; LIU Jixing
2005-01-01
Frame skipping in low bit video coding could significantly reduce the visual quality of reconstructed video. At the same time, if the complexity of the video sequence remains high for a long period, then driving up the long term average bit rate, the only resort of MPEG-4 Q2 rate control algorithm results in using a high quantization scale, which shows a poor visual quality of the reconstructed video. This paper analyzes the main causes of frame skipping in current MPEG-4 frame rate control scheme, and presents a new rate control algorithm based on the quadratic R-D model over a CBR channel. Key features of the present work are: 1) the bits allocated to each P-frame or B-frame are in proportion to its distance from the end of this GOP, i.e. more bits are allocated to the frames that are nearer to their reference Ⅰ-frame; 2) the target buffer level is changeable in the GOP, at the end of each GOP(five P-frames or B-frames), the target buffer level is linearly reduced from 1/2 to 1/4 of buffer size, to other frames, the target buffer level is set to 1/2 of buffer size; 3) a selective and judicious use of the reduced resolution mode, in addition to a modulation of the quantization scale parameter, is to control the average long term bit rate. Experimental results with different video sequences of varied complexity, encoded at low bit rates show better efficacy of the proposed algorithm than MPEG-4 Q2 rate control scheme, and the experimental results also show that the improved algorithm has significantly reduced the number of frame skipping, increased the overall PSNR, and improved the perceptual quality.
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.
New Iterative Learning Control Algorithms Based on Vector Plots Analysis1）
XIESheng-Li; TIANSen-Ping; XIEZhen-Dong
2004-01-01
Based on vector plots analysis, this paper researches the geometric frame of iterativelearning control method. New structure of iterative learning algorithms is obtained by analyzingthe vector plots of some general algorithms. The structure of the new algorithm is different fromthose of the present algorithms. It is of faster convergence speed and higher accuracy. Simulationspresented here illustrate the effectiveness and advantage of the new algorithm.
Development of wind turbine control algorithms for industrial use
Van Engelen, T.G.; Van der Hooft, E.L; Schaak, P. [ECN Wind, Petten (Netherlands)
2001-09-01
A tool has been developed for design of industry-ready control algorithms. These pertain to the prevailing wind turbine type: variable speed, active pitch to vane. Main control objectives are rotor speed regulation, energy yield optimisation and structural fatigue reduction. These objectives are satisfied through individually tunable control loops. The split-up in loops for power control and damping of tower and drive-train resonance is allowed by the use of dedicated filters. Time domain simulation results from the design tool show high-performance power regulation by feed forward of the estimated wind speed and enhanced damping in sideward tower bending by generator torque control. The tool for control design has been validated through extensive test runs with the authorised aerodynamic code PHATAS-IV. 7 refs.
A neuro-fuzzy controlling algorithm for wind turbine
Li Lin [Tampere Univ. of Technology (Finland); Eriksson, J.T. [Tampere Univ. of Technology (Finland)
1995-12-31
The wind turbine control system is stochastic and nonlinear, offering a demanding field for different control methods. An improved and efficient controller will have great impact on the cost-effectiveness of the technology. In this article, a design method for a self-organizing fuzzy controller is discussed, which combines two popular computational intelligence techniques, neural networks and fuzzy logic. Based on acquisited dynamic parameters of the wind, it can effectively predict wind changes in speed and direction. Maximum power can always be extracted from the kinetic energy of the wind. Based on the stimulating experiments applying nonlinear dynamics to a `Variable Speed Fixed Angle` wind turbine, it is demonstrated that the proposed control model 3rd learning algorithm provide a predictable, stable and accurate performance. The robustness of the controller to system parameter variations and measurement disturbances is also discussed. (author)
Control strategy of maglev vehicles based on particle swarm algorithm
Hui Wang; Gang Shen; Jinsong Zhou
2014-01-01
Taking a single magnet levitation system as the object, a nonlinear numerical model of the vehicle-guide-way coupling system was established to study the levitation control strategies. According to the similarity in dynamics, the single magnet-guideway coupling system was simpli-fied into a magnet-suspended track system, and the corre-sponding hardware-in-loop test rig was set up using dSPACE. A full-state-feedback controller was developed using the levitation gap signal and the current signal, and controller parameters were optimized by particle swarm algorithm. The results from the simulation and the test rig show that, the proposed control method can keep the sys-tem stable by calculating the controller output with the full-state information of the coupling system, Step responses from the test rig show that the controller can stabilize the system within 0.15 s with a 2% overshot, and performs well even in the condition of violent external disturbances. Unlike the linear quadratic optimal method, the particle swarm algorithm carries out the optimization with the nonlinear controlled object included, and its optimized results make the system responses much better.
Fuzzy Controllers Based Multipath Routing Algorithm in MANET
Pi, Shangchao; Sun, Baolin
Mobile ad hoc networks (MANETs) consist of a collection of wireless mobile nodes which dynamically exchange data among themselves without the reliance on a fixed base station or a wired backbone network. Due to the limited transmission range of wireless network nodes, multiple hops are usually needed for a node to exchange information with any other node in the network. Multipath routing allows the establishment of multiple paths between a single source and single destination node. The multipath routing in mobile ad hoc networks is difficult because the network topology may change constantly, and the available alternative path is inherently unreliable. This paper introduces a fuzzy controllers based multipath routing algorithm in MANET (FMRM). The key idea of FMRM algorithm is to construct the fuzzy controllers with the help to reduce reconstructions in the ad hoc network. The simulation results show that the proposed approach is effective and efficient in applications to the MANETs. It is an available approach to multipath routing decision.
A Concurrency Control Algorithm in Multi-Version Multilevel DBMS
ZHANGMin; FENGDengguo
2005-01-01
The conventional transaction concurrency control theory and mechanisms are challenged in the context of a multilevel DBMS (Data base management system). Not only the correctness of transaction processing, namely the serializability of the transaction histories, but also the security properties should be followed. These requirements include diminishing the timing covert channels and preventing the starving problem in high-level transactions' unlimited waiting. In this paper we present a timestamp order based concurrency control algorithm that produce serializable histories by correctly combining all the 1SR histories generated by different level schedulers. We also provide an implementation scheduler algorithm based on snapshots. This approach is free from timing covert channels and transactions of different security levels have the same privilege to execute. In addition, this approach does not require the existence of a global trusted scheduler. Instead, it can be built on enhanced untrusted traditional multi-version schedulers, with the supplement of appropriate process towards read-down operations.
van den Bogert Sander CA
2011-01-01
Full Text Available Abstract Background Medication can be effective but can also be harmful and even cause hospital admissions. Medication review or pharmacotherapy review has often been proposed as a solution to prevent these admissions and to improve the effectiveness and safety of pharmacotherapy. However, most published randomised controlled trials on pharmacotherapy reviews showed no or little effect on morbidity and mortality. Therefore we designed the PHARM (Preventing Hospital Admissions by Reviewing Medication-study with the objective to study the effect of the total pharmaceutical care process on medication related hospital admissions and on adverse drug events, survival and quality of life. Methods/Design The PHARM-study is designed as a cluster randomised, controlled, multi-centre study in an integrated primary care setting. Patients with a high risk of a medication related hospital admission are included in the study with randomisation at GP (general practitioner level. We aim to include 14200 patients, 7100 in each arm, from at least 142 pharmacy practices. The intervention consists of a patient-centred, structured, pharmaceutical care process. This process consists of several steps, is continuous and occurrs over multiple encounters of patients and clinicians. The steps of this pharmaceutical care process are a pharmaceutical anamnesis, a review of the patient's pharmacotherapy, the formulation and execution of a pharmaceutical care plan combined with the monitoring and follow up evaluation of the care plan and pharmacotherapy. The patient's own pharmacist and GP carry out the intervention. The control group receives usual care. The primary outcome of the study is the frequency of hospital admissions related to medication within the study period of 12 months of each patient. The secondary outcomes are survival, quality of life, adverse drug events and severe adverse drug events. The outcomes will be analysed by using mixed-effects Cox models
Leendertse, Anne J; de Koning, Fred H P; Goudswaard, Alex N; Jonkhoff, Andries R; van den Bogert, Sander C A; de Gier, Han J; Egberts, Toine C G; van den Bemt, Patricia M L A
2011-01-07
Medication can be effective but can also be harmful and even cause hospital admissions. Medication review or pharmacotherapy review has often been proposed as a solution to prevent these admissions and to improve the effectiveness and safety of pharmacotherapy. However, most published randomised controlled trials on pharmacotherapy reviews showed no or little effect on morbidity and mortality. Therefore we designed the PHARM (Preventing Hospital Admissions by Reviewing Medication)-study with the objective to study the effect of the total pharmaceutical care process on medication related hospital admissions and on adverse drug events, survival and quality of life. The PHARM-study is designed as a cluster randomised, controlled, multi-centre study in an integrated primary care setting. Patients with a high risk of a medication related hospital admission are included in the study with randomisation at GP (general practitioner) level. We aim to include 14200 patients, 7100 in each arm, from at least 142 pharmacy practices.The intervention consists of a patient-centred, structured, pharmaceutical care process. This process consists of several steps, is continuous and occurs over multiple encounters of patients and clinicians. The steps of this pharmaceutical care process are a pharmaceutical anamnesis, a review of the patient's pharmacotherapy, the formulation and execution of a pharmaceutical care plan combined with the monitoring and follow up evaluation of the care plan and pharmacotherapy. The patient's own pharmacist and GP carry out the intervention. The control group receives usual care.The primary outcome of the study is the frequency of hospital admissions related to medication within the study period of 12 months of each patient. The secondary outcomes are survival, quality of life, adverse drug events and severe adverse drug events. The outcomes will be analysed by using mixed-effects Cox models. The PHARM-study is one of the largest controlled trials to
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...
A comparison of three self-tuning control algorithms developed for the Bristol-Babcock controller
Tapp, P.A.
1992-04-01
A brief overview of adaptive control methods relating to the design of self-tuning proportional-integral-derivative (PID) controllers is given. The methods discussed include gain scheduling, self-tuning, auto-tuning, and model-reference adaptive control systems. Several process identification and parameter adjustment methods are discussed. Characteristics of the two most common types of self-tuning controllers implemented by industry (i.e., pattern recognition and process identification) are summarized. The substance of the work is a comparison of three self-tuning proportional-plus-integral (STPI) control algorithms developed to work in conjunction with the Bristol-Babcock PID control module. The STPI control algorithms are based on closed-loop cycling theory, pattern recognition theory, and model-based theory. A brief theory of operation of these three STPI control algorithms is given. Details of the process simulations developed to test the STPI algorithms are given, including an integrating process, a first-order system, a second-order system, a system with initial inverse response, and a system with variable time constant and delay. The STPI algorithms` performance with regard to both setpoint changes and load disturbances is evaluated, and their robustness is compared. The dynamic effects of process deadtime and noise are also considered. Finally, the limitations of each of the STPI algorithms is discussed, some conclusions are drawn from the performance comparisons, and a few recommendations are made. 6 refs.
A comparison of three self-tuning control algorithms developed for the Bristol-Babcock controller
Tapp, P.A.
1992-04-01
A brief overview of adaptive control methods relating to the design of self-tuning proportional-integral-derivative (PID) controllers is given. The methods discussed include gain scheduling, self-tuning, auto-tuning, and model-reference adaptive control systems. Several process identification and parameter adjustment methods are discussed. Characteristics of the two most common types of self-tuning controllers implemented by industry (i.e., pattern recognition and process identification) are summarized. The substance of the work is a comparison of three self-tuning proportional-plus-integral (STPI) control algorithms developed to work in conjunction with the Bristol-Babcock PID control module. The STPI control algorithms are based on closed-loop cycling theory, pattern recognition theory, and model-based theory. A brief theory of operation of these three STPI control algorithms is given. Details of the process simulations developed to test the STPI algorithms are given, including an integrating process, a first-order system, a second-order system, a system with initial inverse response, and a system with variable time constant and delay. The STPI algorithms' performance with regard to both setpoint changes and load disturbances is evaluated, and their robustness is compared. The dynamic effects of process deadtime and noise are also considered. Finally, the limitations of each of the STPI algorithms is discussed, some conclusions are drawn from the performance comparisons, and a few recommendations are made. 6 refs.
Comparison of Adaptive Antenna Arrays Controlled by Gradient Algorithms
Z. Raida
1994-09-01
Full Text Available The paper presents the Simple Kalman filter (SKF that has been designed for the control of digital adaptive antenna arrays. The SKF has been applied to the pilot signal system and the steering vector one. The above systems based on the SKF are compared with adaptive antenna arrays controlled by the classical LMS and the Variable Step Size (VSS LMS algorithms and by the pure Kalman filter. It is shown that the pure Kalman filter is the most convenient for the control of the adaptive arrays because it does not require any a priori information about noise statistics and excels in high rate of convergence and low misadjustment. Extremely high computational requirements are drawback of this filter. Hence, if low computational power of signal processors is at the disposal, the SKF is recommended to be used. Computational requirements of the SKF are of the same order as the classical LMS algorithm exhibits. On the other hand, all the important features of the pure Kalman filter are inherited by the SKF. The paper shows that presented Kalman filters can be regarded as special gradient algorithms. That is why they can be compared with the LMS family.
New algorithm to control a cycle ergometer using electrical stimulation.
Petrofsky, J S
2003-01-01
Data were collected from four male subjects to determine the relationships between load, speed and muscle use during cycle ergometry. These data were then used to construct equations to govern the stimulation of muscle in paralysed individuals, during cycle ergometry induced by functional electrical stimulation (FES) of the quadriceps, gluteus maximus and hamstring muscles. The algorithm was tested on four subjects who were paralysed owing to a complete spinal cord injury between T4 and T11. Using the multivariate equation, the control of movement was improved, and work was accomplished that was double (2940 Nm min(-1) compared with 5880 Nm min(-1)) that of traditional FES cycle ergometry, when muscle stimulation was also controlled by electrical stimulation. Stress on the body, assessed by cardiac output, was increased almost two-fold during maximum work with the new algorithm (81 min(-1) compared with 15 l min(-1) with the new algorithm). These data support the concept that the limitation to workload that a person can achieve on FES cycle ergometry is in the control equations and not in the paralysed muscle.
control of a dc motor using fuzzy logic control algorithm
user
conditions such as changes in motor load demand, non- linearity ... Figure 1: Structure of a fuzzy logic controller (Source. [6]). A typical fuzzy logic ... mathematical modeling based on first principles; and via ..... applied. On the premise of these findings, it would be tactful in ... and Sugeno Type Fuzzy Inference Systems for Air.
李波; 杨从有; 武浩; 裴以建
2012-01-01
SaaS是一种基于网络的软件应用模式,是服务提供商将应用软件统一部署在自己的服务器上,用户根据自己的实际需要,通过互联网向服务提供商订购并支付自己所需的服务.在未来,SaaS模式是占主导地位的云服务模型.文中阐 述SaaS的基本概念,介绍了SaaS的参考结构以及服务流程,分析概括了不同类型的服务要求的接入控制策略,总结了不同性能要求作业的调度策略,最后结合已有的云计算环境下的SaaS接人控制和调度策略研究成果,展望了未来的研究方向和亟待解决的关键问题.%SaaS is a kind of network-based software application paradigm that service providers deploy their application software on their servers. Users order and pay for their actual services via the internet. In the future, the SaaS model will be the dominant cloud service model. It introduces the concept of SaaS , its architecture and its service processes, and analyzes the types of admission control and scheduling algorithms for different service and performance requirements. It also presents a summary of the current state-of-the-art of the admission control and scheduling algorithms for SaaS in cloud computing environments, a discussion on the future work and some crucial problems should be solved pressingly.
A Feedback Optimal Control Algorithm with Optimal Measurement Time Points
Felix Jost
2017-02-01
Full Text Available Nonlinear model predictive control has been established as a powerful methodology to provide feedback for dynamic processes over the last decades. In practice it is usually combined with parameter and state estimation techniques, which allows to cope with uncertainty on many levels. To reduce the uncertainty it has also been suggested to include optimal experimental design into the sequential process of estimation and control calculation. Most of the focus so far was on dual control approaches, i.e., on using the controls to simultaneously excite the system dynamics (learning as well as minimizing a given objective (performing. We propose a new algorithm, which sequentially solves robust optimal control, optimal experimental design, state and parameter estimation problems. Thus, we decouple the control and the experimental design problems. This has the advantages that we can analyze the impact of measurement timing (sampling independently, and is practically relevant for applications with either an ethical limitation on system excitation (e.g., chemotherapy treatment or the need for fast feedback. The algorithm shows promising results with a 36% reduction of parameter uncertainties for the Lotka-Volterra fishing benchmark example.
A nonlinear regression model-based predictive control algorithm.
Dubay, R; Abu-Ayyad, M; Hernandez, J M
2009-04-01
This paper presents a unique approach for designing a nonlinear regression model-based predictive controller (NRPC) for single-input-single-output (SISO) and multi-input-multi-output (MIMO) processes that are common in industrial applications. The innovation of this strategy is that the controller structure allows nonlinear open-loop modeling to be conducted while closed-loop control is executed every sampling instant. Consequently, the system matrix is regenerated every sampling instant using a continuous function providing a more accurate prediction of the plant. Computer simulations are carried out on nonlinear plants, demonstrating that the new approach is easily implemented and provides tight control. Also, the proposed algorithm is implemented on two real time SISO applications; a DC motor, a plastic injection molding machine and a nonlinear MIMO thermal system comprising three temperature zones to be controlled with interacting effects. The experimental closed-loop responses of the proposed algorithm were compared to a multi-model dynamic matrix controller (MPC) with improved results for various set point trajectories. Good disturbance rejection was attained, resulting in improved tracking of multi-set point profiles in comparison to multi-model MPC.
Comparison of Algorithms for Control of Loads for Voltage Regulation
Douglass, Philip James; Han, Xue; You, Shi
2014-01-01
Autonomous flexible loads can be utilized to regulate voltag e on low voltage feeders. This paper compares two algorithms for controllin g loads: a simple voltage droop, where load power consumption is a varied in proportio n to RMS voltage; and a normalized relative voltage droop, which modifies...... the simpl e voltage droop by subtracting the mean voltage value at the bus and dividing by the standard deviation. These two controllers are applied to hot water heaters simul ated in a simple residential feeder. The simulation results show that both controllers r educe the frequency of undervoltage events...
RATE-ADJUSTMENT ALGORITHM FOR AGGREGATE TCP CONGESTION CONTROL
P. TINNAKORNSRISUPHAP, ET AL
2000-09-01
The TCP congestion-control mechanism is an algorithm designed to probe the available bandwidth of the network path that TCP packets traverse. However, it is well-known that the TCP congestion-control mechanism does not perform well on networks with a large bandwidth-delay product due to the slow dynamics in adapting its congestion window, especially for short-lived flows. One promising solution to the problem is to aggregate and share the path information among TCP connections that traverse the same bottleneck path, i.e., Aggregate TCP. However, this paper shows via a queueing analysis of a generalized processor-sharing (GPS) queue with regularly-varying service time that a simple aggregation of local TCP connections together into a single aggregate TCP connection can result in a severe performance degradation. To prevent such a degradation, we introduce a rate-adjustment algorithm. Our simulation confirms that by utilizing our rate-adjustment algorithm on aggregate TCP, connections which would normally receive poor service achieve significant performance improvements without penalizing connections which already receive good service.
Mathematics Admission Test Remarks
Ideon Erge
2016-12-01
Full Text Available Since 2014, there have been admission tests in mathematics for applicants to the Estonian University of Life Sciences for Geodesy, Land Management and Real Estate Planning; Civil Engineering; Hydraulic Engineering and Water Pollution Control; Engineering and Technetronics curricula. According to admission criteria, the test must be taken by students who have not passed the specific mathematics course state exam or when the score was less than 20 points. The admission test may also be taken by those who wish to improve their state exam score. In 2016, there were 126 such applicants of whom 63 took the test. In 2015, the numbers were 129 and 89 and in 2014 150 and 47 accordingly. The test was scored on scale of 100. The arithmetic average of the score was 30.6 points in 2016, 29.03 in 2015 and 18.84 in 2014. The test was considered to be passed with 1 point in 2014 and 20 points in 2015 and 2016. We analyzed test results and gave examples of problems which were solved exceptionally well or not at all.
Iterative learning control algorithm for spiking behavior of neuron model
Li, Shunan; Li, Donghui; Wang, Jiang; Yu, Haitao
2016-11-01
Controlling neurons to generate a desired or normal spiking behavior is the fundamental building block of the treatment of many neurologic diseases. The objective of this work is to develop a novel control method-closed-loop proportional integral (PI)-type iterative learning control (ILC) algorithm to control the spiking behavior in model neurons. In order to verify the feasibility and effectiveness of the proposed method, two single-compartment standard models of different neuronal excitability are specifically considered: Hodgkin-Huxley (HH) model for class 1 neural excitability and Morris-Lecar (ML) model for class 2 neural excitability. ILC has remarkable advantages for the repetitive processes in nature. To further highlight the superiority of the proposed method, the performances of the iterative learning controller are compared to those of classical PI controller. Either in the classical PI control or in the PI control combined with ILC, appropriate background noises are added in neuron models to approach the problem under more realistic biophysical conditions. Simulation results show that the controller performances are more favorable when ILC is considered, no matter which neuronal excitability the neuron belongs to and no matter what kind of firing pattern the desired trajectory belongs to. The error between real and desired output is much smaller under ILC control signal, which suggests ILC of neuron’s spiking behavior is more accurate.
Control algorithm for multiscale flow simulations of water
Kotsalis, E. M.; Walther, Jens Honore; Kaxiras, E.
2009-01-01
. 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......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...... Communication, we extend a control algorithm, previously introduced for monatomic molecules, to the case of atomistic water and demonstrate the effectiveness of this approach. The proposed computational method is validated for the cases of equilibrium and Couette flow of water....
Control algorithm for multiscale flow simulations of water
Kotsalis, Evangelos M.; Walther, Jens H.; Kaxiras, Efthimios; Koumoutsakos, Petros
2009-04-01
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 Communication, we extend a control algorithm, previously introduced for monatomic molecules, to the case of atomistic water and demonstrate the effectiveness of this approach. The proposed computational method is validated for the cases of equilibrium and Couette flow of water.
Diversity Controlling Genetic Algorithm for Order Acceptance and Scheduling Problem
Cheng Chen
2014-01-01
Full Text Available Selection and scheduling are an important topic in production systems. To tackle the order acceptance and scheduling problem on a single machine with release dates, tardiness penalty, and sequence-dependent setup times, in this paper a diversity controlling genetic algorithm (DCGA is proposed, in which a diversified population is maintained during the whole search process through survival selection considering both the fitness and the diversity of individuals. To measure the similarity between individuals, a modified Hamming distance without considering the unaccepted orders in the chromosome is adopted. The proposed DCGA was validated on 1500 benchmark instances with up to 100 orders. Compared with the state-of-the-art algorithms, the experimental results show that DCGA improves the solution quality obtained significantly, in terms of the deviation from upper bound.
A computational algorithm for spacecraft control and momentum management
Dzielski, John; Bergmann, Edward; Paradiso, Joseph
1990-01-01
Developments in the area of nonlinear control theory have shown how coordinate changes in the state and input spaces of a dynamical system can be used to transform certain nonlinear differential equations into equivalent linear equations. These techniques are applied to the control of a spacecraft equipped with momentum exchange devices. An optimal control problem is formulated that incorporates a nonlinear spacecraft model. An algorithm is developed for solving the optimization problem using feedback linearization to transform to an equivalent problem involving a linear dynamical constraint and a functional approximation technique to solve for the linear dynamics in terms of the control. The original problem is transformed into an unconstrained nonlinear quadratic program that yields an approximate solution to the original problem. Two examples are presented to illustrate the results.
Combined Intelligent Control (CIC: An Intelligent decision making algorithm
Moteaal Asadi Shirzi
2008-11-01
Full Text Available The focus of this research is to introduce the concept of combined intelligent control (CIC as an effective architecture for decision making and control of intelligent agents and multi robot sets. Basically, the CIC is a combination of various architectures and methods from fields such as artificial intelligence, Distributed Artificial Intelligence (DAI, control and biological computing. Although any intelligent architecture may be very effective for some specific applications, it could be less for others. Therefore, CIC combines and arranges them in a way that the strengths of any approach cover the weaknesses of others. In this paper first, we introduce some intelligent architectures from a new aspect. Afterward, we offer the CIC by combining them. CIC has been executed in a multi agent set. In this set, robots must cooperate to perform some various tasks in a complex and nondeterministic environment with a low sensory feedback and relationship. In order to investigate, improve, and correct the combined intelligent control method, simulation software has been designed which will be presented and considered. To show the ability of the CIC algorithm as a distributed architecture, a central algorithm is designed and compared with the CIC.
A cooperative control algorithm for camera based observational systems.
Young, Joseph G.
2012-01-01
Over the last several years, there has been considerable growth in camera based observation systems for a variety of safety, scientific, and recreational applications. In order to improve the effectiveness of these systems, we frequently desire the ability to increase the number of observed objects, but solving this problem is not as simple as adding more cameras. Quite often, there are economic or physical restrictions that prevent us from adding additional cameras to the system. As a result, we require methods that coordinate the tracking of objects between multiple cameras in an optimal way. In order to accomplish this goal, we present a new cooperative control algorithm for a camera based observational system. Specifically, we present a receding horizon control where we model the underlying optimal control problem as a mixed integer linear program. The benefit of this design is that we can coordinate the actions between each camera while simultaneously respecting its kinematics. In addition, we further improve the quality of our solution by coupling our algorithm with a Kalman filter. Through this integration, we not only add a predictive component to our control, but we use the uncertainty estimates provided by the filter to encourage the system to periodically observe any outliers in the observed area. This combined approach allows us to intelligently observe the entire region of interest in an effective and thorough manner.
Time-Based Dithering Algorithm and Frame Rate Control Technique for STN LCD Controller
LEIJianming; ZOUXuechen
2004-01-01
Time-based dithering algorithm and Frame rate control (FRC) technique applied to the STN liquid crystal display controller are presented. The dithering unit performs time-based dithering algorithm on pixel data to advantageously increase smoothness of an image displayed. The frame rate control unit is responsive to the dithering unit and performs frame rate controlling to generate more gray-shades, which may reduce flicker and visual artifacts. Results show that the gray shades displayed on images can be up to 256 for monochrome STN LCD panels or 2563 colors for color STN LCD panels respectively by using timebased dithering algorithm and frame rate control technique if each encoded pixel data is 8 bits. The images displayed on the STN liquid crystal display can get desirable grayshades and very little flicker and visual artifacts.
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.
Adaptive and Reliable Control Algorithm for Hybrid System Architecture
Osama Abdel Hakeem Abdel Sattar
2012-01-01
Full Text Available A stand-alone system is defined as an autonomous system that supplies electricity without being connected to the electric grid. Hybrid systems combined renewable energy source, that are never depleted (such solar (photovoltaic (PV, wind, hydroelectric, etc. , With other sources of energy, like Diesel. If these hybrid systems are optimally designed, they can be more cost effective and reliable than single systems. However, the design of hybrid systems is complex because of the uncertain renewable energy supplies, load demands and the non-linear characteristics of some components, so the design problem cannot be solved easily by classical optimisation methods. The use of heuristic techniques, such as the genetic algorithms, can give better results than classical methods. This paper presents to a hybrid system control algorithm and also dispatches strategy design in which wind is the primary energy resource with photovoltaic cells. The dimension of the design (max. load is 2000 kW and the sources is implemented as flow 1500 kw from wind, 500 kw from solar and diesel 2000 kw. The main task of the preposed algorithm is to take full advantage of the wind energy and solar energy when it is available and to minimize diesel fuel consumption.
Navigation Algorithm Using Fuzzy Control Method in Mobile Robotics
Cviklovič Vladimír
2016-03-01
Full Text Available The issue of navigation methods is being continuously developed globally. The aim of this article is to test the fuzzy control algorithm for track finding in mobile robotics. The concept of an autonomous mobile robot EN20 has been designed to test its behaviour. The odometry navigation method was used. The benefits of fuzzy control are in the evidence of mobile robot’s behaviour. These benefits are obtained when more physical variables on the base of more input variables are controlled at the same time. In our case, there are two input variables - heading angle and distance, and two output variables - the angular velocity of the left and right wheel. The autonomous mobile robot is moving with human logic.
Application of Improved Genetic Algorithm in PID Controller Parameters Optimization
Ying Chen
2013-01-01
Full Text Available Ying Chen, Yong-jie Ma, Wen-xia Yun College of Physics and Electronic Engineering, Northwest Normal University, Anning Road no.967 ,Lanzhou,China,0931-7971503 e-mail:chenying1386685@126.com Abstract The setting and optimization of Proportion Integration Differentiation(PID parameters have been always the important study topics in the automatic control field. The current optimization design methods are often difficult to consider the system requirements for quickness ,reliability and robustness .So a method of PID controller parameters optimization based on Improved Genetic Algorithm(IGA is presented .Simulations with Matlab have proved that the control performance index based on IGA is better than that of the GA method and Z-N method, and is a method which has good practical value of the PID parameter setting and optimization .
Controlling chaos in unidimensional maps using macroevolutionary algorithms.
Marín, Jesús; Solé, Ricard V
2002-02-01
We introduce a simple search algorithm that explores the parameter of periodically perturbed discrete maps in order to find desired orbits through chaos control. The method has been applied to one-dimensional maps but is easily extendable to higher-dimensional systems. Here, we consider two types of chaos control involving proportional pulses in the system variables [Phys. Rev. Lett. 72, 1455 (1994)] and constant feedback [Phys. Rev. E 51, 6239 (1995)], the first case being presented in detail. It is shown that our method allows a rapid exploration of parameter space and the finding of high-fitness (i.e., controlled) solutions close to the target orbits, even when high periodicities are required.
A combined model reduction algorithm for controlled biochemical systems.
Snowden, Thomas J; van der Graaf, Piet H; Tindall, Marcus J
2017-02-13
Systems Biology continues to produce increasingly large models of complex biochemical reaction networks. In applications requiring, for example, parameter estimation, the use of agent-based modelling approaches, or real-time simulation, this growing model complexity can present a significant hurdle. Often, however, not all portions of a model are of equal interest in a given setting. In such situations methods of model reduction offer one possible approach for addressing the issue of complexity by seeking to eliminate those portions of a pathway that can be shown to have the least effect upon the properties of interest. In this paper a model reduction algorithm bringing together the complementary aspects of proper lumping and empirical balanced truncation is presented. Additional contributions include the development of a criterion for the selection of state-variable elimination via conservation analysis and use of an 'averaged' lumping inverse. This combined algorithm is highly automatable and of particular applicability in the context of 'controlled' biochemical networks. The algorithm is demonstrated here via application to two examples; an 11 dimensional model of bacterial chemotaxis in Escherichia coli and a 99 dimensional model of extracellular regulatory kinase activation (ERK) mediated via the epidermal growth factor (EGF) and nerve growth factor (NGF) receptor pathways. In the case of the chemotaxis model the algorithm was able to reduce the model to 2 state-variables producing a maximal relative error between the dynamics of the original and reduced models of only 2.8% whilst yielding a 26 fold speed up in simulation time. For the ERK activation model the algorithm was able to reduce the system to 7 state-variables, incurring a maximal relative error of 4.8%, and producing an approximately 10 fold speed up in the rate of simulation. Indices of controllability and observability are additionally developed and demonstrated throughout the paper. These provide
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.
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.
Micro-Turbine Generation Control System Optimization Using Evolutionary algorithm
Mohanraj B S
2014-10-01
Full Text Available Distribution systems management is becoming an increasingly complicated issue due to the introduction of new technologies, new energy trading strategies, and new deregulated environment. In the new deregulated energy market and considering the incentives coming from the technical and economical fields, it is reasonable to consider Distributed Generation (DG as a viable option to solve the lacking electric power supply problem. This paper presents a mathematical distribution system planning model considering three planning options to system expansion and to meet the load growth requirements with a reasonable price as well as the system power quality problems. DG is introduced as an attractive planning option in competition with voltage regulator devices and Interruptible load. This paper presents a dynamic modelling and simulation of a high speed single shaft micro-turbine generation (MTG system for grid connected operation and shows genetic algorithm (GA role in improvement of control system operation. The model is developed with the consideration of the main parts including: compressor-turbine, permanent magnet (PM generator, three phase bridge rectifier and inverter. The simulation results show the capability of Genetic Algorithm for controlling MTG system. The model is developed in Mat lab / Simulink.
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.
VST telescope dynamic analisys and position control algorithms
Schipani, P
2001-01-01
The VST (VLT Survey Telescope) is a 2.6 m class Alt-Az telescope to be installed on Cerro Paranal in the Atacama desert, Northern Chile, in the European Southern Observatory (ESO) site. The VST is a wide-field imaging facility planned to supply databases for the ESO Very Large Telescope (VLT) science and carry out stand-alone observations in the UV to I spectral range. So far no telescope has been dedicated entirely to surveys; the VST will be the first survey telescope to start the operation, as a powerful survey facility for the VLT observatory. This paper will focus on the axes motion control system. The dynamic model of the telescope will be analyzed, as well as the effect of the wind disturbance on the telescope performance. Some algorithms for the telescope position control will be briefly discussed.
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.
Algorithms to Solve Stochastic H2/H∞ Control with State-Dependent Noise
Ming Gao
2014-01-01
Full Text Available This paper is concerned with the algorithms which solve H2/H∞ control problems of stochastic systems with state-dependent noise. Firstly, the algorithms for the finite and infinite horizon H2/H∞ control of discrete-time stochastic systems are reviewed and studied. Secondly, two algorithms are proposed for the finite and infinite horizon H2/H∞ control of continuous-time stochastic systems, respectively. Finally, several numerical examples are presented to show the effectiveness of the algorithms.
Motion Control Algorithms for a Free-swimming Biomimetic Robot Fish
YUJun-Zhi; CHENEr-Kui; WANGShuo; TANMin
2005-01-01
A practical motion control strategy for a radio-controlled, 4-1ink and free-swimming biomimetic robot fish is presented. Based on control performance of the fish the fish's motion control task is decomposed into on-line speed control and orientation control. The speed control algorithm is implemented by using piecewise control, and orientation control is realized by fuzzy logic. Combining with step control and fuzzy control, a point-to-point (PTP) control algorithm is proposed and applied to the closed-loop experimental system that uses a vision-based position sensing subsystem to provide feedback. Experiments confirm the reliability and effectiveness of the presented algorithms.
Research of network topological control algorithm in mWSN
Xinlian Zhou
2011-10-01
Full Text Available Relying on this paper presented clustering mobile wireless sensor model, we use the topological control of the combination of the clustering hierarchical structure and sleep scheduling mechanism. Firstly, present a inner-cluster node scheduling algorithm solution of inner-cluster connectivity coverage problem, which can meet user’s expected coverage scale and high-efficiency, avoiding the influence of mobile node location. This algorithm based on coverage analysis theory, deducts smallest mobile nodes number of user’s expected coverage scale , realizes inner-cluster nodes optimal scheduling, which only select k nodes with higher energy and nearer close to fixed node, others should be sleeping. Consequently realizes the schedule of higher energy nodes round sleeping, and better adapt to the mobility of inner-cluster nodes. Then, the whole network use TDMA to uniformly divide the time slots to avoid the interrupt of inter-cluster and inner-cluster communication. The slot scheduling makes the half of cluster realize parallel work, and cross-layer design. Simulation result display by this schedule, EDG(Efficient Data Gathering decreases data delay, and largely relieves the burden of cluster-head, and has apparent energy-saving effect, and thinks about node’s mobility, can preferably suit to mobile wireless sensor network.
Comparative Analysis of Congestion Control Algorithms Using ns-2
Sanjeev Patel
2011-09-01
Full Text Available 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. We also included the comparative analysis of loss rate having different bandwidth for these algorithms.
Energy Optimal Control Strategy of PHEV Based on PMP Algorithm
Tiezhou Wu
2017-01-01
Full Text Available Under the global voice of “energy saving” and the current boom in the development of energy storage technology at home and abroad, energy optimal control of the whole hybrid electric vehicle power system, as one of the core technologies of electric vehicles, is bound to become a hot target of “clean energy” vehicle development and research. This paper considers the constraints to the performance of energy storage system in Parallel Hybrid Electric Vehicle (PHEV, from which lithium-ion battery frequently charges/discharges, PHEV largely consumes energy of fuel, and their are difficulty in energy recovery and other issues in a single cycle; the research uses lithium-ion battery combined with super-capacitor (SC, which is hybrid energy storage system (Li-SC HESS, working together with internal combustion engine (ICE to drive PHEV. Combined with PSO-PI controller and Li-SC HESS internal power limited management approach, the research proposes the PHEV energy optimal control strategy. It is based on revised Pontryagin’s minimum principle (PMP algorithm, which establishes the PHEV vehicle simulation model through ADVISOR software and verifies the effectiveness and feasibility. Finally, the results show that the energy optimization control strategy can improve the instantaneity of tracking PHEV minimum fuel consumption track, implement energy saving, and prolong the life of lithium-ion batteries and thereby can improve hybrid energy storage system performance.
A BPTT-like Min-Max Optimal Control Algorithm for Nonlinear Systems
Milić, Vladimir; Kasać, Josip; Majetić, Dubravko; Šitum, Željko
2010-09-01
This paper presents a conjugate gradient-based algorithm for feedback min-max optimal control of nonlinear systems. The algorithm has a backward-in-time recurrent structure similar to the back propagation through time (BPTT) algorithm. The control law is given as the output of the one-layer neural network. Main contribution of the paper includes the integration of BPTT techniques, conjugate gradient methods, Adams method for solving ODEs and automatic differentiation (AD), to provide an effective, novel algorithm for solving numerically optimally min-max control problems. The proposed algorithm is applied to the rotational/translational actuator (RTAC) nonlinear benchmark problem with control and state vector constraints.
Wavelet Adaptive Algorithm and Its Application to MRE Noise Control System
Zhang Yulin
2015-01-01
Full Text Available To address the limitation of conventional adaptive algorithm used for active noise control (ANC system, this paper proposed and studied two adaptive algorithms based on Wavelet. The twos are applied to a noise control system including magnetorheological elastomers (MRE, which is a smart viscoelastic material characterized by a complex modulus dependent on vibration frequency and controllable by external magnetic fields. Simulation results reveal that the Decomposition LMS algorithm (D-LMS and Decomposition and Reconstruction LMS algorithm (DR-LMS based on Wavelet can significantly improve the noise reduction performance of MRE control system compared with traditional LMS algorithm.
Model algorithm control using neural networks for input delayed nonlinear control system
Yuanliang Zhang; Kil To Chong
2015-01-01
The performance of the model algorithm control method is partial y based on the accuracy of the system’s model. It is diffi-cult to obtain a good model of a nonlinear system, especial y when the nonlinearity is high. Neural networks have the ability to“learn”the characteristics of a system through nonlinear mapping to rep-resent nonlinear functions as wel as their inverse functions. This paper presents a model algorithm control method using neural net-works for nonlinear time delay systems. Two neural networks are used in the control scheme. One neural network is trained as the model of the nonlinear time delay system, and the other one pro-duces the control inputs. The neural networks are combined with the model algorithm control method to control the nonlinear time delay systems. Three examples are used to il ustrate the proposed control method. The simulation results show that the proposed control method has a good control performance for nonlinear time delay systems.
A Cultural Algorithm for POMDPs from Stochastic Inventory Control
Prestwich, S.; Tarim, S.A.; Rossi, R.; Hnich, B.
2008-01-01
Reinforcement Learning algorithms such as SARSA with an eligibility trace, and Evolutionary Computation methods such as genetic algorithms, are competing approaches to solving Partially Observable Markov Decision Processes (POMDPs) which occur in many fields of Artificial Intelligence. A powerful fo
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...
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
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.
Perez C, B
2003-07-01
In this thesis work there are presented: a) The characteristics and main components used in an electronic system based on a Dsp guided to control applications of processes, b) The description of an algorithm of diffuse control whose objective is the regulation of neutron power in a model of the punctual kinetics of a nuclear research reactor type TRIGA, and c) The installation in language assembler and execution in real time of the control algorithm in the system based on a Dsp. With regard to the installation and execution of the algorithm, the reaches of the project have been delimited to the following: a) Readiness of the entrance values to the controller in specific registrations of the system Dsp, b) Conversion of the entrances to the numerical formats with those that one obtains the best acting in the control algorithm, c) Execution of the algorithm until the obtaining of the value of the controller's exit, and d) Placement of the result in specific registrations of the Dsp for their later reading for an external parallel interface. It is necessary to mention that the simulation of the punctual kinetics of a reactor type TRIGA in the Pc and its integration with the control system based on the one Dsp is had contemplated as continuation of this work and that one of those will constitute main activities in my project of master thesis. A brief description of the topics presented in this thesis is given next. In the chapter one it is presented a general description of the diffuse logic and some of their applications in the industry. The main characteristics of a Dsp are also presented that they make it different from a micro controller or a microprocessor of general purpose. In the chapter 2 details of the internal architecture of the Dsp TMS320CS0 of Texas Instruments that are not explained with detail in the manual of user of the same one. This chapter has as objective to understand the internal hardware of the Dsp that is used for to carry out the program
Debbarma, Sanjoy; Saikia, Lalit Chandra; Sinha, Nidul
2014-03-01
Present work focused on automatic generation control (AGC) of a three unequal area thermal systems considering reheat turbines and appropriate generation rate constraints (GRC). A fractional order (FO) controller named as I(λ)D(µ) controller based on crone approximation is proposed for the first time as an appropriate technique to solve the multi-area AGC problem in power systems. A recently developed metaheuristic algorithm known as firefly algorithm (FA) is used for the simultaneous optimization of the gains and other parameters such as order of integrator (λ) and differentiator (μ) of I(λ)D(µ) controller and governor speed regulation parameters (R). The dynamic responses corresponding to optimized I(λ)D(µ) controller gains, λ, μ, and R are compared with that of classical integer order (IO) controllers such as I, PI and PID controllers. Simulation results show that the proposed I(λ)D(µ) controller provides more improved dynamic responses and outperforms the IO based classical controllers. Further, sensitivity analysis confirms the robustness of the so optimized I(λ)D(µ) controller to wide changes in system loading conditions and size and position of SLP. Proposed controller is also found to have performed well as compared to IO based controllers when SLP takes place simultaneously in any two areas or all the areas. Robustness of the proposed I(λ)D(µ) controller is also tested against system parameter variations.
Celler, Branko; Varnfield, Marlien; Nepal, Surya; Sparks, Ross; Li, Jane; Jayasena, Rajiv
2017-09-08
Telemonitoring is becoming increasingly important for the management of patients with chronic conditions, especially in countries with large distances such as Australia. However, despite large national investments in health information technology, little policy work has been undertaken in Australia in deploying telehealth in the home as a solution to the increasing demands and costs of managing chronic disease. The objective of this trial was to evaluate the impact of introducing at-home telemonitoring to patients living with chronic conditions on health care expenditure, number of admissions to hospital, and length of stay (LOS). A before and after control intervention analysis model was adopted whereby at each location patients were selected from a list of eligible patients living with a range of chronic conditions. Each test patient was case matched with at least one control patient. Test patients were supplied with a telehealth vital signs monitor and were remotely managed by a trained clinical care coordinator, while control patients continued to receive usual care. A total of 100 test patients and 137 control patients were analyzed. Primary health care benefits provided to Australian patients were investigated for the trial cohort. Time series data were analyzed using linear regression and analysis of covariance for a period of 3 years before the intervention and 1 year after. There were no significant differences between test and control patients at baseline. Test patients were monitored for an average of 276 days with 75% of patients monitored for more than 6 months. Test patients 1 year after the start of their intervention showed a 46.3% reduction in rate of predicted medical expenditure, a 25.5% reduction in the rate of predicted pharmaceutical expenditure, a 53.2% reduction in the rate of predicted unscheduled admission to hospital, a 67.9% reduction in the predicted rate of LOS when admitted to hospital, and a reduction in mortality of between 41
Conrad, Finn; Zhou, Jianjun; Gabacik, Andrzej;
1998-01-01
Invited paper presents a new control algorithm based on feed-forward geometrical compensation strategy combined with adaptive feedback control.......Invited paper presents a new control algorithm based on feed-forward geometrical compensation strategy combined with adaptive feedback control....
AUTOMATION OF PLC PROGRAMMING WHEN IMPLEMENTING ALGORITHMS OF GUARANTEEING CONTROL
M. V. Levinskyi
2015-05-01
Full Text Available During developing programs for programmable logic controllers (PLCs the concept of model-oriented design is increasingly used. In particular, usage of Simulink PLC Coder is giving the opportunity to get SCL program codefrom Simulink model which contains certain dynamic elements. Then, for example, this SCL code can be transformed to functional blocks of the Simatic S7-300 (VIPA 300 PLC. This significantly reduces the timerequired to develop code in the language of SCL and reduces requirements for specialists’ qualification when developing control systems. In this article we provide an example of PLC programming automation whenimplementing algorithms of guaranteeing control (AGC. For certain types of technological processes it is typical to contain monotonically increasing function of the effectiveness with fixed one-way restriction in regulations. Forexample, in the grinders, presses, extruders the load current of the drive is stabilized using the change of feed. Energy efficiency of these plants will increase with increasing of the set point (SP to the controller of the drive loadcurrent stabilization loop. However, an increase in SP increases the probability of triggering appropriate protection, for example, as a result of random changes in the properties of raw materials. Therefore, to avoid this accident, thepower of driving motors is often unreasonably overrated. And in this case they are used with currents equal to the half of rated.Systems of guaranteeing control (SGC are used to solve the contradiction between the need to improvethe efficiency and increasing probability of an accident.
Active Control of Automotive Intake Noise under Rapid Acceleration using the Co-FXLMS Algorithm
Lee, Hae-Jin; Lee, Gyeong-Tae; Oh, Jae-Eung
The method of reducing automotive intake noise can be classified by passive and active control techniques. However, passive control has a limited effect of noise reduction at low frequency range (below 500 Hz) and is limited by the space of the engine room. However, active control can overcome these passive control limitations. The active control technique mostly uses the Least-Mean-Square (LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time, particularly when the Filtered-X LMS (FXLMS) algorithm is applied to an active noise control (ANC) system. However, the convergence performance of the LMS algorithm decreases significantly when the FXLMS algorithm is applied to the active control of intake noise under rapidly accelerating driving conditions. Therefore, in this study, the Co-FXLMS algorithm was proposed to improve the control performance of the FXLMS algorithm during rapid acceleration. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. The performance of the Co-FXLMS algorithm is presented in comparison with that of the FXLMS algorithm. Experimental results show that active noise control using Co-FXLMS is effective in reducing automotive intake noise during rapid acceleration.
Meysam Gheisarnezhad
2015-01-01
Full Text Available Fractional-order PID (FOPID controller is a generalization of standard PID controller using fractional calculus. Compared with the Standard PID controller, two adjustable variables “differential order” and “integral order” are added to the PID controller.Three tank system is a nonlinear multivariable process that is a good prototype of chemical industrial processes. Cuckoo Optimization Algorithm (COA, that was recently introduced has shown its good performance in optimization problems. In this study, Improved Cuckoo Optimization Algorithm (ICOA has been presented. The aim of the paper is to compare different controllers tuned with a Improved Cuckoo Optimization Algorithm (ICOA for Three Tank System. In order to compare the performance of the optimized FOPID controller with other controllers, Genetic Algorithm(GA, Particle swarm optimization (PSO, Cuckoo Optimization Algorithm (COA and Imperialist Competitive Algorithm (ICA.
Sukanta Nama
2016-04-01
Full Text Available Differential evolution (DE is an effective and powerful approach and it has been widely used in different environments. However, the performance of DE is sensitive to the choice of control parameters. Thus, to obtain optimal performance, time-consuming parameter tuning is necessary. Backtracking Search Optimization Algorithm (BSA is a new evolutionary algorithm (EA for solving real-valued numerical optimization problems. An ensemble algorithm called E-BSADE is proposed which incorporates concepts from DE and BSA. The performance of E-BSADE is evaluated on several benchmark functions and is compared with basic DE, BSA and conventional DE mutation strategy.
A Scheduling Algorithm Based on Communication Delay for Wireless Network Control System
Jun Wang
2012-09-01
Full Text Available In this study, a scheduling algorithm based on communication delay is proposed. This scheduling algorithm can tolerate delay of periodic communication tasks in wireless network control system. It resolves real-time problem of periodic communication tasks in wireless network control system and partly reduces overtime phenomenon of periodic communication tasks caused by delay in wireless network. At the same time, the nonlinear programming model is built for solving scheduling timetable based on the proposed scheduling algorithm. Finally, the performance of the proposed scheduling algorithm is evaluated by an application example. The statistics results show that it is more effective than traditional scheduling algorithms in wireless network control system.
One-of-a-kind Production: Controller Algorithms for Real-time Control
Ørum-Hansen, Claus
PhD Dissertation.IPS2-programme - Integrated Production Systems - supportet by the Danish Technical Research Council, STVF.The project is a part of the IPS 2 research Programmme - Integrated Production System - with focus on one-of-a-kind production.The research area deals with controller...... algorithms for real-time control. The work includes practical cases from ship design and manufacturing. Cooperation with Odense Steel Shipyard....
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.
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.
Fan, Qinqin; Yan, Xuefeng
2016-01-01
The performance of the differential evolution (DE) algorithm is significantly affected by the choice of mutation strategies and control parameters. Maintaining the search capability of various control parameter combinations throughout the entire evolution process is also a key issue. A self-adaptive DE algorithm with zoning evolution of control parameters and adaptive mutation strategies is proposed in this paper. In the proposed algorithm, the mutation strategies are automatically adjusted with population evolution, and the control parameters evolve in their own zoning to self-adapt and discover near optimal values autonomously. The proposed algorithm is compared with five state-of-the-art DE algorithm variants according to a set of benchmark test functions. Furthermore, seven nonparametric statistical tests are implemented to analyze the experimental results. The results indicate that the overall performance of the proposed algorithm is better than those of the five existing improved algorithms.
Neural Network Control Optimization based on Improved Genetic Algorithm
Zhaoyin Zhang
2013-08-01
Full Text Available To clearly find the effect of factors in network classification, the classification process of PNN is analyzed in detail. The XOR problem is described by PNN and the elements in PNN are also studied. Through simulations and combined with genetic algorithm, a novel PNN supervised learning algorithm is proposed. This algorithm introduces the classification accuracy of training samples to the network parameter learning. It adopts genetic algorithm to train the PNN smoothing parameter and hidden centric vector. Then the effects of hidden neuron number, hidden centric vector and smoothing parameter in PNN are verified in the experiments. It is shown that this algorithm is superior to other PNN learning algorithms on classification effect.
Wesselink, J.M.; Berkhoff, A.P.
2008-01-01
In this paper, real-time results are given for broadband multichannel active noise control using the regularized modified filtered-error algorithm. As compared to the standard filtered-error algorithm, the improved convergence rate and stability of the algorithm are obtained by using an inner-outer
Myles, Puja R; Nguyen-Van-Tam, Jonathan S; Lim, Wei Shen; Nicholson, Karl G; Brett, Stephen J; Enstone, Joanne E; McMenamin, James; Openshaw, Peter J M; Read, Robert C; Taylor, Bruce L; Bannister, Barbara; Semple, Malcolm G
2012-01-01
Triage tools have an important role in pandemics to identify those most likely to benefit from higher levels of care. We compared Community Assessment Tools (CATs), the CURB-65 score, and the Pandemic Medical Early Warning Score (PMEWS); to predict higher levels of care (high dependency--Level 2 or intensive care--Level 3) and/or death in patients at or shortly after admission to hospital with A/H1N1 2009 pandemic influenza. This was a case-control analysis using retrospectively collected data from the FLU-CIN cohort (1040 adults, 480 children) with PCR-confirmed A/H1N1 2009 influenza. Area under receiver operator curves (AUROC), sensitivity, specificity, positive predictive values and negative predictive values were calculated. CATs best predicted Level 2/3 admissions in both adults [AUROC (95% CI): CATs 0.77 (0.73, 0.80); CURB-65 0.68 (0.64, 0.72); PMEWS 0.68 (0.64, 0.73), ptools for predicting need for higher levels of care and/or mortality in patients of all ages.
Levenberg – Marquardt’s Algorithm used for PID Controller Parameters Optimization
Ahmed S. Abd El-Hamid; Ahmed H. Eissa; Aly M. Radwan
2015-01-01
The determination of parameters of controllers is an important problem in automatic control systems. In this paper, the Levenberg Marquardt (LM) Algorithm is used to effectively solve this problem with reasonable computational effort. The Levenberg Marquardt (LM) Algorithm for optimization of three term (PID) controller parameters with dynamic model of pH neutralization process is presented. The main goal is to show the merits of Levenberg Marquardt algorithm optimizat...
Global Convergence of Adaptive Generalized Predictive Controller Based on Least Squares Algorithm
张兴会; 陈增强; 袁著祉
2003-01-01
Some papers on stochastic adaptive control schemes have established convergence algorithm using a leastsquares parameters. With the popular application of GPC, global convergence has become a key problem in automatic control theory. However, now global convergence of GPC has not been established for algorithms in computing a least squares iteration. A generalized model of adaptive generalized predictive control is presented. The global convergebce is also given on the basis of estimating the parameters of GPC by least squares algorithm.
Woonki Na
2017-03-01
Full Text Available This paper presents an improved maximum power point tracking (MPPT algorithm using a fuzzy logic controller (FLC in order to extract potential maximum power from photovoltaic cells. The objectives of the proposed algorithm are to improve the tracking speed, and to simultaneously solve the inherent drawbacks such as slow tracking in the conventional perturb and observe (P and O algorithm. The performances of the conventional P and O algorithm and the proposed algorithm are compared by using MATLAB/Simulink in terms of the tracking speed and steady-state oscillations. Additionally, both algorithms were experimentally validated through a digital signal processor (DSP-based controlled-boost DC-DC converter. The experimental results show that the proposed algorithm performs with a shorter tracking time, smaller output power oscillation, and higher efficiency, compared with the conventional P and O algorithm.
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…
Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao
2016-01-01
In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…
High order single step time delay compensation algorithm for structural active control
王焕定; 耿淑伟; 王伟
2002-01-01
The optimal instantaneous high order single step algorithm for active control is first discussed andthen, the n + 1 time step controlling force vector of the instantaneous optimal algorithm is derived from way of ntime state vector. An estimating algorithm, is developed from this to solve the problem of active control withtime delay compensation. The estimating algorithm based on this high order single step β method (HSM) foun-dation, is proven by simulation and experiment analysis, to be a valid solution to problem of active control withtime delay compensation.
A topology control algorithm for preserving minimum-energy paths in wireless ad hoc networks
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 Self-tuning Fuzzy Queue Management Algorithm for Congestion Control
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.
无
2005-01-01
The Dynamic Matrix Control (DMC) algorithm for integral processes is investigated in this paper. The reason why the original DMC algorithm cannot be applied to these processes is analyzed. The shifting matrix is transformed into another form and the corresponding theorem is proved, then its applicable range is extended. Compared with other algorithms on the integral processes, this algorithm is more practical and simple to implement. Simulation results also prove its validity. Applying this algorithm, we succeed in the control of the boiler level system in power units.
A Congestion—point Orientd Congestion Control Algorithm for Resilient Packet Ring
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.
Hybrid genetic algorithm approach for selective harmonic control
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)
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.
An efficient artificial bee colony algorithm with application to nonlinear predictive control
Ait Sahed, Oussama; Kara, Kamel; Benyoucef, Abousoufyane; Laid Hadjili, Mohamed
2016-05-01
In this paper a constrained nonlinear predictive control algorithm, that uses the artificial bee colony (ABC) algorithm to solve the optimization problem, is proposed. The main objective is to derive a simple and efficient control algorithm that can solve the nonlinear constrained optimization problem with minimal computational time. Indeed, a modified version, enhancing the exploring and the exploitation capabilities, of the ABC algorithm is proposed and used to design a nonlinear constrained predictive controller. This version allows addressing the premature and the slow convergence drawbacks of the standard ABC algorithm, using a modified search equation, a well-known organized distribution mechanism for the initial population and a new equation for the limit parameter. A convergence statistical analysis of the proposed algorithm, using some well-known benchmark functions is presented and compared with several other variants of the ABC algorithm. To demonstrate the efficiency of the proposed algorithm in solving engineering problems, the constrained nonlinear predictive control of the model of a Multi-Input Multi-Output industrial boiler is considered. The control performances of the proposed ABC algorithm-based controller are also compared to those obtained using some variants of the ABC algorithms.
Saifullah Khalid
2016-09-01
Full Text Available Three conventional control constant instantaneous power control, sinusoidal current control, and synchronous reference frame techniques for extracting reference currents for shunt active power filters have been optimized using Fuzzy Logic control and Adaptive Tabu search Algorithm and their performances have been compared. Critical analysis of Comparison of the compensation ability of different control strategies based on THD and speed will be done, and suggestions will be given for the selection of technique to be used. The simulated results using MATLAB model are presented, and they will clearly prove the value of the proposed control method of aircraft shunt APF. The waveforms observed after the application of filter will be having the harmonics within the limits and the power quality will be improved.
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...
Fackler James C
2011-09-01
Full Text Available Abstract Background Children with viral respiratory infections who undergo general anesthesia are at increased risk of respiratory complications. We investigated the impact of RSV and influenza infection on perioperative outcomes in children undergoing general anesthesia. Methods We performed a retrospective case-control study. All patients under the age of 18 years who underwent general anesthesia at our institution with confirmed RSV or influenza infection diagnosed within 24 hours following induction between October 2002 and September 2008 were identified. Controls were randomly selected and were matched by surgical procedure, age, and time of year in a ratio of three controls per case. The primary outcome was postoperative length of stay (LOS. Results Twenty-four patients with laboratory-confirmed RSV or influenza who underwent general anesthesia prior to diagnosis of viral infection were identified and matched to 72 controls. Thirteen cases had RSV and 11 had influenza. The median postoperative LOS was three days (intra-quartile range 1 to 8 days for cases and two days (intra-quartile range 1 to 5 days for controls. Patients with influenza had a longer postoperative LOS (p Conclusions Our results suggest that children with evidence of influenza infection undergoing general anesthesia, even in the absence of symptoms previously thought to be associated with a high risk of complications, may have a longer postoperative hospital LOS when compared to matched controls. RSV and influenza infection was associated with an increased risk of unplanned PICU admission.
Novel postural control algorithm for control of multifunctional myoelectric prosthetic hands.
Segil, Jacob L; Weir, Richard F
2015-01-01
The myoelectric controller (MEC) remains a technological bottleneck in the development of multifunctional prosthetic hands. Current MECs require physiologically inappropriate commands to indicate intent and lack effectiveness in a clinical setting. Postural control schemes use surface electromyography signals to drive a cursor in a continuous two-dimensional domain that is then transformed into a hand posture. Here, we present a novel algorithm for a postural controller and test the efficacy of the system during two experiments with 11 total subjects. In the first experiment, we found that performance increased when a velocity cursor-control technique versus a position cursor-control technique was used. Also, performance did not change when using 3, 4, or 12 surface electrodes. In the second experiment, subjects commanded a six degree-of-freedom virtual hand into seven functional postures without training, with completion rates of 82 +/- 4%, movement times of 3.5 +/- 0.2 s, and path efficiencies of 45 +/- 3%. Subjects retained the ability to use the postural controller at a high level across days after a single 1 hr training session. Our results substantiate the novel algorithm for a postural controller as a robust and advantageous design for a MEC of multifunction prosthetic hands.
Morris, John S.
1983-01-01
Discusses the changing role of admissions officers which corresponds to the declining student enrollment rate. Looks at changes in higher education over the past 15 years, and considers such issues as marketing, consumerism, and integrity as they relate to college admissions. (WAS)
POUDYAL, N.
2011-02-01
Full Text Available In this paper a novel schedulability criteria is developed to provide Quality of Service (QoS guarantees in terms of both minimum available bandwidth and maximum tolerated packet delay as required by the real-time traffic class. The contribution makes use of a measurement based admission control scheme at the base station of the 802.16m based 4G IMT�advanced network by considering the effects of various kinds of delays including the channel access delay, queuing delay and MAC layer transmission delay on the system's end to end delay. The paper also provides a way for the mobile station to proactively increase the chances of success of bandwidth grants by predicting in advance whether its bandwidth request will be approved by the base station, and then modifying or suspending its bandwidth request in case the chances of success is not favorable at that instant.
Model predictive control algorithms and their application to a continuous fermenter
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.
STEREO MATCHING ALGORITHM BASED ON ILLUMINATION CONTROL TO IMPROVE THE ACCURACY
Rostam Affendi Hamzah; Haidi Ibrahim; Anwar Hasni Abu Hassan
2016-01-01
This paper presents a new method of pixel based stereo matching algorithm using illumination control. The state of the art algorithm for absolute difference (AD) works fast, but only precise at low texture areas. Besides, it is sensitive to radiometric distortions (i.e., contrast or brightness) and discontinuity areas. To overcome the problem, this paper proposes an algorithm that utilizes an illumination control to enhance the image quality of absolute difference (AD) matching. Thus, pixel i...
Performance of Concurrency Control Algorithms in Distributed Systems
1989-08-01
these processes then discover that they are chosen is a dilemma shared with mutual exclusion algorithms. Leader election is a special case of mutual...exclusion. In both leader election and mutual exclusion algorithms, some single process is chosen from among the other processes in the system. This...process is then granted spe- cial status: in mutual exclusion, the chosen process enters the critical section; in leader election , the chosen process
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.
Synthesis of sequential control algorithms for pneumatic drives controlled by monostable valves
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.
PEBB Feedback Control Low Library. Volume 1: Three-Phase Inverter Control Algorithms
1999-01-01
ship propulsion electrical loads are powered from a common set of prime movers. Presently, the current generation of PEBB-like devices include high-power, fast-switching, high-bandwidth dc-dc converters and dc-ac inverters. This report summarized the algorithms required to control a conventional three-phase inverter. First, implementation issues regarding the Sine-Triangle Pulse-Width-Modulation and Space-Vector Modulation are presented with an emphasis placed on digital realizations. Then, two current control schemes are documented via analysis, design example, and
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...
Algorithms and Complexity Analyses for Control of Singleton Attractors in Boolean Networks
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
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.
Implementation of Genetic Algorithm in Control Structure of Induction Motor A.C. Drive
BRANDSTETTER, P.
2014-11-01
Full Text Available Modern concepts of control systems with digital signal processors allow the implementation of time-consuming control algorithms in real-time, for example soft computing methods. The paper deals with the design and technical implementation of a genetic algorithm for setting proportional and integral gain of the speed controller of the A.C. drive with the vector-controlled induction motor. Important simulations and experimental measurements have been realized that confirm the correctness of the proposed speed controller tuned by the genetic algorithm and the quality speed response of the A.C. drive with changing parameters and disturbance variables, such as changes in load torque.
Self-learning Fuzzy Controllers Based On a Real-time Reinforcement Genetic Algorithm
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.
A guidance and control algorithm for scent tracking micro-robotic vehicle swarms
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.
An improved filter-u least mean square vibration control algorithm for aircraft framework.
Huang, Quanzhen; Luo, Jun; Gao, Zhiyuan; Zhu, Xiaojin; Li, Hengyu
2014-09-01
Active vibration control of aerospace vehicle structures is very a hot spot and in which filter-u least mean square (FULMS) algorithm is one of the key methods. But for practical reasons and technical limitations, vibration reference signal extraction is always a difficult problem for FULMS algorithm. To solve the vibration reference signal extraction problem, an improved FULMS vibration control algorithm is proposed in this paper. Reference signal is constructed based on the controller structure and the data in the algorithm process, using a vibration response residual signal extracted directly from the vibration structure. To test the proposed algorithm, an aircraft frame model is built and an experimental platform is constructed. The simulation and experimental results show that the proposed algorithm is more practical with a good vibration suppression performance.
An improved filter-u least mean square vibration control algorithm for aircraft framework
Huang, Quanzhen; Luo, Jun; Gao, Zhiyuan; Zhu, Xiaojin; Li, Hengyu
2014-09-01
Active vibration control of aerospace vehicle structures is very a hot spot and in which filter-u least mean square (FULMS) algorithm is one of the key methods. But for practical reasons and technical limitations, vibration reference signal extraction is always a difficult problem for FULMS algorithm. To solve the vibration reference signal extraction problem, an improved FULMS vibration control algorithm is proposed in this paper. Reference signal is constructed based on the controller structure and the data in the algorithm process, using a vibration response residual signal extracted directly from the vibration structure. To test the proposed algorithm, an aircraft frame model is built and an experimental platform is constructed. The simulation and experimental results show that the proposed algorithm is more practical with a good vibration suppression performance.
Pyragas, V. [Semiconductor Physics Institute, Center for Physical Sciences and Technology, A. Gostauto 11, LT-01108 Vilnius (Lithuania); Pyragas, K. [Semiconductor Physics Institute, Center for Physical Sciences and Technology, A. Gostauto 11, LT-01108 Vilnius (Lithuania)
2011-10-24
We propose a simple adaptive delayed feedback control algorithm for stabilization of unstable periodic orbits with unknown periods. The state dependent time delay is varied continuously towards the period of controlled orbit according to a gradient-descent method realized through three simple ordinary differential equations. We demonstrate the efficiency of the algorithm with the Roessler and Mackey-Glass chaotic systems. The stability of the controlled orbits is proven by computation of the Lyapunov exponents of linearized equations. -- Highlights: → A simple adaptive modification of the delayed feedback control algorithm is proposed. → It enables the control of unstable periodic orbits with unknown periods. → The delay time is varied continuously according to a gradient descend method. → The algorithm is embodied by three simple ordinary differential equations. → The validity of the algorithm is proven by computation of the Lyapunov exponents.
Puja R Myles
Full Text Available Triage tools have an important role in pandemics to identify those most likely to benefit from higher levels of care. We compared Community Assessment Tools (CATs, the CURB-65 score, and the Pandemic Medical Early Warning Score (PMEWS; to predict higher levels of care (high dependency--Level 2 or intensive care--Level 3 and/or death in patients at or shortly after admission to hospital with A/H1N1 2009 pandemic influenza. This was a case-control analysis using retrospectively collected data from the FLU-CIN cohort (1040 adults, 480 children with PCR-confirmed A/H1N1 2009 influenza. Area under receiver operator curves (AUROC, sensitivity, specificity, positive predictive values and negative predictive values were calculated. CATs best predicted Level 2/3 admissions in both adults [AUROC (95% CI: CATs 0.77 (0.73, 0.80; CURB-65 0.68 (0.64, 0.72; PMEWS 0.68 (0.64, 0.73, p<0.001] and children [AUROC: CATs 0.74 (0.68, 0.80; CURB-65 0.52 (0.46, 0.59; PMEWS 0.69 (0.62, 0.75, p<0.001]. CURB-65 and CATs were similar in predicting death in adults with both performing better than PMEWS; and CATs best predicted death in children. CATs were the best predictor of Level 2/3 care and/or death for both adults and children. CATs are potentially useful triage tools for predicting need for higher levels of care and/or mortality in patients of all ages.
A Hierarchical Algorithm for Integrated Scheduling and Control With Applications to Power Systems
Sokoler, Leo Emil; Dinesen, Peter Juhler; Jørgensen, John Bagterp
2016-01-01
The contribution of this paper is a hierarchical algorithm for integrated scheduling and control via model predictive control of hybrid systems. The controlled system is a linear system composed of continuous control, state, and output variables. Binary variables occur as scheduling decisions...... portfolio case study show that the hierarchical algorithm reduces the computation to solve the OCP by several orders of magnitude. The improvement in computation time is achieved without a significant increase in the overall cost of operation....
A novel adaptive joint power control algorithm with channel estimation in a CDMA cellular system
无
2005-01-01
Joint power control has advantages of multi-user detection and power control; and it can combat the multi-access interference and the near-far problem. A novel adaptive joint power control algorithm with channel estimation in a CDMA cellular system was designed. Simulation results show that the algorithm can control the power not only quickly but also precisely with a time change. The method is useful for increasing system capacity.
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.
A.J. Leendertse (Anne); F.H.P. de Koning (Fred); A.N. Goudswaard (Alex); A.R. Jonkhoff (Andries); S.C.A. van den Bogert; H.J. de Gier (Han); T.C.G. Egberts (Toine); P.M.L.A. van den Bemt (Patricia)
2011-01-01
textabstractBackground: Medication can be effective but can also be harmful and even cause hospital admissions. Medication review or pharmacotherapy review has often been proposed as a solution to prevent these admissions and to improve the effectiveness and safety of pharmacotherapy. However, most
Leendertse, Anne J.; de Koning, Fred H. P.; Goudswaard, Alex N.; Jonkhoff, Andries R.; van den Bogert, Sander C. A.; de Gier, Han J.; Egberts, Toine C. G.; van den Bemt, Patricia M. L. A.
2011-01-01
Background: Medication can be effective but can also be harmful and even cause hospital admissions. Medication review or pharmacotherapy review has often been proposed as a solution to prevent these admissions and to improve the effectiveness and safety of pharmacotherapy. However, most published
Distributed Multitarget Probabilistic Coverage Control Algorithm for Wireless Sensor Networks
Ying Tian
2014-01-01
Full Text Available This paper is concerned with the problem of multitarget coverage based on probabilistic detection model. Coverage configuration is an effective method to alleviate the energy-limitation problem of sensors. Firstly, considering the attenuation of node’s sensing ability, the target probabilistic coverage problem is defined and formalized, which is based on Neyman-Peason probabilistic detection model. Secondly, in order to turn off redundant sensors, a simplified judging rule is derived, which makes the probabilistic coverage judgment execute on each node locally. Thirdly, a distributed node schedule scheme is proposed for implementing the distributed algorithm. Simulation results show that this algorithm is robust to the change of network size, and when compared with the physical coverage algorithm, it can effectively minimize the number of active sensors, which guarantees all the targets γ-covered.
Algorithms and Methods for High-Performance Model Predictive Control
Frison, Gianluca
routines employed in the numerical tests. The main focus of this thesis is on linear MPC problems. In this thesis, both the algorithms and their implementation are equally important. About the implementation, a novel implementation strategy for the dense linear algebra routines in embedded optimization...... is proposed, aiming at improving the computational performance in case of small matrices. About the algorithms, they are built on top of the proposed linear algebra, and they are tailored to exploit the high-level structure of the MPC problems, with special care on reducing the computational complexity....
CAS algorithm-based optimum design of PID controller in AVR system
Zhu Hui [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China); Key Laboratory of Network and Information Attack and Defence Technology of Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876 (China); National Engineering Laboratory for Disaster Backup and Recovery, Beijing 100876 (China)], E-mail: zhuhui05608@hotmail.com; Li Lixiang; Zhao Ying; Guo Yu; Yang Yixian [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China); Key Laboratory of Network and Information Attack and Defence Technology of Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876 (China); National Engineering Laboratory for Disaster Backup and Recovery, Beijing 100876 (China)
2009-10-30
This paper presents a novel design method for determining the optimal PID controller parameters of an automatic voltage regulator (AVR) system using the chaotic ant swarm (CAS) algorithm. In the tuning process of parameters, the CAS algorithm is iterated to give the optimal parameters of the PID controller based on the fitness theory, where the position vector of each ant in the CAS algorithm corresponds to the parameter vector of the PID controller. The proposed CAS-PID controllers can ensure better control system performance with respect to the reference input in comparison with GA-PID controllers. Numerical simulations are provided to verify the effectiveness and feasibility of PID controller based on CAS algorithm.
A Novel Control Algorithm for Static Series Compensators by Use of PQR Instantaneous Power Theory
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...... in coordinates is very simple and clear, has better steady state and dynamic performance. The controlled variables in coordinates are then inversely transformed to the original coordinates without time delay, generating control signals to SSCs. The control algorithm can be used for various kinds of SSCs...... 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-q-r p-q-r p-q-r p...
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.
Deyuan Meng
2014-05-01
Full Text Available The dynamics of pneumatic systems are highly nonlinear, and there normally exists a large extent of model uncertainties; the precision motion trajectory tracking control of pneumatic cylinders is still a challenge. In this paper, two typical nonlinear controllers—adaptive controller and deterministic robust controller—are constructed firstly. Considering that they have both benefits and limitations, an adaptive robust controller (ARC is further proposed. The ARC is a combination of the first two controllers; it employs online recursive least squares estimation (RLSE to reduce the extent of parametric uncertainties, and utilizes the robust control method to attenuate the effects of parameter estimation errors, unmodeled dynamics, and disturbances. In order to solve the conflicts between the robust control design and the parameter adaption law design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Theoretically, ARC possesses the advantages of the adaptive control and the deterministic robust control, and thus an even better tracking performance can be expected. Extensive comparative experimental results are presented to illustrate the achievable performance of the three proposed controllers and their performance robustness to the parameter variations and sudden disturbance.
Development of adaptive IIR filtered-e LMS algorithm for active noise control
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.
H~ Estimation Approach to Active Noise Control: Theory, Algorithm and Real-Time Implementation
Bambang Riyanto
2003-11-01
Full Text Available This paper presents an H¥ estimation approach to active control of acoustic noise inside an enclosure. It is shown how H¥ filter theory and algorithm can be effectively applied to active noise control to provide important robustness property. Real-time implementation of the algorithm is performed on Digital Signal Processor. Experimental comparison to conventional FxLMS algorithm for active noise control is presented for both single channel and multichannel cases. While providing some new results, this paper also serves as a brief review on H¥ filter theory and on active noise control.
Controller Parameter Optimization for Nonlinear Systems Using Enhanced Bacteria Foraging Algorithm
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.
Development of real-time plasma analysis and control algorithms for the TCV tokamak using SIMULINK
Felici, F., E-mail: f.felici@tue.nl [École Polytechnique Fédérale de Lausanne (EPFL), Centre de Recherches en Physique des Plasmas, Association EURATOM-Suisse, 1015 Lausanne (Switzerland); Eindhoven University of Technology, Department of Mechanical Engineering, Control Systems Technology Group, P.O. Box 513, 5600MB Eindhoven (Netherlands); Le, H.B.; Paley, J.I.; Duval, B.P.; Coda, S.; Moret, J.-M.; Bortolon, A.; Federspiel, L.; Goodman, T.P. [École Polytechnique Fédérale de Lausanne (EPFL), Centre de Recherches en Physique des Plasmas, Association EURATOM-Suisse, 1015 Lausanne (Switzerland); Hommen, G. [FOM-Institute DIFFER, Association EURATOM-FOM, Nieuwegein (Netherlands); Eindhoven University of Technology, Department of Mechanical Engineering, Control Systems Technology Group, P.O. Box 513, 5600MB Eindhoven (Netherlands); Karpushov, A.; Piras, F.; Pitzschke, A. [École Polytechnique Fédérale de Lausanne (EPFL), Centre de Recherches en Physique des Plasmas, Association EURATOM-Suisse, 1015 Lausanne (Switzerland); Romero, J. [National Laboratory of Fusion, EURATOM-CIEMAT, Madrid (Spain); Sevillano, G. [Department of Automatic Control and Systems Engineering, Bilbao University of the Basque Country, Bilbao (Spain); Sauter, O.; Vijvers, W. [École Polytechnique Fédérale de Lausanne (EPFL), Centre de Recherches en Physique des Plasmas, Association EURATOM-Suisse, 1015 Lausanne (Switzerland)
2014-03-15
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.
Nonimmigrant Admissions: Fiscal Year 2009
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Model Predictive Control Algorithms for Pen and Pump Insulin Administration
Boiroux, Dimitri
(OCP) is solved using a multiple-shooting based algorithm. We use an explicit Runge-Kutta method (DOPRI45) with an adaptive stepsize for numerical integration and sensitivity computation. The OCP is solved using a Quasi-Newton sequential quadratic programming (SQP) with a linesearch and a BFGS update...
Self-Learning Algorithm for Coiling Temperature Controlling
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.
THE DDTCI SWITCH ALGORITHM FOR ABR TRAFFIC CONTROL IN ATM NETWORKS
Lu Zhaoyi; Ning Yuxin
2005-01-01
For the issue of flow control for Available Bit Rate (ABR) traffic in ATM network,a new improved Explicit Rate (ER) algorithm named Dynamic Double Threshold Congestion Indication (DDTCI) algorithm is presented based on the Explicit Forward Congestion Indication (EFCI) Current Cell Rate (CCR) algorithm and Relative Rate (RR) algorithm. Different from the early ER algorithm, both the high-level and the low-level threshold is dynamically changing according to the state of the bottleneck node. We determinate the congestion state with the information of the two dynamic threshold, and control the cell rate of the source by feed back mechanism. Except for the well performance in both link utilization and fairness in distribution of available bandwidth, the improved algorithm can alleviate the fluctuation of sending rate dramatically. The mechanism is modeled by a fluid model, and the useful expressions are derived.Simulation results show up our conclusion.
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.
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.
Saini, J. S.; Jain, V.
2015-03-01
This paper presents a genetic algorithm (GA)-based design and optimization of fuzzy logic controller (FLC) for automatic generation control (AGC) for a single area. FLCs are characterized by a set of parameters, which are optimized using GA to improve their performance. The design of input and output membership functions (mfs) of an FLC is carried out by automatically tuning (off-line) the parameters of the membership functions. Tuning is based on maximization of a comprehensive fitness function constructed as inverse of a weighted average of three performance indices, i.e., integral square deviation (ISD), the integral of square of the frequency deviation and peak overshoot (Mp), and settling time (ts). The GA-optimized FLC (GAFLC) shows better performance as compared to a conventional proportional integral (PI) and a hand-designed fuzzy logic controller not only for a standard system (displaying frequency deviations) but also under parametric and load disturbances.
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 improved cooperative adaptive cruise control (CACC) algorithm considering invalid communication
Wang, Pangwei; Wang, Yunpeng; Yu, Guizhen; Tang, Tieqiao
2014-05-01
For the Cooperative Adaptive Cruise Control (CACC) Algorithm, existing research studies mainly focus on how inter-vehicle communication can be used to develop CACC controller, the influence of the communication delays and lags of the actuators to the string stability. However, whether the string stability can be guaranteed when inter-vehicle communication is invalid partially has hardly been considered. This paper presents an improved CACC algorithm based on the sliding mode control theory and analyses the range of CACC controller parameters to maintain string stability. A dynamic model of vehicle spacing deviation in a platoon is then established, and the string stability conditions under improved CACC are analyzed. Unlike the traditional CACC algorithms, the proposed algorithm can ensure the functionality of the CACC system even if inter-vehicle communication is partially invalid. Finally, this paper establishes a platoon of five vehicles to simulate the improved CACC algorithm in MATLAB/Simulink, and the simulation results demonstrate that the improved CACC algorithm can maintain the string stability of a CACC platoon through adjusting the controller parameters and enlarging the spacing to prevent accidents. With guaranteed string stability, the proposed CACC algorithm can prevent oscillation of vehicle spacing and reduce chain collision accidents under real-world circumstances. This research proposes an improved CACC algorithm, which can guarantee the string stability when inter-vehicle communication is invalid.
Huang, Quanzhen; Luo, Jun; Li, Hengyu; Wang, Xiaohua
2013-08-01
With the wide application of large-scale flexible structures in spacecraft, vibration control problems in these structures have become important design issues. The filtered-X least mean square (FXLMS) algorithm is the most popular one in current active vibration control using adaptive filtering. It assumes that the source of interference can be measured and the interference source is considered as the reference signal input to the controller. However, in the actual control system, this assumption is not accurate, because it does not consider the impact of the reference signal on the output feedback signal. In this paper, an adaptive vibration active control algorithm based on an infinite impulse response (IIR) filter structure (FULMS, filtered-U least mean square) is proposed. The algorithm is based on an FXLMS algorithm framework, which replaces the finite impulse response (FIR) filter with an IIR filter. This paper focuses on the structural design of the controller, the process of the FULMS filtering control method, the design of the experimental model object, and the experimental platform construction for the entire control system. The comparison of the FXLMS algorithm with FULMS is theoretically analyzed and experimentally validated. The results show that the FULMS algorithm converges faster and controls better. The design of the FULMS controller is feasible and effective and has greater value in practical applications of aerospace engineering.
Computationally efficient algorithm for high sampling-frequency operation of active noise control
Rout, Nirmal Kumar; Das, Debi Prasad; Panda, Ganapati
2015-05-01
In high sampling-frequency operation of active noise control (ANC) system the length of the secondary path estimate and the ANC filter are very long. This increases the computational complexity of the conventional filtered-x least mean square (FXLMS) algorithm. To reduce the computational complexity of long order ANC system using FXLMS algorithm, frequency domain block ANC algorithms have been proposed in past. These full block frequency domain ANC algorithms are associated with some disadvantages such as large block delay, quantization error due to computation of large size transforms and implementation difficulties in existing low-end DSP hardware. To overcome these shortcomings, the partitioned block ANC algorithm is newly proposed where the long length filters in ANC are divided into a number of equal partitions and suitably assembled to perform the FXLMS algorithm in the frequency domain. The complexity of this proposed frequency domain partitioned block FXLMS (FPBFXLMS) algorithm is quite reduced compared to the conventional FXLMS algorithm. It is further reduced by merging one fast Fourier transform (FFT)-inverse fast Fourier transform (IFFT) combination to derive the reduced structure FPBFXLMS (RFPBFXLMS) algorithm. Computational complexity analysis for different orders of filter and partition size are presented. Systematic computer simulations are carried out for both the proposed partitioned block ANC algorithms to show its accuracy compared to the time domain FXLMS algorithm.
New mode switching algorithm for the JPL 70-meter antenna servo controller
Nickerson, J. A.
1988-01-01
The design of control mode switching algorithms and logic for JPL's 70 m antenna servo controller are described. The old control mode switching logic was reviewed and perturbation problems were identified. Design approaches for mode switching are presented and the final design is described. Simulations used to compare old and new mode switching algorithms and logic show that the new mode switching techniques will significantly reduce perturbation problems.
Real-time Design Constraints in Implementing Active Vibration Control Algorithms
Mohammed Alamgir Hossain; Mohammad Osman Tokhi
2006-01-01
Although computer architectures incorporate fast processing hardware resources, high performance real-time implementation of a complex control algorithm requires an efficient design and software coding of the algorithm so as to exploit special features of the hardware and avoid associated architecture shortcomings. This paper presents an investigation into the analysis and design mechanisms that will lead to reduction in the execution time in implementing real-time control algorithms. The proposed mechanisms are exemplified by means of one algorithm, which demonstrates their applicability to real-time applications. An active vibration control (AVC) algorithm for a flexible beam system simulated using the finite difference (FD) method is considered to demonstrate the effectiveness of the proposed methods. A comparative performance evaluation of the proposed design mechanisms is presented and discussed through a set of experiments.
高速网中最小阻塞率的接入控制研究%Call Admission Control with Optimal Block Probability in High-Speed Network
赵尔敦; 石冰心; 郭喻茹; 黄川
2001-01-01
A call admission control scheme with optimal block probability in high-speed network is given. Under the environment of multi-class calls ,the acceptance area with minimum call block probability is obtained. Numerical results show that the maximum call number decreases with the stay-time of the call and increases with the load of the call.
Fuzzy Sets-based Control Rules for Terminating Algorithms
Jose L. VERDEGAY
2002-01-01
Full Text Available In this paper some problems arising in the interface between two different areas, Decision Support Systems and Fuzzy Sets and Systems, are considered. The Model-Base Management System of a Decision Support System which involves some fuzziness is considered, and in that context the questions on the management of the fuzziness in some optimisation models, and then of using fuzzy rules for terminating conventional algorithms are presented, discussed and analyzed. Finally, for the concrete case of the Travelling Salesman Problem, and as an illustration of determination, management and using the fuzzy rules, a new algorithm easy to implement in the Model-Base Management System of any oriented Decision Support System is shown.
Data-Driven Participation: Algorithms, Cities, Citizens, and Corporate Control
Matthew Tenney
2016-07-01
Full Text Available In this paper, we critically explore the interplay of algorithms and civic participation in visions of a city governed by equation, sensor and tweet. We begin by discussing the rhetoric surrounding techno-enabled paths to participatory democracy. This leads to us interrogating how the city is impacted by a discourse that promises to harness social/human capital through data science. We move to a praxis level and examine the motivations of local planners to adopt and increasingly automate forms of VGI as a form of citizen engagement. We ground theory and praxis with a report on the uneven impacts of algorithmic civic participation underway in the Canadian city of Toronto.
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...
Data-Driven Participation: Algorithms, Cities, Citizens, and Corporate Control
Matthew Tenney
2016-07-01
Full Text Available In this paper, we critically explore the interplay of algorithms and civic participation in visions of a city governed by equation, sensor and tweet. We begin by discussing the rhetoric surrounding techno-enabled paths to participatory democracy. This leads to us interrogating how the city is impacted by a discourse that promises to harness social/human capital through data science. We move to a praxis level and examine the motivations of local planners to adopt and increasingly automate forms of VGI as a form of citizen engagement. We ground theory and praxis with a report on the uneven impacts of algorithmic civic participation underway in the Canadian city of Toronto.
Chen, Xinjia
2015-05-01
We consider the general problem of analysis and design of control systems in the presence of uncertainties. We treat uncertainties that affect a control system as random variables. The performance of the system is measured by the expectation of some derived random variables, which are typically bounded. We develop adaptive sequential randomized algorithms for estimating and optimizing the expectation of such bounded random variables with guaranteed accuracy and confidence level. These algorithms can be applied to overcome the conservatism and computational complexity in the analysis and design of controllers to be used in uncertain environments. We develop methods for investigating the optimality and computational complexity of such algorithms.
Moini, A
2002-01-01
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.
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.
van Ophem, S.; Berkhoff, Arthur P.
2016-01-01
For broadband active noise control applications with a rapidly changing primary path, it is desirable to find algorithms with a rapid convergence, a fast tracking performance, and a low computational cost. Recently, a promising algorithm has been presented, called the fast-array Kalman filter, which
Intelligent Control Algorithm of PTZ System Driven by Two-DOF Ultrasonic Motor
Wu Songsen; Leng Xuefei; Jin Jiamei; Wang Bihui; Mao Xingyun
2015-01-01
It is difficult for the traditional pan-tilt-zoom (PTZ) system driven by electromagnetic motor to meet the growing demand for video surveillance system .The key challenge is high positioning accuracy ,high dynamic per-formance and miniaturization of the PTZ system .Here a PTZ system driven by two degree-of-freedom obelisk-shaped ultrasonic motor with single stator is presented ,and its intelligent control algorithm is studied .The struc-ture and driving mechanism of the presented PTZ system are analyzed by both simulation and experiment .To solve the complex nonlinear factors ,e .g .time-variation ,dead zone ,the fuzzy PID control algorithm and the variable gain cross-coupled control strategy are combined to improve the control performance .The results show that the proposed algorithm has faster response ,higher precision than traditional control algorithm ,and it also has a good robustness to prevent the effect of interference .
Monitoring and Automatic Control for Ship Power Plants Based Logical Algorithms
Mahmoud Mohammad Salem Al-suod
2014-12-01
Full Text Available Controlling power station systems with diesel engines is vital issue. Algorithms of microprocessors are developed to be used in the control unit of this type of power station systems. Such Algorithms are built in a logic form, and then the control functions are derived using logic functions. Analyzing the contents of the received logic signals allows us to overcome structural redundancy of the systems. Monitor the network parameter is very important to protect the devices used in the power station systems. In this paper automated controller is developed using microprocessor algorithms to view and control the parameters of the system devices such as generator, synchronizers, and load sharers on-line, this will help in improving the system to be fast, reliable and more accurate. This paper proposes an implementation of a subsequent optimization for structural and algorithmic blocks of microprocessor systems automation of ship power plants.
Control Algorithms of Propulsion Unit with Induction Motors for Electric Vehicle
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.
Fuzzy PID control algorithm based on PSO and application in BLDC motor
Lin, Sen; Wang, Guanglong
2017-06-01
A fuzzy PID control algorithm is studied based on improved particle swarm optimization (PSO) to perform Brushless DC (BLDC) motor control which has high accuracy, good anti-jamming capability and steady state accuracy compared with traditional PID control. The mathematical and simulation model is established for BLDC motor by simulink software, and the speed loop of the fuzzy PID controller is designed. The simulation results show that the fuzzy PID control algorithm based on PSO has higher stability, high control precision and faster dynamic response speed.
Cull, R. C.; Eltimsahy, A. H.
1983-01-01
The present investigation is concerned with the formulation of energy management strategies for stand-alone photovoltaic (PV) systems, taking into account a basic control algorithm for a possible predictive, (and adaptive) controller. The control system controls the flow of energy in the system according to the amount of energy available, and predicts the appropriate control set-points based on the energy (insolation) available by using an appropriate system model. Aspects of adaptation to the conditions of the system are also considered. Attention is given to a statistical analysis technique, the analysis inputs, the analysis procedure, and details regarding the basic control algorithm.
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.
Umesh Kumar Rout
2013-09-01
Full Text Available This paper presents the design and performance analysis of Differential Evolution (DE algorithm based Proportional-Integral (PI controller for Automatic Generation Control (AGC of an interconnected power system. A two area non-reheat thermal system equipped with PI controllers which is widely used in literature is considered for the design and analysis purpose. The design problem is formulated as an optimization problem control and DE is employed to search for optimal controller parameters. Three different objective functions using Integral Time multiply Absolute Error (ITAE, damping ratio of dominant eigenvalues and settling time with appropriate weight coefficients are derived in order to increase the performance of the controller. The superiority of the proposed DE optimized PI controller has been shown by comparing the results with some recently published modern heuristic optimization techniques such as Bacteria Foraging Optimization Algorithm (BFOA and Genetic Algorithm (GA based PI controller for the same interconnected power system.
Endelt, Benny Ørtoft; Volk, Wolfram
2013-01-01
Feedback control of sheet metal forming operations has been an active research field the last two decades and highly advanced control algorithms have been proposed - controlling both the total blank-holder force and in some cases also the distribution of the blank-holder force. However, there is ......Feedback control of sheet metal forming operations has been an active research field the last two decades and highly advanced control algorithms have been proposed - controlling both the total blank-holder force and in some cases also the distribution of the blank-holder force. However......, 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...
MST-BASED CLUSTERING TOPOLOGY CONTROL ALGORITHM FOR WIRELESS SENSOR NETWORKS
Cai Wenyu; Zhang Meiyan
2010-01-01
In this paper,we propose a novel clustering topology control algorithm named Minimum Spanning Tree (MST)-based Clustering Topology Control (MCTC) for Wireless Sensor Networks (WSNs),which uses a hybrid approach to adjust sensor nodes' transmission power in two-tiered hierarchical WSNs. MCTC algorithm employs a one-hop Maximum Energy & Minimum Distance (MEMD) clustering algorithm to decide clustering status. Each cluster exchanges information between its own Cluster Members (CMs) locally and then deliveries information to the Cluster Head (CH). Moreover,CHs exchange information between CH and CH and afterwards transmits aggregated information to the base station finally. The intra-cluster topology control scheme uses MST to decide CMs' transmission radius,similarly,the inter-cluster topology control scheme applies MST to decide CHs' transmission radius. Since the intra-cluster topology control is a full distributed approach and the inter-cluster topology control is a pure centralized approach performed by the base station,therefore,MCTC algorithm belongs to one kind of hybrid clustering topology control algorithms and can obtain scalability topology and strong connectivity guarantees simultaneously. As a result,the network topology will be reduced by MCTC algorithm so that network energy efficiency will be improved. The simulation results verify that MCTC outperforms traditional topology control schemes such as LMST,DRNG and MEMD at the aspects of average node's degree,average node's power radius and network lifetime,respectively.
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...
Research on coal-mine gas monitoring system controlled by annealing simulating algorithm
Zhou, Mengran; Li, Zhenbi
2007-12-01
This paper introduces the principle and schematic diagram of gas monitoring system by means of infrared method. Annealing simulating algorithm is adopted to find the whole optimum solution and the Metroplis criterion is used to make iterative algorithm combination optimization by control parameter decreasing aiming at solving large-scale combination optimization problem. Experiment result obtained by the performing scheme of realizing algorithm training and flow of realizing algorithm training indicates that annealing simulating algorithm applied to identify gas is better than traditional linear local search method. It makes the algorithm iterate to the optimum value rapidly so that the quality of the solution is improved efficiently. The CPU time is shortened and the identifying rate of gas is increased. For the mines with much-gas gushing fatalness the regional danger and disaster advanced forecast can be realized. The reliability of coal-mine safety is improved.
Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm
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.
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...
The research of automatic speed control algorithm based on Green CBTC
Lin, Ying; Xiong, Hui; Wang, Xiaoliang; Wu, Youyou; Zhang, Chuanqi
2017-06-01
Automatic speed control algorithm is one of the core technologies of train operation control system. It’s a typical multi-objective optimization control algorithm, which achieve the train speed control for timing, comfort, energy-saving and precise parking. At present, the train speed automatic control technology is widely used in metro and inter-city railways. It has been found that the automatic speed control technology can effectively reduce the driver’s intensity, and improve the operation quality. However, the current used algorithm is poor at energy-saving, even not as good as manual driving. In order to solve the problem of energy-saving, this paper proposes an automatic speed control algorithm based on Green CBTC system. Based on the Green CBTC system, the algorithm can adjust the operation status of the train to improve the efficient using rate of regenerative braking feedback energy while ensuring the timing, comfort and precise parking targets. Due to the reason, the energy-using of Green CBTC system is lower than traditional CBTC system. The simulation results show that the algorithm based on Green CBTC system can effectively reduce the energy-using due to the improvement of the using rate of regenerative braking feedback energy.
The Ways of Fuzzy Control Algorithms Using for Harvesting Machines Tracking
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.
Optimization of PID Controller for Brushless DC Motor by using Bio-inspired Algorithms
Sanjay Kr. Singh; Nitish Katal; S.G. Modani
2014-01-01
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...
Ant colony optimization algorithm and its application to Neuro-Fuzzy controller design
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.
Liu, Derong; Li, Hongliang; Wang, Ding
2015-06-01
In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update equations of both value function and control policy. We utilize a new assumption instead of the contraction assumption in discounted optimal control problems. We establish the error bounds for approximate value iteration based on a new error condition. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. It is shown that the iterative approximate value function can converge to a finite neighborhood of the optimal value function under some conditions. To implement the developed algorithms, critic and action neural networks are used to approximate the value function and control policy, respectively. Finally, a simulation example is given to demonstrate the effectiveness of the developed algorithms.
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...
Control of Chaotic Regimes in Encryption Algorithm Based on Dynamic Chaos
Sidorenko, V.; Mulyarchik, K. S.
2013-01-01
Chaotic regime of a dynamic system is a necessary condition determining cryptographic security of an encryption algorithm. A chaotic dynamic regime control method is proposed which uses parameters of nonlinear dynamics regime for an analysis of encrypted data.
Unit Template Synchronous Reference Frame Theory Based Control Algorithm for DSTATCOM
Bangarraju, J.; Rajagopal, V.; Jayalaxmi, A.
2014-04-01
This article proposes new and simplified unit templates instead of standard phase locked loop (PLL) for Synchronous Reference Frame Theory Control Algorithm (SRFT). The extraction of synchronizing components (sinθ and cosθ) for parks and inverse parks transformation using standard PLL takes more execution time. This execution time in control algorithm delays the extraction of reference source current generation. The standard PLL not only takes more execution time but also increases the reactive power burden on the Distributed Static Compensator (DSTATCOM). This work proposes a unit template based SRFT control algorithm for four-leg insulated gate bipolar transistor based voltage source converter for DSTATCOM in distribution systems. This will reduce the execution time and reactive power burden on the DSTATCOM. The proposed DSTATCOM suppress harmonics, regulates the terminal voltage along with neutral current compensation. The DSTATCOM in distribution systems with proposed control algorithm is modeled and simulated using MATLAB using SIMULINK and Simpower systems toolboxes.
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...
Elevator Group-Control Policy Based on Neural Network Optimized by Genetic Algorithm
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.
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...
An Optimal Flow Control Algorithm for Real-time Traffic over the Internet
无
2001-01-01
According to the Wide Area Network model and queue dynamics in the router, the authors formulate the Internet flow control as a constrained convex programming problem, where the objective is to maximize the total utility and minimize transmission delay and delay jitter of all sources over their transmission rates. Based on this formulation, flow control can be solved by means of a gradient projection algorithm with properly rate iterations. The main difficulty facing the realization of the iteration algorithm is the distributed computation of the congestion measure. Fortunately, Explicit Congestion Notification (ECN) is likely to be used to improving the performance of TCP in the near future. By using ECN, it is possible to realize the iteration algorithm in IP networks. The algorithm is divided into two parts, algorithms in the router and the source. The main advantage of the scheme is its fast convergence ability and robustness, but small queue length fluctuation is unavoidable when the number of users increases.
Design of Combined Sliding Mode Controller Back Stepping Using Genetic Algorithm
Atefeh Marvi Moghadam
2013-01-01
Full Text Available This research has tried to achieve a new robust controller with back stepping control and sliding mode control method. Also as we know, in all analytical controllers there are constant coefficients like the back stepping and sliding mode controllers, redesigning the Lyapunov and the feedback linearization, - and so forth. There are two major problems in their set: firstly, the adjustment is cumbersome and time-consuming. Secondly, assuming that these parameters can be adjusted to workability, a designer can never tell exactly what are the parameters chosen to be optimal. To resolve this problem, the numerical algorithm which is a genetic algorithm is used here and we have the optimal parameters of the proposed controller. That genetic algorithm (GA has been used to solve difficult engineering problems that are complex and difficult to solve by conventional optimization methods, and at the end of this section, we apply a new robust controller on ball and beam system. Simulation results are expressed.
Optimization of S-surface controller for autonomous underwater vehicle with immune-genetic algorithm
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 Application Research about Modified Genetic Algorithm in the Flywheel Charging-Control System
Jiaqi Zhong
2013-05-01
Full Text Available In the flywheel charging-control system, there exists the flywheel motor’s nonlinearity, variable elements etc, which leads to the problem of parameter tuning of PID controller of its charging-control system’s revolving speed loop. In this study, I will introduce an optimizing way based on modified genetic algorithm for the flywheel charging-control system PID controller, which by means of simulation and performance index quantization to observe its optimizing performance and convergence characteristic, so that we can check the feasibility and effectiveness in the flywheel charging-control system. It turns out that tuning PID controller parameters based on modified genetic algorithm has a better rapidity and stability, which proves the feasibility of the modified genetic algorithm.
Fault Tolerant Control Using Proportional-Integral-Derivative Controller Tuned by Genetic Algorithm
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.
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. ...
Stability of networked control systems with multi-step delay based on time-division algorithm
Changlin MA; Huajing FANG
2005-01-01
A new control mode is proposed for a networked control system whose network-induced delay is longer than a sampling period. A time-division algorithm is presented to implement the control and for the mathematical modeling of such networked control system. The infinite horizon controller is designed, which renders the networked control system mean square exponentially stable. Simulation results show the validity of the proposed theory.
Different Control Algorithms for a Platoon of Autonomous Vehicles
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.
Optimal Control Problem Governed by Semilinear Parabolic Equation and its Algorithm
Chun-fa Li; Xue Yang; En-min Feng
2008-01-01
In this paper, an optimal control problem governed by semilinear parabolic equation which involves the control variable acting on forcing term and coefficients appearing in the higher order derivative terms is formulated and analyzed. The strong variation method, due originally to Mayne et al to solve the optimal control problem of a lumped parameter system, is extended to solve an optimal control problem governed by semilinear parabolic equation, a necessary condition is obtained, the strong variation algorithm for this optimal control problem is presented, and the corresponding convergence result of the algorithm is verified.
Control algorithms along relative equilibria of underactuated Lagrangian systems on Lie groups
Nordkvist, Nikolaj; Bullo, Francesco
2007-01-01
We present novel algorithms to control underactuated mechanical systems. For a class of invariant systems on Lie groups, we design iterative small-amplitude control forces to accelerate along, decelerate along, and stabilize relative equilibria. The technical approach is based upon a perturbation...... analysis and the design of inversion primitives and composition methods. We illustrate the algorithms on an underactuated planar rigid body and on a satellite with two thrusters....
2013-10-01
Insider Threat Control: Using Plagiarism Detection Algorithms to Prevent Data Exfiltration in Near Real Time Todd Lewellen George J. Silowash...algorithms used in plagiarism detection software—to search the index for bodies of text similar to the text found in the outgoing web request. If the...2. REPORT DATE October 2013 3. REPORT TYPE AND DATES COVERED Final 4. TITLE AND SUBTITLE Insider Threat Control: Using Plagiarism Detection
Chaos control of ferroresonance system based on RBF-maximum entropy clustering algorithm
Liu Fan [Key Lab of High Voltage and Electrical New Technology of Ministry of Education, Chongqing University, Chongqing 400044 (China)]. E-mail: liufan2003@yahoo.com.cn; Sun Caixin [Key Lab of High Voltage and Electrical New Technology of Ministry of Education, Chongqing University, Chongqing 400044 (China); Sima Wenxia [Key Lab of High Voltage and Electrical New Technology of Ministry of Education, Chongqing University, Chongqing 400044 (China); Liao Ruijin [Key Lab of High Voltage and Electrical New Technology of Ministry of Education, Chongqing University, Chongqing 400044 (China); Guo Fei [Key Lab of High Voltage and Electrical New Technology of Ministry of Education, Chongqing University, Chongqing 400044 (China)
2006-09-11
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.
Active Engine Mounting Control Algorithm Using Neural Network
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.
Oscillation control algorithms for resonant sensors with applications to vibratory gyroscopes.
Park, Sungsu; Tan, Chin-Woo; Kim, Haedong; Hong, Sung Kyung
2009-01-01
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.
Christopher Dyke
2015-05-01
Full Text Available Currently, there is no manual blind control guideline used consistently throughout the energy modeling community. This paper identifies and compares five manual blind control algorithms with unique control patterns and reports blind occlusion, rate of change data, and annual building energy consumption. The blind control schemes detailed here represent five reasonable candidates for use in lighting and energy simulation based on difference driving factors. This study was performed on a medium-sized office building using EnergyPlus with the internal daylight harvesting engine. Results show that applying manual blind control algorithms affects the total annual consumption of the building by as much as 12.5% and 11.5% for interior and exterior blinds respectively, compared to the Always Retracted blinds algorithm. Peak demand was also compared showing blind algorithms affected zone load sizing by as much as 9.8%. The alternate algorithms were tested for their impact on American Society of Heating, Refrigeration and Air-Conditioning Engineers (ASHRAE Guideline 14 calibration metrics and all models were found to differ from the original calibrated baseline by more than the recommended ±15% for coefficient of variance of the mean square error (CVRMSE and ±5% for normalized mean bias error (NMBE. The paper recommends that energy modelers use one or more manual blind control algorithms during design stages when making decisions about energy efficiency and other design alternatives.
Oscillation Control Algorithms for Resonant Sensors with Applications to Vibratory Gyroscopes
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.
Russel J Stonier
2003-08-01
Full Text Available In this paper we examine the application of evolutionary algorithms to find open-loop control solutions of the optimal control problem arising from the semidiscretisation of a linear parabolic tracking problem with boundary control. The solution is compared with the solutions obtained by methods based upon the variational equations of the Minimum Principle and the finite element method.
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...
Research on Optimal Control for the Vehicle Suspension Based on the Simulated Annealing Algorithm
Jie Meng
2014-01-01
Full Text Available A method is designed to optimize the weight matrix of the LQR controller by using the simulated annealing algorithm. This method utilizes the random searching characteristics of the algorithm to optimize the weight matrices with the target function of suspension performance indexes. This method improves the design efficiency and control performance of the LQR control, and solves the problem of the LQR controller when defining the weight matrices. And a simulation is provided for vehicle active chassis control. The result shows that the active suspension using LQR optimized by the genetic algorithm compared to the chassis controlled by the normal LQR and the passive one, shows better performance. Meanwhile, the problem of defining the weight matrices is greatly solved.
Automatic Tuning of PID Controller for a 1-D Levitation System Using a Genetic Algorithm
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...
Output Feedback Control of Electro-Hydraulic Cylinder Drives using the Twisting Algorithm
Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.
2014-01-01
This paper discusses the utilization of the so-called twisting algorithm when applied in output feedback position control schemes for electro-hydraulic cylinder drives. The twisting controller was the first second order sliding controller ever introduced, and can structure-wise be considered a st...
Technology of Endpoint Admission Control in Computer Networks%计算机网络终端准入控制技术
周超; 周城; 丁晨路
2011-01-01
终端准入控制根据预定安全策略,对接入网络的终端进行身份认证和安全性检查,确保可信、安全的终端访问网络,拒绝或限制不安全终端的接入,体现了终端安全与准入控制的结合,可以有效提高网络对安全威胁的主动防御能力.现行部署的解决方案在身份认证、安全状态检查中存在缺陷,容易受到中间人攻击、会话劫持攻击等,并且对虚拟化应用适应性不足.可考虑通过完善认证过程、改善交互机制等方法加以改进.%Endpoint Admission Control technology takes authentication and security state checking on endpoints accessing to network on the basis of pre-determinate security policies. It makes sure that only the trustworthy and secure endpoints could access to networks while rejects or limits the accessing of insecure endpoints. It' s exemplification of the combination of Endpoint Security and Access Control, which can efficiently improve the active defense ability against security threaten of networks. However, the existing solution has shortages in authentication and security state checking that it could easily attacked by Man-in-the-Middle Attack and Session Hijack. What's more, it also has limitation in Virtualization appliance as well. It's considerable to consummate the mechanism of authentication and communication processes for improvement.
Optimal fuzzy PID control tuned with genetic algorithms
Santos, Carlos Miguel Almeida
2013-01-01
Fuzzy logic controllers (FLC) are intelligent systems, based on heuristic knowledge, that have been largely applied in numerous areas of everyday life. They can be used to describe a linear or nonlinear system and are suitable when a real system is not known or too difficult to find their model. FLC provide a formal methodology for representing, manipulating and implementing a human heuristic knowledge on how to control a system. These controllers can be seen as artificial decision makers tha...
A Review of Router based Congestion Control Algorithms
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.
Research on OEF geometry control algorithm in dual-galvanometric laser scanning manufacturing
Huilai Sun; Shuzhong Lin; Tao Wang
2005-01-01
For the dual-galvanometric laser scanning manufacturing, the traditional geometry algorithm-fθ only considered the distance between the two swaying mirrors, the distance between the swaying mirror and the convex lens, the mirror swaying angle, and the lens focal length. And it could not correctly express the manufacturing track which was made geometry distorted. Based on analysis, a creative geometry control algorithm - optical entire factors (OEF) was brought forward. From the creative algorithm it can be known that OEF geometry control algorithm was concerned with not only the distance of the two swaying mirrors, distance between the swaying mirror and the convex lens, mirror swaying angle, and lens focal length, but also the lens central height, lens convex radius, and medium refractive index. The manufacturing system can manufacture satisfied geometry with the creative double ends approach (DEA) control model based on OEF in the experiments.
A FUZZY-LOGIC CONTROL ALGORITHM FOR ACTIVE QUEUE MANAGEMENT IN IP NETWORKS
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.
Pan, Indranil; Das, Saptarshi; Gupta, Amitava
2011-01-01
An optimal PID and an optimal fuzzy PID have been tuned by minimizing the Integral of Time multiplied Absolute Error (ITAE) and squared controller output for a networked control system (NCS). The tuning is attempted for a higher order and a time delay system using two stochastic algorithms viz. the Genetic Algorithm (GA) and two variants of Particle Swarm Optimization (PSO) and the closed loop performances are compared. The paper shows that random variation in network delay can be handled efficiently with fuzzy logic based PID controllers over conventional PID controllers.
Designing a feedback control algorithm for the tube hydroforming process
Endelt, Benny Ørtoft; Cheng, Ming; Zhang, Shihong
2013-01-01
to the dynamic behavior of the system and the numerical tests show that it is possible to control the quality and plastic deformation of the tube. Numerical simulations show that the control system can eliminate both rupture and irreversible wrinkling - which are the two major failure modes in tube hydroforming....
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
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....
Involuntary admission and treatment
Anirudh Kala
2015-01-01
Full Text Available Provisions for involuntary admission proposed in the Mental Health Care Bill, which is currently before the parliament, are discussed. Concerns about feasibility and cost-effectiveness of the postadmission judicial review, which is a novel feature in the Indian context, are put forward.
The Admissions Equity Struggle
Freedman, Eric
2012-01-01
It has been a long, litigious road from Heman Sweatt, an African-American mail carrier who wanted to attend the prestigious, all-White law school at the University of Texas at Austin in 1946, to Abigail Fisher, a White high school student who failed to win undergraduate admission to the same university a half-century later. Depending on what the…
Optimization of PID controller based on The Bees Algorithm for one leg of a quadruped robot
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.
Moore, J H
1995-06-01
A genetic algorithm for instrumentation control and optimization was developed using the LabVIEW graphical programming environment. The usefulness of this methodology for the optimization of a closed loop control instrument is demonstrated with minimal complexity and the programming is presented in detail to facilitate its adaptation to other LabVIEW applications. Closed loop control instruments have variety of applications in the biomedical sciences including the regulation of physiological processes such as blood pressure. The program presented here should provide a useful starting point for those wishing to incorporate genetic algorithm approaches to LabVIEW mediated optimization of closed loop control instruments.
Scalable algorithms for optimal control of stochastic PDEs
Ghattas, Omar
2016-01-07
We present methods for the optimal control of systems governed by partial differential equations with infinite-dimensional uncertain parameters. We consider an objective function that involves the mean and variance of the control objective, leading to a risk-averse optimal control formulation. To make the optimal control problem computationally tractable, we employ a local quadratic approximation of the objective with respect to the uncertain parameter. This enables computation of the mean and variance of the control objective analytically. The resulting risk-averse optimization problem is formulated as a PDE-constrained optimization problem with constraints given by the forward and adjoint PDEs for the first and second-order derivatives of the quantity of interest with respect to the uncertain parameter, and with an objective that involves the trace of a covariance-preconditioned Hessian (of the objective with respect to the uncertain parameters) operator. A randomized trace estimator is used to make tractable the trace computation. Adjoint-based techniques are used to derive an expression for the infinite-dimensional gradient of the risk-averse objective function via the Lagrangian, leading to a quasi-Newton method for solution of the optimal control problem. A specific problem of optimal control of a linear elliptic PDE that describes flow of a fluid in a porous medium with uncertain permeability field is considered. We present numerical results to study the consequences of the local quadratic approximation and the efficiency of the method.
ZHENG Qing; YANG Zhen
2005-01-01
Based on the Multi-Packet Reception(MPR)capability at the physical layer and the Distributed Coordination Function(DCF)of the IEEE 802.11 MAC protocol,we propose a modified new solution about WAITING mechanism to make full use of the MPR capability in this paper,which is named as modified distributed medium access control algorithm.We describe the details of each step of the algorithm after introducing the WAITING mechanism.Then,we also analyze how the waiting-time affects the throughput performance of the network.The network simulator NS-2 is used to evaluate the throughput performance of the new WAITING algorithm and we compare it with IEEE 802.11 MAC protocol and the old WAITING algorithm.The experimental results show that our new algorithm has the best performance.
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; · ...
Optimization of type-2 fuzzy controllers using the bee colony algorithm
Amador, Leticia
2017-01-01
This book focuses on the fields of fuzzy logic, bio-inspired algorithm; especially bee colony optimization algorithm and also considering the fuzzy control area. The main idea is that this areas together can to solve various control problems and to find better results. In this book we test the proposed method using two benchmark problems; the problem for filling a water tank and the problem for controlling the trajectory in an autonomous mobile robot. When Interval Type-2 Fuzzy Logic System is implemented to model the behavior of systems, the results show a better stabilization, because the analysis of uncertainty is better. For this reason we consider in this book the proposed method using fuzzy systems, fuzzy controllers, and bee colony optimization algorithm improve the behavior of the complex control problems.
LMI-Based Generation of Feedback Laws for a Robust Model Predictive Control Algorithm
Acikmese, Behcet; Carson, John M., III
2007-01-01
This technical note provides a mathematical proof of Corollary 1 from the paper 'A Nonlinear Model Predictive Control Algorithm with Proven Robustness and Resolvability' that appeared in the 2006 Proceedings of the American Control Conference. The proof was omitted for brevity in the publication. The paper was based on algorithms developed for the FY2005 R&TD (Research and Technology Development) project for Small-body Guidance, Navigation, and Control [2].The framework established by the Corollary is for a robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems that guarantees the resolvability of the associated nite-horizon optimal control problem in a receding-horizon implementation. Additional details of the framework are available in the publication.
Automatic Weight Selection Algorithm for Designing H Infinity controller for Active Magnetic Bearing
Sarath S Nair
2011-01-01
Full Text Available In recent times active magnetic bearing has got wide acceptance in industries and other special systems. Current researches focus on improving the disturbance rejection properties of magnetic bearings towork well in industrial environment. So far many controllers have been developed to control the system, of which the H∞ controller is found to guarantee robustness and performance. In this paper an automatic weight selection algorithm is proposed to design robust H Infinity controller automatically for active magnetic bearing system and detailed disturbance analysis is done. This paper focuses on the controller implementation point of view and analyses the variation in control current, peak responses and steady state error of the developed controller. Comparison with a well tuned PID controller shows the efficacy of H infinity controller designed using the proposed algorithm.
Acikmese, Ahmet Behcet; Carson, John M., III
2006-01-01
A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees resolvability. With resolvability, initial feasibility of the finite-horizon optimal control problem implies future feasibility in a receding-horizon framework. The control consists of two components; (i) feed-forward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives and derivatives in polytopes. An illustrative numerical example is also provided.
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)...
Approximation of Reachable Sets using Optimal Control Algorithms
Baier, Robert; Gerdts, Matthias; Xausa, Ilaria
2013-01-01
To appear; International audience; Numerical experiences with a method for the approximation of reachable sets of nonlinear control systems are reported. The method is based on the formulation of suitable optimal control problems with varying objective functions, whose discretization by Euler's method lead to finite dimensional non-convex nonlinear programs. These are solved by a sequential quadratic programming method. An efficient adjoint method for gradient computation is used to reduce th...
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
Stewart, Simon; Ball, Jocasta; Horowitz, John D; Marwick, Thomas H; Mahadevan, Gnanadevan; Wong, Chiew; Abhayaratna, Walter P; Chan, Yih K; Esterman, Adrian; Thompson, David R; Scuffham, Paul A; Carrington, Melinda J
2015-02-28
Patients are increasingly being admitted with chronic atrial fibrillation, and disease-specific management might reduce recurrent admissions and prolong survival. However, evidence is scant to support the application of this therapeutic approach. We aimed to assess SAFETY--a management strategy that is specific to atrial fibrillation. We did a pragmatic, multicentre, randomised controlled trial in patients admitted with chronic, non-valvular atrial fibrillation (but not heart failure). Patients were recruited from three tertiary referral hospitals in Australia. 335 participants were randomly assigned by computer-generated schedule (stratified for rhythm or rate control) to either standard management (n=167) or the SAFETY intervention (n=168). Standard management consisted of routine primary care and hospital outpatient follow-up. The SAFETY intervention comprised a home visit and Holter monitoring 7-14 days after discharge by a cardiac nurse with prolonged follow-up and multidisciplinary support as needed. Clinical reviews were undertaken at 12 and 24 months (minimum follow-up). Coprimary outcomes were death or unplanned readmission (both all-cause), measured as event-free survival and the proportion of actual versus maximum days alive and out of hospital. Analyses were done on an intention-to-treat basis. The trial is registered with the Australian New Zealand Clinical Trials Registry (ANZCTRN 12610000221055). During median follow-up of 905 days (IQR 773-1050), 49 people died and 987 unplanned admissions were recorded (totalling 5530 days in hospital). 127 (76%) patients assigned to the SAFETY intervention died or had an unplanned readmission (median event-free survival 183 days [IQR 116-409]) and 137 (82%) people allocated standard management achieved a coprimary outcome (199 days [116-249]; hazard ratio 0·97, 95% CI 0·76-1·23; p=0·851). Patients assigned to the SAFETY intervention had 99·5% maximum event-free days (95% CI 99·3-99·7), equating to a median
Tu, Jianwei; Lin, Xiaofeng; Tu, Bo; Xu, Jiayun; Tan, Dongmei
2014-09-01
In the process of sudden natural disasters (such as earthquake or typhoon), the active mass damper (AMD) system can reduce the structural vibration response optimally, which serves as a frequently applied but less mature vibration-reducing technology in wind and earthquake resistance of high-rise buildings. As the core of this technology, the selection of control algorithm is extremely challenging due to the uncertainty of structural parameters and the randomness of external loads. It is not necessary for the Model Reference Adaptive Control (MRAC) based on the Minimal Controller Synthesis (MCS) algorithm to know in advance the structural parameters, which produces special advantages in conditions of real-time change of system parameters, uncertain external disturbance, and the nonlinear dynamic system. This paper studies the application of the MRAC into the AMD active control system. The principle of MRAC algorithm is recommended and the dynamic model and the motion differential equation of AMD system based on MRAC is established under seismic excitation. The simulation analysis for linear and nonlinear structures when the structural stiffness is degenerated is performed under AMD system controlled by MRAC algorithm. To verify the validity of the MRAC over the AMD system, experimental tests are carried out on a linear structure and a structure with variable stiffness with the AMD system under seismic excitation on the shake table, and the experimental results are compared with those of the traditional pole assignment control algorithm.
Serious injury prediction algorithm based on large-scale data and under-triage control.
Nishimoto, Tetsuya; Mukaigawa, Kosuke; Tominaga, Shigeru; Lubbe, Nils; Kiuchi, Toru; Motomura, Tomokazu; Matsumoto, Hisashi
2017-01-01
The present study was undertaken to construct an algorithm for an advanced automatic collision notification system based on national traffic accident data compiled by Japanese police. While US research into the development of a serious-injury prediction algorithm is based on a logistic regression algorithm using the National Automotive Sampling System/Crashworthiness Data System, the present injury prediction algorithm was based on comprehensive police data covering all accidents that occurred across Japan. The particular focus of this research is to improve the rescue of injured vehicle occupants in traffic accidents, and the present algorithm assumes the use of an onboard event data recorder data from which risk factors such as pseudo delta-V, vehicle impact location, seatbelt wearing or non-wearing, involvement in a single impact or multiple impact crash and the occupant's age can be derived. As a result, a simple and handy algorithm suited for onboard vehicle installation was constructed from a sample of half of the available police data. The other half of the police data was applied to the validation testing of this new algorithm using receiver operating characteristic analysis. An additional validation was conducted using in-depth investigation of accident injuries in collaboration with prospective host emergency care institutes. The validated algorithm, named the TOYOTA-Nihon University algorithm, proved to be as useful as the US URGENCY and other existing algorithms. Furthermore, an under-triage control analysis found that the present algorithm could achieve an under-triage rate of less than 10% by setting a threshold of 8.3%.
New predictive control algorithms based on Least Squares Support Vector Machines
LIU Bin; SU Hong-ye; CHU Jian
2005-01-01
Used for industrial process with different degree of nonlinearity, the two predictive control algorithms presented in this paper are based on Least Squares Support Vector Machines (LS-SVM) model. For the weakly nonlinear system, the system model is built by using LS-SVM with linear kernel function, and then the obtained linear LS-SVM model is transformed into linear input-output relation of the controlled system. However, for the strongly nonlinear system, the off-line model of the controlled system is built by using LS-SVM with Radial Basis Function (RBF) kernel. The obtained nonlinear LS-SVM model is linearized at each sampling instant of system running, after which the on-line linear input-output model of the system is built. Based on the obtained linear input-output model, the Generalized Predictive Control (GPC) algorithm is employed to implement predictive control for the controlled plant in both algorithms. The simulation results after the presented algorithms were implemented in two different industrial processes model; respectively revealed the effectiveness and merit of both algorithms.
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.
Yazdi, Ebrahim
2010-01-01
In this paper, a simple Neural controller has been used to achieve stable walking in a NAO biped robot, with 22 degrees of freedom that implemented in a virtual physics-based simulation environment of Robocup soccer simulation environment. The algorithm uses a Matsuoka base neural oscillator to generate control signal for the biped robot. To find the best angular trajectory and optimize network parameters, a new population-based search algorithm, called the Harmony Search (HS) algorithm, has been used. The algorithm conceptualized a group of musicians together trying to search for better state of harmony. Simulation results demonstrate that the modification of the step period and the walking motion due to the sensory feedback signals improves the stability of the walking motion.
Fuzzy Control Hardware for Segmented Mirror Phasing Algorithm
Roth, Elizabeth
1999-01-01
This paper presents a possible implementation of a control model developed to phase a system of segmented mirrors, with a PAMELA configuration, using analog fuzzy hardware. Presently, the model is designed for piston control only, but with the foresight that the parameters of tip and tilt will be integrated eventually. The proposed controller uses analog circuits to exhibit a voltage-mode singleton fuzzifier, a mixed-mode inference engine, and a current-mode defuzzifier. The inference engine exhibits multiplication circuits that perform the algebraic product composition through the use of operational transconductance amplifiers rather than the typical min-max circuits. Additionally, the knowledge base, containing exemplar data gained a priori through simulation, interacts via a digital interface.
An algorithm for formation control of mobile robots
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
Multi-Rate Digital Control Systems with Simulation Applications. Volume II. Computer Algorithms
1980-09-01
34 ~AFWAL-TR-80-31 01 • • Volume II L IL MULTI-RATE DIGITAL CONTROL SYSTEMS WITH SIMULATiON APPLICATIONS Volume II: Computer Algorithms DENNIS G. J...29 Ma -8 - Volume II. Computer Algorithms ~ / ’+ 44MWLxkQT N Uwe ~~ 4 ~jjskYIF336l5-79-C-369~ 9. PER~rORMING ORGANIZATION NAME AND ADDRESS IPROG AMEL...additional options. The analytical basis for the computer algorithms is discussed in Ref. 12. However, to provide a complete description of the program, some
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.
Design of PID controller with incomplete derivation based on differential evolution algorithm
Wu Lianghong; Wang Yaonan; Zhou Shaowu; Tan Wen
2008-01-01
To determine the optimal or near optimal parameters of PID controller with incomplete derivation, a novel design method based on differential evolution (DE) algorithm is presented. The controller is called DE-PID controller. To overcome the disadvantages of the integral performance criteria in the frequency domain such as IAE, ISE, and ITSE, a new performance criterion in the time domain is proposed. The optimization procedures employing the DE algorithm to search the optimal or near optimal PID controller parameters of a control system are demonstrated in detail. Three typical control systems are chosen to test and evaluate the adaptation and robustness of the proposed DE-PID controller. The simulation results show that the proposed approach has superior features of easy implementation, stable convergence characteristic, and good computational efficiency. Compared with the ZN, GA, and ASA, the proposed design method is indeed more efficient and robust in improving the step response of a control system.
Bat algorithm optimized fuzzy PD based speed controller for brushless direct current motor
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.
Design of PID controller with incomplete derivation based on ant system algorithm
Guanzheng TAN; Qingdong ZENG; Wenbin LI
2004-01-01
A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm (ASA).For a given control system with this kind of PID controller,a group of optimal PID controller parameters K*p,T*i, and T*d can be obtained by taking the overshoot,settling time,and steady-state error of the system's unit step response as the performance indexes and by use of our improved ant system algorithm.K*p,T*i, and T*d can be used in real-time control.This kind of controller is called the ASA-PID controller with incomplete derivation.To verify the performance of the ASA-PID controller,three different typical transfer functions were tested,and three existing typical tuning methods of PID controller parameters,including the Ziegler-Nichols method (ZN),the genetic algorithm (GA),and the simulated annealing (SA),were adopted for comparison.The simulation results showed that the ASA-PID controller can be used to control different objects and has better performance compared with the ZN-PID and GA-PID controllers,and comparable performance compared with the SA-PID controller.
A Hybrid Bacterial Foraging - PSO Algorithm Based Tuning of Optimal FOPI Speed Controller
Rajasekhar Anguluri
2011-11-01
Full Text Available Bacterial Foraging Optimization Algorithm (BFOA has recently emerged as a very powerful technique for real parameteroptimization. In order to overcome the delay in optimization and to further enhance the performance of BFO, this paper proposeda new hybrid algorithm combining the features of BFOA and Particle Swarm Optimization (PSO for tuning a Fractional orderspeed controller in a Permanent Magnet Synchronous Motor (PMSM Drive. Computer simulations illustrate the effectiveness of theproposed approach compared to that of basic versions of PSO and BFO.
The Distribution Population-based Genetic Algorithm for Parameter Optimization PID Controller
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.
Control Algorithms for a Shape-shifting Tracked Robotic Vehicle Climbing Obstacles
2008-12-01
conduits sur Ie vrai robot afin de verifier la fiabilite et la robust esse des controleurs avec de vrais environnements, capteurs et actuateurs...perception, control and learning algorithms that are widely applicable , fast to compute and adaptive to changing ground conditions. The development of...navigation tasks [11-201. There has been limited application of learning algorithms to shape-shifting platforms for choice of geometry based on
Scheduling algorithms for automatic control systems for technological processes
Chernigovskiy, A. S.; Tsarev, R. Yu; Kapulin, D. V.
2017-01-01
Wide use of automatic process control systems and the usage of high-performance systems containing a number of computers (processors) give opportunities for creation of high-quality and fast production that increases competitiveness of an enterprise. Exact and fast calculations, control computation, and processing of the big data arrays – all of this requires the high level of productivity and, at the same time, minimum time of data handling and result receiving. In order to reach the best time, it is necessary not only to use computing resources optimally, but also to design and develop the software so that time gain will be maximal. For this purpose task (jobs or operations), scheduling techniques for the multi-machine/multiprocessor systems are applied. Some of basic task scheduling methods for the multi-machine process control systems are considered in this paper, their advantages and disadvantages come to light, and also some usage considerations, in case of the software for automatic process control systems developing, are made.
Distributed topology control algorithm for multihop wireless netoworks
Borbash, S. A.; Jennings, E. H.
2002-01-01
We present a network initialization algorithmfor wireless networks with distributed intelligence. Each node (agent) has only local, incomplete knowledge and it must make local decisions to meet a predefined global objective. Our objective is to use power control to establish a topology based onthe relative neighborhood graph which has good overall performance in terms of power usage, low interference, and reliability.
Efficiency analysis of control algorithms in spatially distributed systems with chaotic behavior
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.
Adaptive control of parallel manipulators via fuzzy-neural network algorithm
Dachang ZHU; Yuefa FANG
2007-01-01
This paper considers adaptive control of parallel manipulators combined with fuzzy-neural network algorithms (FNNA). With this algorithm, the robustness is guaranteed by the adaptive control law and the parametric uncertainties are eliminated. FNNA is used to handle model uncertainties and external disturbances. In the proposed control scheme,we consider modifying the weight of fuzzy rules and present these rules to a MIMO system of parallel manipulators with more than three degrees-of-freedom (DoF). The algorithm has the advantage of not requiring the inverse of the Jacobian matrix especially for the low DoF parallel manipulators. The validity of the control scheme is shown through numerical simulations of a 6-RPS parallel manipulator with three DoF.
A new autotuning algorithm for PID controllers using dead-beat format.
Bandyopadhyay, R; Patranabis, D
2001-01-01
A novel algorithm for PID controllers based on dead-beat control and fuzzy inference mechanism is presented in this paper. The proposition is an extension of the work by the authors where the PI form of the algorithm was presented. The inclusion of the derivative term makes the method suitable for application in all types of processes including the ones having high rate disturbances. The proposed algorithm seems to be a complete and generalized PID autotuner as can be seen by the simulated and experimental results. In all the cases the method shows substantial improvement over the controller tuned with Ziegler Nichol's formula and the PI controller proposed in R. Bandyopadhyay, D. Patranabis, A fuzzy logic based PI autotuner, ISA Transactions 37 (1998) 227-235.
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.
Distributed power control algorithm based on game theory for wireless sensor networks
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.