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Networking, Sensing and Control, 2005. Proceedings. 2005 IEEE

Date 19-22 March 2005

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Displaying Results 1 - 25 of 203
  • Adaptive fuzzy system for disassembly process planning

    Publication Year: 2005 , Page(s): 141 - 146
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (263 KB) |  | HTML iconHTML  

    Disassembly is rapidly growing in importance as manufacturers face increasing pressure to deal with obsolete products in an environmentally responsible and economically sound manner. This paper builds, upon our previous work to address uncertainty management and human factors in disassembly. A fuzzy Petri net (FPN) model is proposed to mathematically represent uncertain factors in disassembly. An adaptive fuzzy system is then designed to dynamically estimate their impact on the disassembly process. Finding the disassembly path of a discarded product with the highest economic value and prediction confidence is accomplished through a recursive algorithm. View full abstract»

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  • Agent-based dynamic scheduling for semiconductor wafer fab

    Publication Year: 2005 , Page(s): 163 - 168
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (334 KB) |  | HTML iconHTML  

    Semiconductor wafer fab is considered as the third kind of production system, differentiated with job shop and flow shop. It has its own scheduling and control characteristics, such as re-entrance, large-scale, mix processing model and unbalanced production facilities. To solve scheduling problem of semiconductor wafer fab, an agent-based scheduling approach for semiconductor wafer fab is proposed. Firstly, an agent-based scheduling model, which integrates release control, dispatching and machine maintenance scheduling, is presented. Secondly, negotiation protocol between agents, extended contract net protocol (ECNP), is given. Thirdly, scheduling algorithms for decision making of agents are offered. Finally, a simple model, but with essential characters of semiconductor wafer fabrication, is used to demonstrate how to use the proposed agent-based scheduling approach. View full abstract»

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  • A compound-cosine-based neural networks for design of 2-D FIR filters

    Publication Year: 2005 , Page(s): 29 - 33
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (158 KB)  

    Two-dimensional digital filters are one of the most fundamental and most important processing techniques in digital vision and image processing and other 2-D digital signal processing fields. This paper studies the relations between the amplitude performances of the 2-D FIR filters and the compound-cosine-based neural network in details. A compound-cosine-based neural network for the design of 2-D filters is proposed. It conquers the main disadvantages of the conventional methods. The convergence theorem, which ensures this neural network convergent, is presented, and the theorem is proved in this paper. The simulation attains near ideal filter characteristics. View full abstract»

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  • Partitioned fractal image compression for binary images using genetic algorithms

    Publication Year: 2005 , Page(s): 734 - 737
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (217 KB) |  | HTML iconHTML  

    The paper presents a novel approach for pre-processing of binary images, which helps in subsequent application of the genetic algorithm in a parallel manner and reduces the computational time, while at the same time improves the quality of the regenerated image and makes the evolutionary approach more practical to employ for fractal image compression. Pre-processing involves division of image into disconnected regions, identification of the largest solid rectangle and final partitioning about the rectangle. The performance of the proposed partitioned technique is tested on a binary image and the experimental results are reported. View full abstract»

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  • Toward a simulation benchmark for distributed mission-critical real-time systems

    Publication Year: 2005 , Page(s): 1037 - 1042
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (388 KB) |  | HTML iconHTML  

    Given the overall increasing trend of airspace demand by commercial, military, and general aviation, researchers are developing new software tools to enhance the level of automation in air traffic control systems to alleviate the already-crowded airspace by allowing controllers and pilots more freedom in planning and conducting flights. These tools utilize high-performance commercial workstations that use high-speed networks and function together to form a distributed real-time computing system. This paper describes a three-dimensional air traffic control simulation benchmark developed by the author for the purpose of running simulations of air traffic scenarios, adding new capabilities, and gauging performance, security, and reliability quality of service management techniques on a variety of platforms. View full abstract»

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  • Detecting anomalies in cluster-based parallel programs using a wavelet based approach

    Publication Year: 2005 , Page(s): 348 - 353
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (384 KB) |  | HTML iconHTML  

    Anomaly detection has the potential to detect unusual behavior and novel attacks that have not been previously observed. Audits of many events including system calls, user command usage, credit card usage, etc. can be used as the basis for anomaly detection. Examination of these traces of ordered events allows classification of audit trails as normal or anomalous. This paper explores the utility of wavelets as a classification method for use in the context of anomaly detection in parallel programs run in a high performance cluster environment. The events considered are traces of function calls and system calls invoked by parallel programs. Two wavelet-based classification methods are described for anomaly detection. The wavelet-based approaches are sensitive to both order and frequency behavior of the events. The experimental results indicate that both wavelet-based classification methods are more effective in the detection of anomalies than sequence matching. View full abstract»

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  • Performance evaluation of quality of service aware request placement techniques

    Publication Year: 2005 , Page(s): 744 - 749
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (407 KB) |  | HTML iconHTML  

    Web services have become very popular over the past few years. However, users are facing the problem of the perceived QoS. Practical approaches to address this issue are based on service replication at multiple locations and on allocation mechanisms to dispatch requests in such a way that the QoS perceived by the user is improved. In this paper we compare user perceived QoS performance of three dynamic request placement techniques. One technique randomly allocates Web requests while the other two techniques implement a market-based mechanism for QoS negotiation and request allocation. The analysis is conducted via simulation with SIDE using a behavioral model of Web traffic to simulate accurate traffic conditions and determine the limitations or validity of these techniques. View full abstract»

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  • SoftMan and agent

    Publication Year: 2005 , Page(s): 904 - 907
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (195 KB) |  | HTML iconHTML  

    SoftMan is a new concept based on the production of distributed technique, intelligent robot and artificial life. SoftMan is the development of a mobile agent and is a virtual robot in the network environment. It inherited many research fruits of robot and agent. Therefore, it has the essential features of the intelligent robot and agent, and at the same time has life features. Comparing with the agent, SoftMan not only has more all-around humanized intelligence, humanized behavior and function, but also has the ability of environment identification, self-determination and free will. SoftMan has some digital life features which agent has none, such as activity, learning and evolution, inheritance, variation and emotion. The corresponding theory and technology fruits provided a good foundation and reference for studying SoftMan. At first, this paper introduces the technology of SoftMan and agent, and then discusses the relationship between SoftMan and agent from the viewpoint of structure model, function, implementation technique, and application example. View full abstract»

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  • Intelligent traffic signal system based on networked control

    Publication Year: 2005 , Page(s): 587 - 591
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (303 KB) |  | HTML iconHTML  

    Several traffic control systems are simply introduced, and based on the networked control presented is a new intelligent intersection control system. It is characterized by the agent-based control and the local simple remote complex (LSRC) design principle. On one hand the intelligent control of intersection is guaranteed, and on the other hand the cost of the control system is decreased. The structure and function of the whole system are described in detail. According to the characteristic of city traffic, the intersection signal is controlled by fuzzy neural network, which fully uses the advantage of this system. View full abstract»

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  • Dynamic road pricing for optimizing network performance with heterogeneous users

    Publication Year: 2005 , Page(s): 407 - 412
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (409 KB) |  | HTML iconHTML  

    In transport networks, travelers individually make route and departure time choice decisions that may not be optimal for the whole network. By introducing (time-dependent) tolls the network performance may be optimized. In the paper, the effects of time-dependent tolls on the network performance are analyzed using a dynamic traffic model. The network design problem is formulated as a bi-level optimization problem in which the upper level describes the network performance with chosen toll levels while the lower level describes the dynamic network model including user-specific route and departure time choice and the dynamic network loading. In case studies on a simple hypothetical network it is shown that network improvements can be obtained by introducing tolls. It is also shown that finding a global solution to the network design problem is complex as it is non-linear and non-convex. View full abstract»

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  • PI/PID based multi-objective control design: an ILMI approach

    Publication Year: 2005 , Page(s): 750 - 755
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (216 KB) |  | HTML iconHTML  

    In many real world control problems, we have to follow several control objectives, simultaneously. At the same time, it is usually desirable to meet all specified goals using the controllers with simple structures such as proportional-integral (PI) and proportional-integral-derivative (PID) which are useful in industry applications. Since, practically these controllers are commonly tuned based on classical or trial-and-error approaches, they are incapable of obtaining good dynamical performance to capture all design objectives and specification. With regard to above problem, this paper addresses a new method to design of multi-objective PI/PID controller. For this purpose, first the multi-objective control design is reduced to an H2/H static output feedback control synthesis, and then the control parameters are easily carried out using an iterative linear matrix inequalities (ILMI) algorithm. As a numerical example, the proposed method is applied to a multi-area power system to design a set of PI-based robust load frequency controllers. View full abstract»

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  • Evaluation of human meal Kansei using AHP

    Publication Year: 2005 , Page(s): 431 - 436
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (301 KB) |  | HTML iconHTML  

    This paper is concerned with human meal preference. For evaluating human meal Kansei a method has been proposed to give the scales for human meal feelings as subjective characteristics of food in which the units of the scales are the standard deviations of the standard normal distribution. Here in addition to the method to evaluate human meal feelings a method is discussed to evaluate individuals' meal intentions by paired comparisons, which is modified AHP (analytic hierarchy process) in judging the consistency of subjects' answers and giving the scales for the answers. Combining the methods to evaluate human meal feelings and individuals' meal intentions a method is studied to evaluate individuals' meal preference. In the method the scales are given so that the units can be considered the standard deviations of the standard normal distribution as well as the scales for human meal feelings. In this paper the methods to evaluate individuals' meal intentions and also individuals' meal preference are described and numerical results of the experiment on Kansei evaluation conducted for this study using 200 menus on home dining tables are shown. A method is also discussed to simplify the judgment on the consistency of a subject's answers in AHP. View full abstract»

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  • Resolution principle based on six lattice-valued first-order logic L6F(X)

    Publication Year: 2005 , Page(s): 838 - 843
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (265 KB) |  | HTML iconHTML  

    Resolution-based automated reasoning theory is an important and active research field in artificial intelligence. It is not only used to judge the satisfiability of any logic formula, but also widely applied to areas such as artificial intelligence, logic programming, problem solving and question answering systems, database theory, and so on. With the development of classical and non-classical logic, resolution theory and method based on different logic system has been discussed widely and deeply. In the present paper, resolution-based automated reasoning theory in a six lattice-valued first-order logic is focused. This resolution principle in this paper is based on ultrafilter of lattice implication algebra. In this paper, some necessary preliminaries are given first. Then resolution principle in L6F(X) is discussed and soundness and completeness theorem is proved. Because of L6F(X) is a non-chain, non-boolean and non-well-ordered algebra structure, resolution based on L6F(X) is the theoretical foundation of resolution on lattice-valued truth-field. Accordingly, the research in this paper is a helpful support for the application of intelligent reasoning system based on lattice-valued logic which includes incomparable information. View full abstract»

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  • A microchannel experimental apparatus for heat exchanging: design and analysis

    Publication Year: 2005 , Page(s): 60 - 64
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (236 KB)  

    An experimental apparatus is developed for testing the heat-exchange performance of microchannel structures. This system mainly consists of microchannel heat exchangers, a simulated heat source, a micro-pump; a few of pipes, some three-way pipes and other test devices. The heat exchange coefficients and the fluid resistant in microchannels can be obtained by testing temperature, pressure and flow rate. The fluid resistance and heat transfer performance of microchannels are analyzed and investigated based on this experimental apparatus. It is shown that classical macroscopic formulas are not applicable for calculating friction resistance and heat exchange coefficients when channel hydraulic diameter is 381 μm. In this case, the flow resistance is smaller from 31.6% to 41.9% than that of calculated by classical macroscopic formulas, and the microchannel structure has a satisfied heat transfer performance while Nussle number being 9.2. View full abstract»

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  • Multicast routing for delay and delay variation bounded Steiner tree using simulated annealing

    Publication Year: 2005 , Page(s): 682 - 687
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (413 KB) |  | HTML iconHTML  

    An efficient heuristic multicast routing algorithm based on simulated annealing named SADDVS is proposed to solve delay and delay variation-bounded Steiner tree problem. This problem is known to be NP-complete. The proposed heuristic algorithm uses a procedure called paths switching to construct, neighbors in feasible region, which greatly reduces the search area and running time. We also give a method to dynamically reorganize the multicast tree in response to changes for the destinations. Simulations demonstrate that our algorithm is better in terms of tree cost as compared to the existing algorithms. Further, it performs excellent performance of delay and delay variation, high success ratio, rapid convergence and better real-time property. View full abstract»

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  • New results on discrete-event counting under reliable and unreliable observation information

    Publication Year: 2005 , Page(s): 688 - 693
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (399 KB) |  | HTML iconHTML  

    We present an approach for addressing the issues of detecting repeated fault events in the framework of model-based monitoring of discrete-event systems (DES) under reliable and unreliable observation information. The analysis task is to determine whether a certain observation configuration is capable of reporting the occurrence of fault events while satisfying the performance requirements. If the reliability of observation information is assured, the assessment is accomplished by evaluating diagnosability notions of interest. To evaluate the notions of diagnosability regarding repeated fault counting, polynomial-time verification algorithms are developed. In order to deal with unreliable observation information, the concept of detection confidence is introduced, which measures the quality of fault counting. An algorithm computing detection confidence is conjectured. For online fault counting, we develop a new online fault counting algorithm assuming observation reliability. The developed algorithm has lower time and space complexities than an online diagnosis algorithm reported in literature for counting the occurrence of repeated faults. This online algorithm is naturally extended to handle the unreliable observation information. View full abstract»

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  • Reliable sensor networks for planet exploration

    Publication Year: 2005 , Page(s): 816 - 821
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (327 KB) |  | HTML iconHTML  

    Wireless sensor networks will play a critical role in space and planet exploration, allowing remote monitoring of non-easily accessible areas in preparation of human or robotic missions. Sensors, however, are fragile and can fail, reporting erroneous measurements, for example. Decisions derived from flawed sensor measurements can adversely impact the correctness of the overall sensor network findings and may jeopardize the success of the mission. Unfortunately, failed sensors in space cannot be easily diagnosed and replaced. To improve the reliability of decisions and minimize the impact of faulty sensor measurements, the preferred approach is to exploit data redundancy. In this paper, we present confidence weighted voting (CWV), a distributed technique that can greatly improve the data reliability and fault tolerance of sensor network applications. We evaluate CWV against traditional approaches (e.g., majority voting (MV) and distance weighted voting (DWV)), in the presence of flawed sensors. The results show that CWV consistently outperforms the other schemes by providing as much as 49% more resiliency. View full abstract»

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  • Flexible automated monitoring and notification for complex processes using KARMEN

    Publication Year: 2005 , Page(s): 443 - 448
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (384 KB) |  | HTML iconHTML  

    Automated monitoring for complex systems such as the space shuttle fueling and launch process can increase the effectiveness of operators in detecting abnormal conditions before become hazardous to the point they may compromise the mission. We have developed the KAoS reactive monitoring and event notification (KARMEN) multi-agent system to allow users to describe and change monitoring conditions at any time in order to effectively monitor such processes and appropriately notify key operations personnel about off-nominal conditions. These notification actions are overseen by policies that contain process requirements and users preferences. View full abstract»

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  • Sparse Bayesian approach to classification

    Publication Year: 2005 , Page(s): 914 - 917
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (235 KB) |  | HTML iconHTML  

    This paper reports our recent efforts in the attempt to apply the relevance vector machine (RVM) to text-independent speaker recognition tasks. The RVM represents a Bayesian extension of the widely applied support vector machine (SVM), one of the leading approaches to pattern recognition and machine learning. Both the SVM and the RVM use a linear combination of kernel functions centered on a subset of the training data to make regressions or classifications. In the SVM, the number of vectors in the subset grows linearly with the size of the available training data, while in the RVM, only the most relevant vectors will be captured. So the RVM yields a much sparser approximation of the Bayesian kernel than the SVM. Our preliminary experimental results show that the RVM overall outperforms the SVM on speaker recognition while being advantageous over the latter for its exceptionally sparse nature, classification accuracy, and Bayesian probabilistic framework. Comparisons are also made for the Gaussian mixture model (GMM), a widely used non-discriminative approach to speaker recognition. View full abstract»

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  • Study on multi-bases coordination technology based on IADS and "Softman" in DSS

    Publication Year: 2005 , Page(s): 954 - 958
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (268 KB) |  | HTML iconHTML  

    In order to improve the present technology of MBC (multi-bases coordination), in this paper, the idea of developing MBC system based on intelligent autonomous decentralized system (IADS) and "Softman" is proposed, and software models applied in decision support system are given. View full abstract»

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  • Using space and network diversity combining to solve masked node collision in wireless adhoc network

    Publication Year: 2005 , Page(s): 1075 - 1080
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (292 KB) |  | HTML iconHTML  

    In wireless ad hoc network, the traditional carrier sensing multiple access/collision avoidance (CSMA/CA) protocol cannot solve the masked node problem, which affect the network performance greatly. Our proposed collision separation technique overcomes the shortcoming of the IEEE 802.11 request-to-send-clear-to-send (RTS-CTS) handshake by combining the space diversity provided by the antenna array and network diversity provided by the media access control (MAC) layer. In this work, the colliding packets caused by masked nodes are not discarded but stored and combined with the selected retransmission packets to separate the data from different nodes. The steady states of the nodes in the network are analyzed via a Markov chain model. The network goodput and delay performance are also investigated. Compared to network assisted diversity multiple access (NDMA), our proposed method, i.e., space and network diversity combination, SNDC for short, can provide higher throughput and lower delay performance. View full abstract»

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  • Geographic grid routing for wireless sensor networks

    Publication Year: 2005 , Page(s): 484 - 489
    Cited by:  Papers (1)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (366 KB) |  | HTML iconHTML  

    High resolution data collection using low-cost wireless sensor networks has recently become feasible due to advances in electronics and wireless networking technologies. The geographic grid routing (GGR) protocol described in this paper aims to provide robust task dissemination and data collection from large sensor networks such that the useful lifetime of the network is prolonged. The work builds on a previously developed routing protocol called two-tier data dissemination (TTDD). Our work is differentiated by the use of multiple paths, a more efficient and useful data collection model, and more authentic environmental assumptions, including the presence of asymmetric links. Extensive and realistic experiments were used to evaluate the performance of GGR. The results show GGR to be a highly efficient, scalable, versatile and robust solution. View full abstract»

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  • Exploring the neural state space learning from one-dimension chaotic time series

    Publication Year: 2005 , Page(s): 437 - 442
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (310 KB) |  | HTML iconHTML  

    Because the chaotic system is initial condition sensitive, it is difficult to decide a proper initial state for a recurrent neural network to model observed one-dimension chaotic time series. In this paper, a recurrent neural network with feedback composed of internal state is introduced to model one-dimension chaotic time series. The neural network output is a nonlinear combination of the internal state variable. To successfully model a chaotic time series, this paper proves that the recurrent neural network with internal state can start from arbitrary initial state. In the simulation, the neural systems perform multi-step ahead prediction, also, the reconstructed neural state space is compared with the original state space, and largest LEs (Lyapunov exponents) of the two systems are calculated and compared to see if the two systems have similar chaotic invariant. View full abstract»

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  • Dynamic flow control and analysis on unicast and multicast architecture networks

    Publication Year: 2005 , Page(s): 389 - 394
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (312 KB) |  | HTML iconHTML  

    With the proliferation of multicast service in the Internet, much attention has been put upon multicast congest control. Multicast traffic poses new challenges to the design of Internet congestion control protocols and system stability analysis. In this paper, we focus on the feedback-based sessions rate control problem on the combination of unicast and multirate multicast traffic architecture networks. Firstly, fairness problem is discussed in detail and reasonable consumption strategy is proposed. Scaling functions are adaptively adjusted based on relationship of session rates. Secondly, in the case of link capacities available for feedback-based unicast and multicast sessions, stability analysis of closed loop system under the modified rate mechanism is made based on Lyapunov stable theory. Finally, the simulations demonstrate the effectiveness and goodness of reasonable consumption strategy. View full abstract»

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  • Robust H control for uncertain discrete-time delayed stochastic systems with saturating nonlinear actuators

    Publication Year: 2005 , Page(s): 844 - 849
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (198 KB) |  | HTML iconHTML  

    The robust H control problem is presented for uncertain discrete-time delayed stochastic systems with saturating nonlinear actuators. In the discrete time systems, the parameter uncertainties are assumed to satisfy norm-bounded conditions, and the time delays exist in state and control simultaneously. By the Lyapunov stability theory, sufficient conditions for the existence of stochastic robust stabilization controller and stochastic robust H controller are presented in terms of linear matrix inequality. With the controllers, the closed-loop systems are robust stochastic stable with a pre-specified H disturbance attenuation coefficient γ. View full abstract»

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