Robust H∞ filtering for a class of nonlinear networked systems with multiple stochastic communication delays and packet dropouts

Copyright [2010] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this paper, the robust H∞ filtering problem is studied for a class of uncertain nonlinear networked systems with both multiple stochastic time-varying communication delays and multiple packet dropouts. A sequence of random variables, all of which are mutually independent but obey Bernoulli distribution, are introduced to account for the randomly occurred communication delays. The packet dropout phenomenon occurs in a random way and the occurrence probability for each sensor is governed by an individual random variable satisfying a certain probabilistic distribution in the interval. The discrete-time system under consideration is also subject to parameter uncertainties, state-dependent stochastic disturbances and sector-bounded nonlinearities. We aim to design a linear full-order filter such that the estimation error converges to zero exponentially in the mean square while the disturbance rejection attenuation is constrained to a give level by means of the H∞ performance index. Intensive stochastic analysis is carried out to obtain sufficient conditions for ensuring the exponential stability as well as prescribed H∞ performance for the overall filtering error dynamics, in the presence of random delays, random dropouts, nonlinearities, and the parameter uncertainties. These conditions are characterized in terms of the feasibility of a set of linear matrix inequalities (LMIs), and then the explicit expression is given for the desired filter parameters. Simulation results are employed to demonstrate the effectiveness of the proposed filter design technique in this paper.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the Royal Society of the U.K., the Alexander von Humboldt Foundation of Germany, National Natural Science Foundation of China under Grant 60825303, 60834003, 973 Project under Grant 2009CB320600, Fok Ying Tung Education Foundation under Grant 111064, and the Youth Science Fund of Heilongjiang Province under Grant QC2009C63

Robust Controller for Delays and Packet Dropout Avoidance in Solar-Power Wireless Network

Solar Wireless Networked Control Systems (SWNCS) are a style of distributed control systems where sensors, actuators, and controllers are interconnected via a wireless communication network. This system setup has the benefit of low cost, flexibility, low weight, no wiring and simplicity of system diagnoses and maintenance. However, it also unavoidably calls some wireless network time delays and packet dropout into the design procedure. Solar lighting system offers a clean environment, therefore able to continue for a long period. SWNCS also offers multi Service infrastructure solution for both developed and undeveloped countries. The system provides wireless controller lighting, wireless communications network (WI-FI/WIMAX), CCTV surveillance, and wireless sensor for weather measurement which are all powered by solar energy

A Survey on Multisensor Fusion and Consensus Filtering for Sensor Networks

Multisensor fusion and consensus filtering are two fascinating subjects in the research of sensor networks. In this survey, we will cover both classic results and recent advances developed in these two topics. First, we recall some important results in the development ofmultisensor fusion technology. Particularly, we pay great attention to the fusion with unknown correlations, which ubiquitously exist in most of distributed filtering problems. Next, we give a systematic review on several widely used consensus filtering approaches. Furthermore, some latest progress on multisensor fusion and consensus filtering is also presented. Finally, conclusions are drawn and several potential future research directions are outlined.the Royal Society of the UK, the National Natural Science Foundation of China under Grants 61329301, 61374039, 61304010, 11301118, and 61573246, the Hujiang Foundation of China under Grants C14002 and D15009, the Alexander von Humboldt Foundation of Germany, and the Innovation Fund Project for Graduate Student of Shanghai under Grant JWCXSL140

Distributed Channel Access for Control Over Unknown Memoryless Communication Channels

We consider the distributed channel access problem for a system consisting of multiple control subsystems that close their loop over a shared wireless network. We propose a distributed method for providing deterministic channel access without requiring explicit information exchange between the subsystems. This is achieved by utilizing timers for prioritizing channel access with respect to a local cost which we derive by transforming the control objective cost to a form that allows its local computation. This property is then exploited for developing our distributed deterministic channel access scheme. A framework to verify the stability of the system under the resulting scheme is then proposed. Next, we consider a practical scenario in which the channel statistics are unknown. We propose learning algorithms for learning the parameters of imperfect communication links for estimating the channel quality and, hence, define the local cost as a function of this estimation and control performance. We establish that our learning approach results in collision-free channel access. The behavior of the overall system is exemplified via a proof-of-concept illustrative example, and the efficacy of this mechanism is evaluated for large-scale networks via simulations.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Control over communication networks : modeling, analysis, and synthesis

The focus of this work is on dynamical systems that are controlled over a communication network, also denoted as Networked Control Systems (NCSs). Such systems consist of a continuous-time plant and a discrete-time controller that are connected via a communication network, such as e.g. controller area network (CAN), wireless networks, or internet. Advantages of the use of such a network are a reduction of installation and maintenance costs and a flexible architecture. The reduction of the costs is achieved by using one (shared) processor to control multiple plants, instead of using dedicated processors for each plant. Adding or removing plants or controllers to the network is easy, which explains the benefit in terms of a flexible architecture of the control system. Moreover, the use of wireless networks obviously allows to separate the controller and plant physically. Typical applications of NCSs are mobile sensor networks, remote surgery, automated highway systems, and the cooperative control of unmanned aerial vehicles. Disadvantages of the use of such networks are the occurrence of time-varying delays, time-varying sampling intervals, and packet dropouts, i.e. loss of data. Moreover, time-varying sampling intervals and delays may also result from other sources than the communication network. Namely, in many high-tech embedded systems, the processor is used for both the control computation and other software tasks, such as interrupt and error handling. This leads to variation in the computation time or variation in the moment of asking for new sensor data, resulting in variable sampling intervals. The amount of variation depends on the chosen software implementation, the chosen architecture, and the processor load. A control design that can deal with the variation in the time-delays, sampling intervals, and the occurrence of packet dropout is important for the multidisciplinary design of high-tech systems. Namely, such robustness properties of the control design represent a relaxation on the demands from control engineering on the software and communication network design. In this thesis, a discrete-time model for linear NCSs is derived that considers time-varying delays, time-varying sampling intervals, and packet dropouts. Based on this model, examples of the destabilizing effect of variations in the delay and variations in the sampling intervals are given to show the necessity of stability conditions that consider the effects of time-varying delays, time-varying sampling intervals, and packet dropouts. To derive such stability conditions, upper and lower bounds of time-varying delays and sampling intervals are assumed, as well as a maximum number for the subsequent packet dropouts. Based on these assumptions, sufficient conditions in terms of linear matrix inequalities (LMIs) are derived that guarantee global asymptotic stability of the NCS. Two different control strategies, i.e. state feedback control and state-feedback control including past control input information are considered. For both control approaches, conditions in terms of LMIs are given for the controller synthesis problem and a comparison of the applicability of both control approaches is made. Besides the stability analysis and controller synthesis conditions, the intersample behavior is investigated to ensure stability of the continuous-time system between the sampling instants. An extension to the stability analysis conditions is given that can be used to solve the approximate tracking problem for NCSs with time-varying delays and sampling intervals and packet dropouts. Only approximate tracking can be achieved because the time-varying delays, sampling intervals, packet dropouts, and the use of a zero-order hold between the controller and actuator cause an inexact feedforward, which induces a perturbation on the tracking error dynamics. Sufficient conditions for the input-tostate stability of the tracking error dynamics are provided and an upper bound for the tracking error is given as a function of the plant properties, the control design, and the bounds on the delays, the sampling interval and the number of subsequent packet dropouts. To validate the obtained stability and controller synthesis conditions experiments are performed on a typical motion control example. First, measurements are performed to validate the stability region, i.e. all stabilizing controllers, for constant time-delays. Second, the destabilizing effect of time-variation of the delays is shown in experiments. Third, the obtained stabilizing controllers for time-varying delays, with constant sampling intervals are validated. A comparison between the stability regions for constant delays and time-varying delays shows that the stability conditions developed in this thesis are not overly conservative. The delay combinations that result in instability in the measurements confirm this observation

State estimation for coupled uncertain stochastic networks with missing measurements and time-varying delays: The discrete-time case

Copyright [2009] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This paper is concerned with the problem of state estimation for a class of discrete-time coupled uncertain stochastic complex networks with missing measurements and time-varying delay. The parameter uncertainties are assumed to be norm-bounded and enter into both the network state and the network output. The stochastic Brownian motions affect not only the coupling term of the network but also the overall network dynamics. The nonlinear terms that satisfy the usual Lipschitz conditions exist in both the state and measurement equations. Through available output measurements described by a binary switching sequence that obeys a conditional probability distribution, we aim to design a state estimator to estimate the network states such that, for all admissible parameter uncertainties and time-varying delays, the dynamics of the estimation error is guaranteed to be globally exponentially stable in the mean square. By employing the Lyapunov functional method combined with the stochastic analysis approach, several delay-dependent criteria are established that ensure the existence of the desired estimator gains, and then the explicit expression of such estimator gains is characterized in terms of the solution to certain linear matrix inequalities (LMIs). Two numerical examples are exploited to illustrate the effectiveness of the proposed estimator design schemes