This paper is concerned with designing a distributed bounded H∞ consensus filter to estimate an array of three-dimensional (3D) nonlinear distributed parameter systems subject to bounded perturbation. An optimization framework based on mobile sensing is proposed to improve the performance of distributed filters. The measurement output is obtained from a mobile sensor network, where a phenomenon of randomly occurring sensor saturation is taken into account to reflect the reality in a mobile networked environment. A sufficient condition is established by utilizing operator-dependent Lyapunov functional for the filtering error system to be finite-time bounded. Note that the velocity law of each mobile sensor is included in this condition. The effect from the exogenous perturbation to the estimation accuracy is guaranteed at a given level by means of H∞ consensus performance constraint. Finally, simulation examples are presented to demonstrate the applicability of the theoretical results.
This paper investigates the formation problem of an array of large-scale mobile sensor networks. A new framework for the dynamic of mobile sensors as a continuum described by the parabolic system with boundary disturbance is proposed. The communication topology of agents is a chain graph and fixed. Leader feedback laws which are designed in a manner to the boundary control of large-scale mobile sensor networks allow the mobile sensors to achieve the formation steadily. By referring to the Lyapunov functional method and employing a boundary control approach, a new protocol is established to deal with a formation problem for the large-scale mobile sensor networks. Finally, numerical examples are given to illustrate the usefulness of the results.
In this paper, design of infinite dimensional distributed consensus filter is addressed for a class of spatially distributed processes utilising mobile sensor networks with multiple packet losses. The missing information is drawn into a sensor network in such a way that it conforms to a conditional probability distribution. A new framework for optimisation of mobile sensors is presented to enhance the performance of the filter. The goal of filtering issue is to construct a distributed consensus filter, for any possible measurements that are missing, such that the filtering error converge to bounded consensus in the mean square. Using the Lyapunov direct method and the spatial operator, certain sufficient criteria for the desired filter to satisfy the consensus performance criterion are developed. Lastly, a numerical simulation is performed to show that the suggested filter presented is effective.
This paper investigates the consensus problem of an array of large
mobile sensor networks. A new framework for the dynamic of mobile
sensors as a continuum which described by parabolic system with boundary
disturbance is proposed. The communication topology of agents is a chain
graph and fixed. Leader feedback laws which is designed in a manner to
the boundary control of large mobile sensor networks allow the mobile
sensors achieve the formation steadily. By referring to Lyapunov
functional method and employing boundary control approach, a new
protocol is established to deal with formation problem for the large
mobile sensor networks. Finally, numerical examples are given to
illustrate the usefulness of the results.
This paper investigates the distributed
H
∞
consensus filtering issue for a class of distributed parameter systems with bounded disturbance. In a framework of optimizing performance, a new approach to improving filter performance is proposed by employing mobile sensor networks. Moreover, the information missing in mobile sensor networks is modeled as a conditional probability distribution. The aim of the filtering challenge is to construct a distributed consensus filter such that the filtering error system is globally asymptotically stable in the mean square, and what disturbances do to the estimation accuracy is attenuated at the
H
∞
consensus performance level. Utilizing the Lyapunov direct approach and the spatial operator technique, several sufficient criteria are given for the proposed filter to satisfy the
H
∞
consensus performance constraint. Finally, a numerical simulation is given to demonstrate the effectiveness of the design scheme of the proposed filter.
This paper study the sampled-data control problem of a class of distributed parameter systems. A novel sampled-data control scheme is presented using mobile actuatorsensor networks. By utilizing a Lyapunov functional which depend on spatial parameter, a controller combine to decentralized static output feedback control scheme and the point measurement of the mobile sensor is designed to derive several sufficient criteria ensuring the distributed parameter systems to be globally asymptotically stable. The criteria are given in the form of linear operator inequalities and the velocity law of each mobile actuator/sensor. It is also shown that static sampleddata control of distributed parameter systems is just a special case of our main results. A numerical simulations illustrate the effectiveness of the proposed control scheme in enhancing system performance.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.