Information-Driven Mobility Control in Mobile Sensor Networks

A mobile sensor network is a powerful tool used to monitor physical phenomena and to provide services over an area of interest. This dissertation addresses mobility control problems, which occur when a mobile sensor network is used to perform multiple simultaneous tasks in addition to coverage. First, we provide a distributed iterative motion control algorithm through cubic and bicubic spline interpolation for scalar field estimation. We prove the convergence of the algorithm that solves for the spline coefficients. We incorporate this algorithm into a coverage control problem whereby we estimate event occurrence density function that drives the mobile sensor nodes to an optimal sensing configuration. Second, we model the cost of information aggregation and develop a distributed motion control algorithm for the network to achieve optimal configuration under three basic types of network structures. In order to ensure low data query latency, the hierarchical network structure has to be well-balanced. We formulate the problem of a query-aware constrained coverage with information aggregation. Within this formalism, we study how routing constraints can be enforced in coverage control with information aggregation. Consequently, we develop a motion control algorithm that drives the mobile sensor nodes to an optimal configuration while ensuring low latency of query processing. Third, we generalize information aggregation to information dissemination where information generated in the area is disseminated to multiple or even an infinite number of destinations in the same area. We study how information dissemination can be modeled through optimization of an appropriate cost function and propose a distributed motion control algorithm that drives the mobile sensor nodes to an optimal configuration

A recommended value of <i>b</i>_<i>i</i> and <i>b</i>_6−<i>i</i>.

<p>A recommended value of <i>b</i>_<i>i</i> and <i>b</i>_6−<i>i</i>.</p

A New Fuzzy-Evidential Controller for Stabilization of the Planar Inverted Pendulum System

<div><p>In order to realize the stability control of the planar inverted pendulum system, which is a typical multi-variable and strong coupling system, a new fuzzy-evidential controller based on fuzzy inference and evidential reasoning is proposed. Firstly, for each axis, a fuzzy nine-point controller for the rod and a fuzzy nine-point controller for the cart are designed. Then, in order to coordinate these two controllers of each axis, a fuzzy-evidential coordinator is proposed. In this new fuzzy-evidential controller, the empirical knowledge for stabilization of the planar inverted pendulum system is expressed by fuzzy rules, while the coordinator of different control variables in each axis is built incorporated with the dynamic basic probability assignment (BPA) in the frame of fuzzy inference. The fuzzy-evidential coordinator makes the output of the control variable smoother, and the control effect of the new controller is better compared with some other work. The experiment in MATLAB shows the effectiveness and merit of the proposed method.</p></div

Fuzzy-evidential controller for the planar inverted pendulum system.

<p>Fuzzy-evidential controller for the planar inverted pendulum system.</p

Fuzzy controller of the rod.

<p>Fuzzy controller of the rod.</p

The setup of the planar inverted pendulum system.

<p>The setup of the planar inverted pendulum system.</p

Fuzzy controller of the cart.

<p>Fuzzy controller of the cart.</p

The deviation of the rod in each axis.

<p>The deviation of the rod in each axis.</p