As the interest of location based-service and ubiquitous environment is proliferated, the development of technologies to determine mobile station location indoors and outdoors is basically demanded for providing vario...
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As the interest of location based-service and ubiquitous environment is proliferated, the development of technologies to determine mobile station location indoors and outdoors is basically demanded for providing various services based on user's location. Representatively, GPS(Global Positioning System) is the most well-known positioning system, but actually isn't an adequate system indoors because of the weakness of positioning signals, NLOS(Non-line of sight) and multipath. Therefore, recently in order to replace it, new technologies using WLAN have been presented. In the thesis, as estimating NLOS errors between mobile station and access points using reference points, a triangulation positioning method based on signal strength will be proposed. Also, indoor positioning experiment results will be shown.
In this paper, we focus on the issue of adaptive H∞- control design for a class of linear parameter-varying (LPV) systems based on the Hamiltonian-Jacobi-Isaac (HJI) method. By combining the idea of polynomially para...
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This paper presents a numerical solution for a mobile sensor motion trajectory scheduling problem under nonholomonic constraints of a project named MAS-net, which stands for Mobile Actuator- Sensor network. The motiva...
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作者：
J.R. RiehlJ.P. HespanhaCenter for Control
Dynamical Systems and Computation Electrical and Computer Engineering Department University of California Santa Barbara CA USA
We introduce methods of hierarchically decomposing three types of graph optimization problems: all-pairs shortest path, all-pairs maximum flow,and search. Each method uses a partition on the graph to create a high lev...
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We introduce methods of hierarchically decomposing three types of graph optimization problems: all-pairs shortest path, all-pairs maximum flow,and search. Each method uses a partition on the graph to create a high level problem and several lower level problems. The computations on each level are identical, so the low level problems can be further decomposed. In this way, the problems become fractal in nature. We use these decomposition methods to establish upper and lower bounds on the optimal criteria of each problem, which can be achieved with much less computation than what is required to solve the original problem. Also, for each problem, we find an optimal number of partitions that minimizes computation time. As the number of hierarchical levels increases, the computational complexity decreases at the expense of looser bounds.
An improved reinforcement learning algorithm is proposed in this paper. This algorithm is based on linear programming method for finding the best-response policy. A pursuit example is tested and the results show that ...
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Active Queue Management (AQM) applies a suitable control policy upon detecting congestion in networks. in this paper, an adaptive Proportional-Integral (PI) controller based on Artificial Neural Networks (ANN) is appl...
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Robust nonlinear controller design with constraint on the poles' location of the linear part of closed-loop system is proposed. The design method is based on the integrator backstepping procedure and linear constr...
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The problem of designing a linear controller for nonlinear polynomial systems that results the largest domain of attraction is considered. Moreover, using the proposed algorithm, the shape of the approximation of doma...
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This paper addresses the design of state feedback H∞ robust controller that satisfies additional constraints on closed-loop poles location. Desired closed-loop poles location is considered to be a clipped sector, cor...
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For a class of nonlinear systems affine in controls and with unknown high frequency gain, we develop a hybrid control strategy that guarantees (practical) global input-to-state stability (ISS) with respect to measurem...
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For a class of nonlinear systems affine in controls and with unknown high frequency gain, we develop a hybrid control strategy that guarantees (practical) global input-to-state stability (ISS) with respect to measurement noise. We provide a design procedure for the hybrid controller and apply it to Freeman’s counterexample and minimum-phase relative degree one systems.
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