Topic
State vector
About: State vector is a research topic. Over the lifetime, 5479 publications have been published within this topic receiving 103755 citations.
Papers published on a yearly basis
Papers
More filters
Posted Content•
TL;DR: In this paper, the tradeoff between the communication cost and control performance was studied in an LQG control system where one of two feedback channels is discrete and incurs a communication cost.
Abstract: In this work, we study an LQG control system where one of two feedback channels is discrete and incurs a communication cost. We assume that a decoder (co-located with the controller) can make noiseless measurements of a subset of the state vector (referred to as side information) meanwhile a remote encoder (co-located with a sensor) can make arbitrary measurements of the entire state vector, but must convey its measurements to the decoder over a noiseless binary channel. Use of the channel incurs a communication cost, quantified as the time-averaged expected length of prefix-free binary codeword. We study the tradeoff between the communication cost and control performance. The formulation motivates a constrained directed information minimization problem, which can be solved via convex optimization. Using the optimization, we propose a quantizer design and a subsequent achievability result.
TL;DR: In this paper, an uncertain linear measurement model is derived and both position and heading are estimated with the instrumental variable (IV) method which can show unbiased estimation results for the uncertainty of the model.
Abstract: In this paper, we proposed a position and heading estimation algorithm using only range difference of arrival (RDOA) measurements. Based on RDOA measurements, an uncertain linear measurement model is derived and both position and heading are estimated with the instrumental variable (IV) method which can show unbiased estimation results for the uncertainty of the model. In addition, to remove the unknown bias included in the measurement model error, we augment the bias to the state vector of the model. Since the proposition inherits the characteristic of the IV method, it does not need the stochastic information of the RDOA measurement excepting the assumption that the RDOA measurement noise is zero mean and white, and the zero mean error performance can be guaranteed when variances of RDOA measurement noises are identical. Through simulations, the performance of the proposed algorithm is verified at various positions and headings in the sensor network and compared with the robust least squares method which shows a zero mean error performance under the assumption that the stochastic information is known exactly.
TL;DR: In this article, the Pontryagin maximum principle is used to solve the problem of minimal-time transfer between any two given points, and the optimal control is specified both as an open-loop and a closed-loop controller.
Abstract: The problem posed is to choose, in a optimal manner, a time-variable, bounded, linear transformation defining the velocity of a state point inn-dimensional space in terms of the state. The two-point boundary-value problem which arises from an application of the Pontryagin maximum principle is explicitly solvable; hence, a formula is derived showing that the optimal trajectories in state space are equiangular spirals in two-dimensional subspaces ofR
n
and also describing the boundary of the set of attainability. This formula is used to solve the problem of minimal-time transfer between any two given points, and the optimal control is specified both as an open-loop and a closed-loop controller. The solutions to the problem of maximizing a linear payoff function of the final state and of maximizing the angle of rotation of the state vector about the origin are also given.
16 Jun 1996
TL;DR: In this article, the salient features of reliable and repeatable algorithms dependent upon physical phenomena are described and how these characteristics are applied to develop a commercial beam tuning product, and initial results are also described.
Abstract: Beam tuning is a problem in which an operating point of a state vector must be determined such that a pregiven objective is optimized. The most reliable approaches involve application of control consistent with the requisite physics of implantation. This paper outlines the salient features of reliable and repeatable algorithms dependent upon physical phenomena and then describes how these characteristics are applied to develop a commercial beam tuning product. Initial results are also described.
06 Nov 2020
TL;DR: In this paper, the problem of quantitatively measuring the observability of the bearing only tracking system with bounded unknown input is investigated according to the linearization target tracking model, the connection between the initial state vector and measurement sequence is established, then the observable degrees for the bearing-only tracking system are defined and some properties of the observable degree are proved.
Abstract: In this paper, the problem of quantitatively measuring the observability of the bearing only tracking system with bounded unknown input is investigated According to the linearization target tracking model, the connection between the initial state vector and measurement sequence is established, then the observable degrees for the bearing only tracking system are defined and some properties of the observable degrees are proved First, the observable degrees can be applied to measure the estimation error lower bounds Second, the observable degrees are inherent properties of the target tracking system and independent of the estimation method In addition, some numerical simulations on the bearing only tracking system are implemented to demonstrate the effectiveness of the observable degrees