Proposed Stabilization Algorithm Research Articles

Shoreline Detection Accuracy from Video Monitoring Systems

Video monitoring has become an indispensable tool to understand beach processes. However, the measurement accuracy derived from the images has been taken for granted despite its dependence on the calibration process and camera movements. An easy to implement self-fed image stabilization algorithm is proposed to solve the camera movements. Georeferenced images were generated from the stabilized images using only one calibration. To assess the performance of the stabilization algorithm, a second set of georeferenced images was created from unstabilized images following the accepted practice of using several calibrations. Shorelines were extracted from the images and corrected with the measured water level and the computed run-up to the 0 m contour. Image-derived corrected shorelines were validated with one hundred beach profile surveys measured during a period of four years along a 1.1 km beach stretch. The simultaneous high-frequency field data available of images and beach surveys are uncommon and allow assessing seasonal changes and long-term trends accuracy. Errors in shoreline position do not increase in time suggesting that the proposed stabilization algorithm does not propagate errors, despite the ever-evolving vegetation in the images. The image stabilization reduces the error in shoreline position by 40 percent, having a larger impact with increasing distance from the camera. Furthermore, the algorithm improves the accuracy on long-term trends by one degree of magnitude (0.01 m/year vs. 0.25 m/year).

Active Chatter Suppression in Low Immersion Intermittent Milling Process

Abstract Chatter in low immersion milling behaves differently from that in full immersion milling, mainly because of the non-negligible time-variant dynamics and the occurrence of period doubling bifurcation. The intermittent and time-variant characteristics make the active chatter suppression based on Lyaponov theorem a non-trivial problem. The main challenges lie in how to deal with the time-variant directional coefficient and how to construct a suitable Lyaponov function so as to alleviate the conservation, as well as the saturation of the controller. Generally, the Lyaponov stability of time-invariant dynamics is more tractable. Hence, in our paper, a first-order piecewise model is proposed to approximate the low immersion milling system as two time-invariant sub-ones that are cyclically switched. To alleviate the conservation, a novel piecewise Lyaponov function is constructed to determine the stability of each subsystem independently. The inequality conditions for determining the stability and stabilization are derived. The validity of the proposed stabilization algorithm to suppress both the hopf and period doubling bifurcation, as well as to reduce the conservation of the controller parameters have been verified.

A convex optimization approach to adaptive stabilization of discrete‐time LTI systems with polytopic uncertainties

SummaryThis paper suggests a simple convex optimization approach to state‐feedback adaptive stabilization problem for a class of discrete‐time LTI systems subject to polytopic uncertainties. The proposed method relies on estimating the uncertain parameters by solving an online optimization at each time step, such as a linear or quadratic programming, and then, on tuning the control law with that information, which can be conceptually viewed as a kind of gain‐scheduling or indirect adaptive control. Specifically, an admissible domain of stabilizing state‐feedback gain matrices is designed offline by means of linear matrix inequality problems, and based on the online estimation of the uncertain parameters, the state‐feedback gain matrix is calculated over the set of stabilizing feedback gains. The proposed stabilization algorithm guarantees the asymptotic stability of the overall closed‐loop control system. An example is given to show the effectiveness of the proposed approach. Copyright © 2014 John Wiley & Sons, Ltd.

On the stabilization of a communication satellite without measuring its angular velocity

The motion control about the center of mass of the communication satellite Yamal-200 is considered. Due to possible failure of the angular velocity sensors, an algorithm for maintaining a prescribed attitude without measuring the angular velocity was developed for this satellite. The algorithm ensures the gyroscopic stabilization of the satellite motion about the local vertical. In the course of control, the onboard computer stores projections of the flywheels' angular momentum vector on the axes of the inertial basis; the control system tries to preserve the angular momentum magnitude and direction in the inertial space based on the measurements of the angular momentum. The workability of the proposed stabilization algorithm was confirmed by flight tests.

기동형 경계로봇 안정화 시스템의 실험적 검증

기동형 경계 로봇은 공항이나 항구 등의 공공 지역을 보호하기 위한 기동형 차량 시스템에 고정되어 있는 경계 로봇을 말한다. 이러한 기동형 경계 로봇은 사격 시스템, 카메라 시스템, 임베디드 시스템 그리고 AHRS 센서로 구성되어 있다. 또한 고각과 방위각을 위한 2 축 제어가 가능하도록 설계되었다. 안정화된 영상과 사격을 위해 이 시스템은 차량의 모션으로부터 발생하는 외란에 대한 보상을 통해 안정화가 되어야 한다. 본 논문에서는 ADAMS 와 Matlab/Simulink 를 이용해서 기동형 경계로봇의 가상 모델을 생성하고 제안한 안정화 알고리즘을 시뮬레이션을 통해 검증하였다. 또한 가상 모델에 상응하는 모형의 기동형 경계 로봇과 6 축 모션 시뮬레이터를 이용하여 안정화 알고리즘을 실험적으로 검증하였다.

Geometric properties of projective constraint violation stabilization method for generally constrained multibody systems on manifolds

During numerical forward dynamics of constrained multibody systems, a numerical violation of system kinematical constraints is the important issue that has to be properly treated. In this paper, the stabilized time-integration procedure, whose constraint stabilization step is based on the projection of integration results to underlying constraint manifold via post-integration correction of the selected coordinates is discussed. A selection of the coordinates is based on the optimization algorithm for coordinates partitioning. After discussing geometric background of the optimization algorithm, new formulae for optimized partitioning of the generalized coordinates are derived. Beside in the framework of the proposed stabilization algorithm, the new formulae can be used for other integration applications where coordinates partitioning is needed. Holonomic and non-holonomic systems are analyzed and optimal partitioning at the position and velocity level are considered further. By comparing the proposed stabilization method to other projective algorithms reported in the literature, the geometric and stabilization issues of the method are addressed. A numerical example that illustrates application of the method to constraint violation stabilization of non-holonomic multibody system is reported.

2216 DFP法を用いたニューラルネットワークによる圧電複合円板の変位制御 : 学習の安定化について(S14-3 材料の傾斜機能性と圧電特性への取り組み,S14 先進材料の材料特性における弾性数理解析の新たな取り組み)

This paper discusses an effect of stabilization of learning process for DFP-based hierarchical neural network on a result of approximate optimization for controlling deformation of a piezoelectric composite disk. Though the DFP formula enables to enhance a learning speed of the neural network, a learning result of the DFP-based neural network is heavily dependent on a set of initial value for weighing coefficients. This will cause a fatal problem in the use of approximate optimization. The proposed stabilization algorithm is applied to the neural network-based approximate optimization technique. From the numerical result, it is shown that the proposed stabilization algorithm improves accuracy of an approximated optimum result using the DFP-based neural network.