Search results for " Process"
showing 10 items of 17204 documents
A Novel Intelligent Technique of Invariant Statistical Embedding and Averaging via Pivotal Quantities for Optimization or Improvement of Statistical …
2020
In the present paper, for intelligent constructing efficient (optimal, uniformly non-dominated, unbiased, improved) statistical decisions under parametric uncertainty, a new technique of invariant embedding of sample statistics in a decision criterion and averaging this criterion over pivots’ probability distributions is proposed. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, the technique of invariant statistical embedding and averaging via pivotal quantities (ISE&APQ) is independent of the choice of priors and represents a novelty i…
LMI-based 2D-3D Registration: from Uncalibrated Images to Euclidean Scene
2015
International audience; This paper investigates the problem of registering a scanned scene, represented by 3D Euclidean point coordinates , and two or more uncalibrated cameras. An unknown subset of the scanned points have their image projections detected and matched across images. The proposed approach assumes the cameras only known in some arbitrary projective frame and no calibration or autocalibration is required. The devised solution is based on a Linear Matrix Inequality (LMI) framework that allows simultaneously estimating the projective transformation relating the cameras to the scene and establishing 2D-3D correspondences without triangulating image points. The proposed LMI framewo…
Convergence of direct recursive algorithm for identification of Preisach hysteresis model with stochastic input
2015
We consider a recursive iterative algorithm for identification of parameters of the Preisach model, one of the most commonly used models of hysteretic input-output relationships. The classical identification algorithm due to Mayergoyz defines explicitly a series of test inputs that allow one to find parameters of the Preisach model with any desired precision provided that (a) such input time series can be implemented and applied; and, (b) the corresponding output data can be accurately measured and recorded. Recursive iterative identification schemes suitable for a number of engineering applications have been recently proposed as an alternative to the classical algorithm. These recursive sc…
Consistent Clustering of Elements in Large Pairwise Comparison Matrices
2018
[EN] In multi-attribute decision making the number of decision elements under consideration may be huge, especially for complex, real-world problems. Typically these elements are clustered and then the clusters organized hierarchically to reduce the number of elements to be simultaneously handled. These decomposition methodologies are intended to bring the problem within the cognitive ability of decision makers. However, such methodologies have disadvantages, and it may happen that such a priori clustering is not clear, and/or the problem has previously been addressed without any grouping action. This is the situation for the case study we address, in which a panel of experts gives opinions…
Improving stock index forecasts by using a new weighted fuzzy-trend time series method
2017
Define a new technical indicator for measuring the trend of the fuzzy time series.Introduce a new weighted fuzzy-trend time series method to forecast stock indices.Compare ex-post performances of weighted FTS methods using stock market indices.Assess statistical significance of ex-post forecast accuracy for weighted FTS methods. We propose using new weighted operators in fuzzy time series to forecast the future performance of stock market indices. Based on the chronological sequence of weights associated with the original fuzzy logical relationships, we define both chronological-order and trend-order weights, and incorporate our proposals for the ex-post forecast into the classical modeling…
Adaptive Backstepping Control of a 2-DOF Helicopter System with Uniform Quantized Inputs
2020
Author's accepted manuscript © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This paper proposes a new adaptive controller for a 2-Degree of Freedom (DOF) helicopter system in the presence of input quantization. The inputs are quantized by uniform quantizers. A nonlinear mathematical model is derived for the 2-DOF helicopter system based on Euler-Lagrange equat…
Decoupled nonlinear adaptive control of position and stiffness for pneumatic soft robots
2020
This article addresses the problem of simultaneous and robust closed-loop control of joint stiffness and position, for a class of antagonistically actuated pneumatic soft robots with rigid links and compliant joints. By introducing a first-order dynamic equation for the stiffness variable and using the additional control degree of freedom, embedded in the null space of the pneumatic actuator matrix, an innovative control approach is introduced comprising an adaptive compensator and a dynamic decoupler. The proposed solution builds upon existing adaptive control theory and provides a technique for closing the loop on joint stiffness in pneumatic variable stiffness actuators. Under a very mi…
Distributed Adaptive Consensus Tracking Control of Uncertain High-order Nonlinear Systems under Directed Graph Condition
2018
In this paper, we investigate the output consensus tracking problem for a class of high-order nonlinear systems subjected to unknown parameters and uncertain external disturbances. A novel backstepping based distributed adaptive control scheme is presented under the directed communication status. For the subsystems without direct access to time-varying desired trajectory, local estimators are introduced and the corresponding adaptive laws are designed in a totally distributed fashion. With the presented scheme, the assumption on linearly parameterized reference signal and the information exchange operation of subsystem inputs in the existing results are no longer needed. It is shown that al…
Adaptive control of uncertain nonlinear systems with quantized input signal
2018
Abstract This paper proposes new adaptive controllers for uncertain nonlinear systems in the presence of input quantization. The control signal is quantized by a class of sector-bounded quantizers including the uniform quantizer, the logarithmic quantizer and the hysteresis quantizer. To clearly illustrate our approaches, we will start with a class of single-loop nonlinear systems and then extend the results to multi-loop interconnected nonlinear systems. By using backstepping technique, a new adaptive control algorithm is developed by constructing a new compensation method for the effects of the input quantization. A hyperbolic tangent function is introduced in the controller with a new tr…
Decentralized Adaptive Control for Interconnected Nonlinear Systems with Input Quantization
2017
Abstract In this paper, a decentralized adaptive control scheme is proposed for a class of uncertain nonlinear interconnected systems with input quantization. A hysteresis uniform quantization is introduced to reduce chattering. In the control design, a smooth function is introduced with backstepping technique to compensate for the effects of interactions. It is shown that the proposed decentralized adaptive controllers can ensure global boundedness of all the signals in the closed-loop interconnected systems and the tracking errors of subsystem converge to a residual, which can be adjusted by choosing suitable design parameters. Simulation results illustrate the effectiveness of the propos…