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recursive calculation of expansion coefficients for generalized orthonormal rational bases

IFAC Proceedings Volumes 1999年第2期32卷 4141-4146页

作者： Per Bodin S3-Automatic Control The Royal Institute of Technology 100 44 Stockholm Sweden

A recursive scheme is derived for calculation of the expansion coefficients of a known system transfer function into a generalized orthonoimal rational basis. The inherent structure of the basis functions leads to a computationally efficient method, which needs the solution of a low-dimensional Sylvester equation at each step. The method is demonstrated with a brief example. Possible applications are also discussed.

关键词： All pass filters Filter banks Function approximation Least-squares approximation recursive algorithms State-space realization Transfer functions

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Parameters Identification of Robots Manipulators via Sequential Hybrid Estimation algorithms

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IFAC Proceedings Volumes 1990年第8期23卷 163-168页

作者： C. Canudas de Wit A. Aubin Laboratoire d'Automatique de Grenoble ENSIEG-INPG B.P. 46 38402 Saint-Martin-d'Hères France

This paper deals with the problem of improving the parameter identifiability properties of robot model. Through the exploitation of the upper-triangular structure of the information matrix, the estimation of the invariants (masses, inertias, etc). which usually requires at the most 11 n parameters for a robot manipulator with n degrees of freedom (DOF), can be performed link by link in a sequential manner by n algorithms of size n i where Σ n i is smaller than 11n. Optimization of the robot trajectories seeking to improve parameters identifiability can be simplified. A study case is presented of a 4-DOF robot used for nuclear maintenance having three co-linear axes. Instead of having a single-pass algorithm of dimension 12, the method yields a 4-passes estimation algorithm with a parameter vector dimension of 4, 4, 3 and 1 respectively for each pass. This method enhances the numerical algorithm conditioning and facilitates the selection of a high excited identification sequence improving the parameter identifiability.

关键词： Identification of robot models parameter identifiability recursive algorithms hybrid identification

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Identification of Hammerstein and Wiener Models Using Spectral Magnitude Matching

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IFAC Proceedings Volumes 2008年第2期41卷 6440-6445页

作者： Emad Abd-Elrady Li Gan Christian Doppler Laboratory for Nonlinear Signal Processing Institute of Signal Processing and Speech Communication Graz University of Technology. Inffeldgasse 16b A-8010 Graz Austria

The problem of the identification of Hammerstein and Wiener models is considered in this paper. The suggested approach in this paper utilizes the spectral magnitude matching method that minimizes the sum squared error between the spectral magnitudes - evaluated for a number of short-time frames - of the measured output signal of the nonlinear system and the output signal of the nonlinear model. The coefficients of Hammerstein and Wiener models are estimated using the generalized Newton iterative algorithm. Simulation results show that the suggested approach gives very good results especially for moderate and high signal to noise ratios.

关键词： Nonlinear models Nonlinear systems Parameter estimation recursive algorithms System identification

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Nested particle filters for online parameter estimation in discrete-time state-space Markov models

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Bernoulli 2018年第4A期24卷 3039-3086页

作者： Dan Crisan Joaquín Míguez Univ Carlos III Madrid Dept Signal Theory & Commun Ave Univ 30 Madrid 28911 Spain Imperial Coll London Dept Math Huxley Bldg180 Queens Gate London SW7 2BZ England

We address the problem of approximating the posterior probability distribution of the fixed parameters of a state-space dynamical system using a sequential Monte Carlo method. The proposed approach relies on a nested structure that employs two layers of particle filters to approximate the posterior probability measure of the static parameters and the dynamic state variables of the system of interest, in a vein similar to the recent “sequential Monte Carlo square” (SMC2) algorithm. However, unlike the SMC2 scheme, the proposed technique operates in a purely recursive manner. In particular, the computational complexity of the recursive steps of the method introduced herein is constant over time. We analyse the approximation of integrals of real bounded functions with respect to the posterior distribution of the system parameters computed via the proposed scheme. As a result, we prove, under regularity assumptions, that the approximation errors vanish asymptotically in Lp (p≥1) with convergence rate proportional to 1N+1M, where N is the number of Monte Carlo samples in the parameter space and N×M is the number of samples in the state space. This result also holds for the approximation of the joint posterior distribution of the parameters and the state variables. We discuss the relationship between the SMC2 algorithm and the new recursive method and present a simple example in order to illustrate some of the theoretical findings with computer simulations.

关键词： error bounds model inference Monte Carlo Parameter estimation particle filtering recursive algorithms state space models

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Dynamics of Flexible Manipulators: A Newton-Euler Based Approach

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IFAC Proceedings Volumes 1995年第16期28卷 175-180页

作者： Frédéric Boyer Philippe Coiffet Ecole des Mines de Nantes 4 rue Alfred Kastler 44070 Nantes France Laboratoire de Robotique de Paris 10 av. de l'Europe 78140 Vélizy France

In this paper an extension of the Newton - Euler models to the case of flexible robots is achieved. Today, such models are mainly used for rigid manipulators. In this case they give the best results to solve the simulation and control problems, as far as time consumption and programming simplicity are concerned. Here, the extension proposed is based on the theoretical notion of description formalism of a motion and on the use of the D'Alembert principle.

关键词： Flexible arm Dynamic modelling recursive algorithms Inverse dynamic problem Control algorithms

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AN INTELLIGENT GENERALIZED PREDICTIVE CONTROLLER FOR SHIP STEERING

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IFAC Proceedings Volumes 2007年第12期40卷 609-614页

作者： Yaohua Hu Suwu Xu Zongnian Zhang Department of Electronic Engineering Dongguan University of Technology Dongguan Guangdong 523808 P. R. China

A generalized predictive controller for ship's steering is introduced. The parameters of the controller can be online adjusted based on some intelligent rules according to the heading error and the differential of the heading error. A recursive algorithm, which is based on the matrix disintegration, is used for matrix inversion; it needs as one third execution time as that of the general algorithm. Simulating results show that the intelligent controller can offset the effects of low frequency disturbances such as wind and current, follow the reference course and track quickly and accurately, and have good transient and steady state performances.

关键词： generalized predictive control intelligent control ship control recursive algorithms matrix inversion

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recursive Approach of H ∞ Control Problems for Nonstandard Singularly Perturbed Systems Under Imperfect State Measurements

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IFAC Proceedings Volumes 1998年第25期31卷 33-38页

作者： H. Mukaidani H. Xu K. Mizukami Graduate School of Engineering Hiroshima University 1-7-1 Kagamiyama Higashi-Hiroshima. JAPAN 739-0046 Faculty of Integrated Arts and Sciences Hiroshima University 1-7-1 Kagamiyama Higashi-Hiroshima JAPAN 739-0046

In this paper, we study the H ∞ control problem for singularly perturbed systems under imperfect state measurements by using the recursive approach. We construct a controller that guarantees a disturbance attenuation level larger than a boundary value of the reduced-order slow and fast subsystems when the singular perturbation parameter ε approaches zero. In order to obtain the controller, we must solve the generalized algebraic Riccati equations. The main results in this paper is to propose a new recursive algorithm to solve the generalized algebraic Riccati equations and to find sufficient conditions for the convergence of the proposed algorithm.

关键词： H ∞ control Singular perturbations Algebraic Riccati equations recursive approaches recursive algorithms

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Parametric System Identification in the Presence of Uncertainty with Model Validation Constraints

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IFAC Proceedings Volumes 1996年第1期29卷 4052-4056页

作者： Er-Wei Bai Roberto Tempo Krishan Nagpal Dept. of Electrical and Electronic Engineering Hong Kong University of Science and Technology on leave from Dept. of Elec. and Comp. Engineering University of Iowa Iowa City Iowa 52242 USA CENS-CNR Politecnico di Torino 10129 Torino Italy Dept of Electrical Engineering and Computer Science University of Michigan

This paper presents two recursive algorithms for parametric identification in the presence of both, noise and model uncertainties. The estimates provided by these algorithms are not invalidated by the observed input-o... 详细信息

关键词： Parametric System Identification Uncertainty Model Validation recursive algorithms

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recursive LEAST SQUARES WITH LINEAR CONSTRAINTS

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COMMUNICATIONS IN INFORMATION AND SYSTEMS 2007年第3期7卷 287-311页

作者： Zhu, Yumin Li, X. Rong Sichuan Univ Coll Math Key Lab Fundamental Sci Natl Defense Chengdu 610064 Sichuan Peoples R China Univ New Orleans Dept Elect Engn New Orleans LA 70148 USA

recursive Least Squares (RLS) algorithms have wide-spread applications in many areas, such as real-time signal processing, control and communications. This paper shows that the unique solutions to linear-equality constrained and the unconstrained LS problems, respectively, always have exactly the same recursive form. Their only difference lies in the initial values. Based on this, a recursive algorithm for the linear-inequality constrained LS problem is developed. It is shown that these RLS solutions converge to the true parameter that satisfies the constraints as the data size increases. A simple and easily implementable initialization of the RLS algorithm is proposed. Its convergence to the exact LS solution and the true parameter is shown. The RLS algorithm, in a theoretically equivalent form by a simple modification, is shown to be robust in that the constraints are always guaranteed to be satisfied no matter how large the numerical errors are. Numerical examples are provided to demonstrate the validity of the above results.

关键词： Restless Legs Syndrome Converge recursive algorithms Constraint data size algorithms recursive least squares

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Friction State Classification Based on Vehicle Inertial Measurements

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IFAC-PapersOnLine 2019年第5期52卷 72-77页

作者： Donald Selmanaj Matteo Corno Sergio M. Savaresi Department of Automation Polytechnic University of Tirana Sheshi “Nënë Tereza” Nr.4 Tirana Albania Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano Piazza L. da Vinci 32 20133 Milano Italy

Tire-road friction is the most important characteristic defining the planar dynamics of wheeled vehicles. It has consequences on the drivability, stability and tuning of the active vehicle dynamics control systems. This paper proposes two online friction estimation methods designed for the adaptation of vehicle dynamics control algorithms. The problem is framed as a classification problem where inertial measurements are used to discriminate between high and low friction regimes. The first method merges a recursive least-squares (RLS) algorithm with a heuristic bistable logic to classify the friction condition and promptly react to its changes. The second method runs a classification algorithm on the slip-acceleration characteristic. Both methods simultaneously account for the longitudinal and lateral dynamics and are tested on experimental data.

关键词： Friction Vehicles dynamics Classification recursive algorithms Nonlinear algorithms

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