scholarly journals Recursive Identification for MIMO Fractional-Order Hammerstein Model Based on AIAGS

Mathematics ◽  
2022 ◽  
Vol 10 (2) ◽  
pp. 212
Author(s):  
Qibing Jin ◽  
Bin Wang ◽  
Zeyu Wang
Keyword(s):  
Fractional Order ◽  
Search Strategy ◽  
Least Square Method ◽  
Global Search ◽  
Least Square ◽  
Hammerstein Model ◽  
Recursive Identification ◽  
Recursive Least Square ◽  
Original Algorithm ◽  
Initial Values

In this paper, adaptive immune algorithm based on a global search strategy (AIAGS) and auxiliary model recursive least square method (AMRLS) are used to identify the multiple-input multiple-output fractional-order Hammerstein model. The model’s nonlinear parameters, linear parameters, and fractional order are unknown. The identification step is to use AIAGS to find the initial values of model coefficients and order at first, then bring the initial values into AMRLS to identify the coefficients and order of the model in turn. The expression of the linear block is the transfer function of the differential equation. By changing the stimulation function of the original algorithm, adopting the global search strategy before the local search strategy in the mutation operation, and adopting the parallel mechanism, AIAGS further strengthens the original algorithm’s optimization ability. The experimental results show that the proposed method is effective.

Experimental Identification Technique of Nonlinear Beams in Time Domain

1997 ◽  
Author(s):  
Kimihio Yasuda ◽  
Keisuke Kamiya
Keyword(s):  
Time Domain ◽  
Harmonic Balance ◽  
Least Square Method ◽  
Least Square ◽  
Governing Equations ◽  
Experimental Identification ◽  
Initial Values ◽  
Nonlinear Beams ◽  
Identification Technique ◽  
The Time Domain

Abstract In previous papers the authors proposed a new experimental identification technique applicable to elastic structures. The proposed technique is based on the principle of harmonic balance, and can be classified as the frequency domain technique. The technique requires the excitation force to be periodic. This is in some cases a restriction. So another technique free from this restriction is of use. In this paper, as a first step for developing such techniques, a technique applicable to beams is proposed. The proposed technique can be classified as the time domain one. Two variations of the technique are proposed, depending on what methods are used for estimating the parameters of the governing equations. The first method is based on the usual least square method. The second is based on solving a minimization problem with constraints. The latter usually yields better results. But in this method, an iteration procedure is used, which requires initial values for the parameters. To determine the initial values, the first method can be used. So both methods are useful. Finally the applicability of the proposed technique is confirmed by numerical simulation and experiments.

Recursive field estimation and tracking for autonomous manipulation

Robotica ◽  
2011 ◽  
Vol 30 (5) ◽  
pp. 743-753 ◽  
Author(s):  
Soo Jeon
Keyword(s):  
Radial Basis Function Network ◽  
Least Square Method ◽  
Least Square ◽  
Source Tracking ◽  
Control Law ◽  
Task Space ◽  
Recursive Least Square ◽  
Wide Range ◽  
Field Estimation ◽  
Task Space Control

SUMMARYAutonomous operation of mechanical systems often requires the ability to detect and locate a particular phenomenon occurring in the surrounding environment. Being implemented to articulated manipulation, such a capability may realize a wide range of applications in autonomous maintenance and repair. This paper presents the sensor-driven task space control of an end-effector that combines the field estimation and the target tracking in an unknown spatial field of interest. The radial basis function network is adopted to model spatial distribution of an environmental phenomenon as a scalar field. Their weight parameters are estimated by a recursive least square method using collective measurements from the on-board sensors mounted to the manipulator. Then the asymptotic source tracking has been achieved by the control law based on the gradient of the estimated field. A new singularity tolerant scheme has been suggested to command the task space control law despite singular configurations. Simulation results using the three-link planar robot and the 6-revolute elbow manipulator are presented to validate the main ideas.

Design and Realization on the Optimal Quadratic Controller for the Positional Servo System of Numerical Control System

2011 ◽  
Vol 317-319 ◽  
pp. 1960-1963
Author(s):  
Li Bing Zhang ◽  
Ting Wu
Keyword(s):  
Control System ◽  
Control Method ◽  
Servo System ◽  
Least Square Method ◽  
Least Square ◽  
Servo Control ◽  
Numerical Control ◽  
Recursive Least Square ◽  
Servo Control System ◽  
Position Servo

This paper presents a technique for the position servo system of numerical control (NC) machine tool by utilizing the optimal quadratic controller. The mathematical model of the position servo control system is structured, which of the plant model is identified by making use of recursive least square method. The fundamental method of designing the optimal quadratic controller is proposed. Simulation of the optimal quadratic controller and PID controller are implemented by using MATLAB. The results of simulation show that the proposed control method of positional servo control system has better dynamic characteristics and better steady performance.

A Method for Modal Parameter Identification of Time Varying Vibration Systems

2012 ◽  
Vol 479-481 ◽  
pp. 688-693
Author(s):  
Zi Ying Wu ◽  
Kun Shi
Keyword(s):  
Linear Time ◽  
Least Square Method ◽  
Degree Of Freedom ◽  
Least Square ◽  
Modal Parameters ◽  
Time Varying ◽  
Recursive Least Square ◽  
Modal Parameter ◽  
Linear Time Invariant ◽  
Prony Method

In this paper a new time varying multivariate Prony (TVM-Prony) method is put forward to identify modal parameters of time varying (TV) multiple-degree-of-freedom systems from measured vibration responses. The proposed method is based on the classical Prony method that is often used to identify modal parameters of linear time invariant systems. The main advantage of the propose approach is that it can analyze multi-dimensional nonstationary signals simultaneously. A modified recursive least square method based on the traditional one is presented to determine the TV coefficient matrices of the multivariate parametric model established in the proposed method. The efficiency and accuracy of the identification approach is demonstrated by a numerical example, in which a TV mass-string system with three-degree-of-freedom is investigated. Satisfied results are obtained.

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