A Nonparametric Algorithm for Data Preprocessing and Modeling Multidimensional Objects with Delay

The paper devotes to modeling tasks of multidimensional inertialess objects with delay (MIOD). The description of identification scheme of MIOD is determined. The proposed identification scheme includes not only blocks of a process and a model but also a data preprocessing block to improve modelling accuracy. A new method of data preprocessing which includes outliers detection and sparsity filling is proposed. It allows generating new training samples based on initial data that is obtained by measurement of input and output variables of the process. A software package is developed to conduct computer experiments. The results of the study show that the proposed algorithms are universal and can be applied to simulate various objects that are described with liner, nonlinear algebraic and nonlinear transcendental mathematical equations. Computational experiments have shown satisfactory accuracy of the algorithms. Proposed algorithms can be used in modeling and control tasks for inertialess objects in various areas of industry such as metallurgy, petrochemicals and etc.

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Development of an Adaptive Trajectory Tracking Control of Wheeled Mobile Robot

Revista Facultad de Ingeniería ◽

10.19053/01211129.v30.n55.2021.12022 ◽

2021 ◽

Vol 30 (55) ◽

pp. e12022

Author(s):

Guiovanny Suarez-Rivera ◽

Nelson David Muñoz-Ceballos ◽

Henry Mauricio Vásquez-Carvajal

Keyword(s):

Mobile Robot ◽

Trajectory Tracking ◽

Tracking Control ◽

Recursive Least Squares ◽

Pid Controllers ◽

Trajectory Tracking Control ◽

Modeling And Control ◽

Analysis Technique ◽

Mathematical Equations ◽

And Control

Classical modeling and control methods applied to differential locomotion mobile robots generate mathematical equations that approximate the dynamics of the system and work relatively well when the system is linear in a specific range. However, they may have low accuracy when there are many variations of the dynamics over time or disturbances occur. To solve this problem, we used a recursive least squares (RLS) method that uses a discrete-time structure first-order autoregressive model with exogenous variable (ARX). We design and modify PID adaptive self-adjusting controllers in phase margin and pole allocation. The main contribution of this methodology is that it allows the permanent and online update of the robot model and the parameters of the adaptive self-adjusting PID controllers. In addition, a Lyapunov stability analysis technique was implemented for path and trajectory tracking control, this makes the errors generated in the positioning and orientation of the robot when performing a given task tend asymptotically to zero. The performance of the PID adaptive self-adjusting controllers is measured through the implementation of the criteria of the integral of the error, which allows to determine the controller of best performance, being in this case, the PID adaptive self-adjusting type in pole assignment, allowing the mobile robot greater precision in tracking the trajectories and paths assigned, as well as less mechanical and energy wear, due to its smooth and precise movements.

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TMTDyn: A Matlab package for modeling and control of hybrid rigid–continuum robots based on discretized lumped systems and reduced-order models

The International Journal of Robotics Research ◽

10.1177/0278364919881685 ◽

2020 ◽

pp. 027836491988168 ◽

Cited By ~ 3

Author(s):

S.M. Hadi Sadati ◽

S. Elnaz Naghibi ◽

Ali Shiva ◽

Brendan Michael ◽

Ludovic Renson ◽

...

Keyword(s):

Software Package ◽

Bernoulli Beam ◽

Continuum Robots ◽

Simulation Accuracy ◽

Modeling And Control ◽

Reduced Order ◽

System Equation ◽

And Control ◽

Euler Bernoulli Beam ◽

Discretized Model

A reliable, accurate, and yet simple dynamic model is important to analyzing, designing, and controlling hybrid rigid–continuum robots. Such models should be fast, as simple as possible, and user-friendly to be widely accepted by the ever-growing robotics research community. In this study, we introduce two new modeling methods for continuum manipulators: a general reduced-order model (ROM) and a discretized model with absolute states and Euler–Bernoulli beam segments (EBA). In addition, a new formulation is presented for a recently introduced discretized model based on Euler–Bernoulli beam segments and relative states (EBR). We implement these models in a Matlab software package, named TMTDyn, to develop a modeling tool for hybrid rigid–continuum systems. The package features a new high-level language (HLL) text-based interface, a CAD-file import module, automatic formation of the system equation of motion (EOM) for different modeling and control tasks, implementing Matlab C-mex functionality for improved performance, and modules for static and linear modal analysis of a hybrid system. The underlying theory and software package are validated for modeling experimental results for (i) dynamics of a continuum appendage, and (ii) general deformation of a fabric sleeve worn by a rigid link pendulum. A comparison shows higher simulation accuracy (8–14% normalized error) and numerical robustness of the ROM model for a system with a small number of states, and computational efficiency of the EBA model with near real-time performances that makes it suitable for large systems. The challenges and necessary modules to further automate the design and analysis of hybrid systems with a large number of states are briefly discussed.

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