Endpoint perfect tracking control of robots — A robust non inversion-based approach

Izadbakhsh, Alireza; Rafiei, S.M.R.

doi:10.1007/s12555-009-0603-z

Cited by 28 publications

(15 citation statements)

References 25 publications

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“…To show the capability of the proposed controller in tasks where precise tracking of fast and complex trajectories is required, we used a second desired trajectory as Reference , where the initial manipulator configuration is

q (0) = {([], \begin{array}{c} 3.4218 & 2.2805 & 0.1971 & - 1.348 & 1.742 & 0.1406 \end{array})}^{T}

. This trajectory is very important, since it involves rapid and complex reactions between different dynamics of the manipulator.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In order to develop our control scheme, assume that Equation (20) can be represented by a nonlinear differential equation, called “ available model ” as

{\overset{J}{true}}_{s} (boldq) (\ddot{boldx} + F) = u (t)

where

F = {\overset{J}{true}}_{s}^{- 1} (boldq) ((M (boldx) - {\overset{J}{true}}_{s} (boldq)) \ddot{boldx} + N (x, \dot{boldx}) \dot{boldx} + G (boldx)) \in ℜ^{m}

is referred to as the lumped uncertainty.Remark Some previous valuable published works have exploited the universal approximation property of Neural Network (NN) to actuator nonlinearities compensation, although the problems originated by NN and Fuzzy approaches still exist, as mentioned in References .…”

Section: Dynamic Modelingmentioning

confidence: 99%

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Robust adaptive control of robot manipulators using Bernstein polynomials as universal approximator

Izadbakhsh

Khorashadizadeh

2020

Intl J Robust & Nonlinear

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This article presents a robust adaptive controller for electrically driven robots using Bernstein polynomials as universal approximator. The lumped uncertainties including unmodeled dynamics, external disturbances, and nonimplemented control signals (they assumed as a function of time, instead a function of several variables) are represented with this powerful mathematical tool. The polynomial coefficients are then tuned based on the adaptation law obtained in the stability analysis. A comprehensive approach is adopted to include the saturated and unsaturated areas and also the transition between these areas in the stability analysis. As a result, the stability and the performance of the proposed controller have been improved considerably in dealing with actuator saturation. Also, in comparison with a recent paper based on uncertainty estimation using Taylor series, the proposed controller is less computational due to reducing the size of the matrix of convergence rate. A performance evaluation has been carried out to verify satisfactory performance of transient response of the controller.Simulation results on a Puma560 manipulator actuated by geared permanent magnet dc motors have been presented to guarantee its satisfactory performance. K E Y W O R D Sactuator saturation, adaptive uncertainty estimation, Bernstein polynomials, electrically driven robots, stability analysis 1 Int J Robust Nonlinear Control. 2020;30:2719-2735.wileyonlinelibrary.com/journal/rnc

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q (0) = {([], \begin{array}{c} 3.4218 & 2.2805 & 0.1971 & - 1.348 & 1.742 & 0.1406 \end{array})}^{T}

. This trajectory is very important, since it involves rapid and complex reactions between different dynamics of the manipulator.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In order to develop our control scheme, assume that Equation (20) can be represented by a nonlinear differential equation, called “ available model ” as

{\overset{J}{true}}_{s} (boldq) (\ddot{boldx} + F) = u (t)

where

F = {\overset{J}{true}}_{s}^{- 1} (boldq) ((M (boldx) - {\overset{J}{true}}_{s} (boldq)) \ddot{boldx} + N (x, \dot{boldx}) \dot{boldx} + G (boldx)) \in ℜ^{m}

Section: Dynamic Modelingmentioning

confidence: 99%

Robust adaptive control of robot manipulators using Bernstein polynomials as universal approximator

Izadbakhsh

Khorashadizadeh

2020

Intl J Robust & Nonlinear

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“…If disturbance is δ(t) = t.cos(wt), then p = 4, b 1 = b 3 = 0, b 2 = −2w 2 , and b 4 = −1 − w 4 are recommended. 50,52 As a further example, consider the differential equation δ (2) (t) = 0 which is satisfied by δ(t) = t. In the first view, it is possible to think that δ(t) = t is not in the postulated form (11), which is not true. It can be easily shown that, choosing…”

Section: Remarkmentioning

confidence: 99%

Tracking Control of Electrically Driven Robots Using a Model-free Observer

Izadbakhsh¹,

Khorashadizadeh²,

Kheirkhahan³

2018

Robotica

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SummaryThis paper presents a robust tracking controller for electrically driven robots, without the need for velocity measurements of joint variables. Many observers require the system dynamics or nominal models, while a model-free observer is presented in this paper. The novelty of this paper is presenting a new observer–controller structure based on function approximation techniques and Stone–Weierstrass theorem using differential equations. In fact, it is assumed that the lumped uncertainty can be modeled by linear differential equations. Then, using Stone–Weierstrass theorem, it is verified that these differential equations are universal approximators. The advantage of proposed approach in comparison with previous related works is simplicity and reducing the dimensions of regressor matrices without the need for any information of the systems’ dynamic. Simulation results on a 6-degrees of freedom robot manipulator driven by geared permanent magnet DC motors indicate the satisfactory performance of the proposed method in overcoming uncertainties and reducing the tracking error. To evaluate the performance of proposed controller in practical implementations, experimental results on an SCARA manipulator are presented.

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“…In this section, we consider actuator saturation compensation to achieve optimal tracking and disturbance rejection for the motion control of robots as an extended form of [16]. For this purpose, suppose (4) is rewritten in the following state and output equation form as …”

Section: Description Of Control Structurementioning

confidence: 99%

“…The core idea of these defenitions is that perturbation can be approximated by a p th order ordinary differential equation (ODE) as (18) [16,17].…”

Section: Description Of Control Structurementioning

confidence: 99%

A robust anti-windup control design for electrically driven robots — Theory and experiment

Izadbakhsh

Kalat

Fateh

et al. 2011

Int. J. Control Autom. Syst.

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A Robust Anti-Windup Control (RAWC) method is proposed for n-Degree-of-Freedom (DOF) electrically driven robots considering the actuator voltage saturation. The actuator's saturation is fairly modeled by a smooth nonlinear function and the control design task is developed to avoid windup besides being robust against both model uncertainties and external disturbances. As a major point, the paper also takes into consideration the fact that windup phenomenon can be caused by some strong disturbances. As a result, being robust to external disturbances promises safer situation against windup. The proposed controller needs no saturation output feedback and torque's measurement for control implementation. The analytical studies as well as the experimental results produced using MATLAB/SIMULINK External Mode Control on a 2-DOF robot manipulator driven by geared Permanent magnet DC motors prove the superiority of the proposed approach.

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Endpoint perfect tracking control of robots — A robust non inversion-based approach

Cited by 28 publications

References 25 publications

Robust adaptive control of robot manipulators using Bernstein polynomials as universal approximator

Robust adaptive control of robot manipulators using Bernstein polynomials as universal approximator

Tracking Control of Electrically Driven Robots Using a Model-free Observer

A robust anti-windup control design for electrically driven robots — Theory and experiment

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