MIMO adaptive fuzzy terminal sliding-mode controller for robotic manipulators

Li, Tzuu-Hseng S.; Huang, Ya‐Chun

doi:10.1016/j.ins.2010.08.009

Cited by 146 publications

(65 citation statements)

References 55 publications

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“…1, as an example to demonstrate the proposed control scheme. The inverse dynamic model is expressed as [6]- [8]: The dynamic equation for the robot shown in Fig. 1 can be rewritten as: Position control, or also the so-called regulation problem is one of the most relevant issues in the operation of robot manipulators.…”

Section: Robot Modelingmentioning

confidence: 99%

A Control Scheme for Industrial Robots Using Artificial Neural Networks

Dinary¹,

El‐Sayed²,

Badie³

et al. 2015

IJMMM

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Section: Robot Modelingmentioning

confidence: 99%

A Control Scheme for Industrial Robots Using Artificial Neural Networks

Dinary¹,

El‐Sayed²,

Badie³

et al. 2015

IJMMM

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“…Sliding-Mode Control (SMC) is e ciently applied for the stabilization and controller design of various linear and nonlinear dynamical systems such as singular systems [2], robotic manipulators [3], nonholonomic mobile robots [4,5], fractional order systems [6], chaotic systems [7,8], under-actuated systems [9], etc. SMC is an in uential control technique, which has access to the favorite responses in spite of the uncertainties and disturbances [10,11].…”

Section: Introduction 1background and Motivationsmentioning

confidence: 99%

Nonsingular fast terminal sliding-mode stabilizer for a class of uncertain nonlinear systems based on disturbance observer

Mobayen

Tchier

2017

Scientia Iranica

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Abstract. This paper investigates a novel nonsingular fast terminal sliding-mode control method for the stabilization of the uncertain time-varying and nonlinear thirdorder systems. The designed disturbance observer satis es the nite-time convergence of the disturbance approximation error and the suggested nite-time stabilizer assures the presence of the switching behavior around the switching curve in the nite time. Furthermore, this approach can overcome the singularity problem of the fast terminal sliding-mode control technique. Moreover, knowledge about the upper bounds of the disturbances is not required and the chattering problem is eliminated. Usefulness and e ectiveness of the o ered procedure are con rmed by numerical simulation results.

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“…The major disadvantages of the variable structure control method are first, chattering, i.e., the occurrence of undesired vibrations and second, the lack of a priori knowledge about function bounds. Extensions with elements of intelligent control as neural networks by Van Cuong et al [1] or fuzzy logic by Roopaei et al [2], Li et al [3], Li et al [4] were introduced to overcome these drawbacks.…”

Section: Introduction mentioning

confidence: 99%

Robust BELBIC-Extension for Trajectory Tracking Control

Klecker

Hichri

Plapper

2017

JMEA

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Abstract:In real-life trajectory tracking applications of robotic manipulators uncertain robot dynamics, external disturbances and switching constraints which cannot be accommodated for by a conventional controller affect the system performance. We suggested an additional control element combining sliding mode and bio-mimetic, neurologically-inspired BELBIC (brain emotional learning-based intelligent control). The former is invariant to internal and external uncertainties and guarantees robust behavior. The latter is based on an interplay of inputs relating to environmental information through error-signals of position and sliding surfaces and of emotional signals regulating the learning rate and adapting the future behaviour based on prior experiences and with the goal to maximize a reward function. We proofed the stability and the performance of the suggested control scheme through Lyapunov theory and numerical simulations, respectively.

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MIMO adaptive fuzzy terminal sliding-mode controller for robotic manipulators

Cited by 146 publications

References 55 publications

A Control Scheme for Industrial Robots Using Artificial Neural Networks

A Control Scheme for Industrial Robots Using Artificial Neural Networks

Nonsingular fast terminal sliding-mode stabilizer for a class of uncertain nonlinear systems based on disturbance observer

Robust BELBIC-Extension for Trajectory Tracking Control

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