Model Free Control of Electrically Driven Manipulator by Optimized Linear Extended State Observer, based on Voltage Control Strategy

Saleki, Amir; Fateh, Mohammad Mehdi

doi:10.1109/icrom.2018.8657617

Cited by 4 publications

(2 citation statements)

References 15 publications

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“…In view of the unknown system dynamics of the robot, another method is to design the state observer of the system so that the error between the state of the observer and the system state approaches zero within a finite time, so as to use the state of the state observer to estimate the system state. Literature [10] designed an extended state observer to dynamically estimate and compensate the uncertain state and disturbance of the system, and adopt nonlinear state feedback control to improve the control performance of the system; in order to observe the disturbance signal, the literature [11] designed an adaptive backstepping sliding mode control strategy based on nonlinear disturbance observer. Literature [12] proposed an improved design of nonlinear disturbance observer for the limited model and control input chattering, but the control method remained unchanged.…”

Section: Introductionmentioning

confidence: 99%

Decentralized control of robot joints based on neural network observer

Pan

Cai

2021

E3S Web Conf.

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In actual work, the system parameters of the robot joints will change in real time or cannot be measured, and the coupling relationship between the various subsystems and the existence of modeling errors make the system model difficult to determine. Based on such problems, a neural network observation is proposed Decentralized control method for robot joints of the robot. In the actual control of the manipulator, firstly, the model of each joint subsystem is established by the decentralized control theory, and the nonlinear function approximation ability of the neural network is used to approach the uncertain part of the manipulator subsystem online through input and output data. The design observer can estimate the state of the system, and use the estimated state to design a sliding mode controller to dynamically estimate and compensate the unknown model dynamics of each independent joint, and realize the self-control of the system when the speed information and model information are unknown. Adaptive control greatly enhances the robustness and adaptability of the robotic arm system. Finally, the stability criterion of the neural network observer and the sliding mode controller is given by the Lyapunov function method, and the simulation results prove the effectiveness of the design method.

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Section: Introductionmentioning

confidence: 99%

Decentralized control of robot joints based on neural network observer

Pan

Cai

2021

E3S Web Conf.

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“…To employ these methods easily in complex practical applications, scholars have tried to find methods that do not need precise system information as much as possible. In these methods [28][29][30], the lumped disturbances such as unmodelled dynamics, unknown uncertainties and disturbances are estimated by the observers. Linear extended state observer (LESO) is well-known as a simple structure observer that can estimate not only disturbances but also unmeasured states, making it easier to implement in engineering.…”

mentioning

confidence: 99%

Observer-Based Control for a Cable-Driven Aerial Manipulator under Lumped Disturbances

Ding¹,

Yao²,

Ma³

2023

Computer Modeling in Engineering &Amp; Sciences

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With the increasing demand for interactive aerial operations, the application of aerial manipulators is becoming more promising. However, there are a few critical problems on how to improve the energetic efficiency and pose control of the aerial manipulator for practical application. In this paper, a novel cable-driven aerial manipulator used for remote water sampling is proposed and then its rigid-flexible coupling dynamics model is constructed which takes joint flexibility into account. To achieve high precision joint position tracking under lumped disturbances, a newly controller, which consists of three parts: linear extended state observer, adaptive super-twisting strategy, and fractional-order nonsingular terminal sliding mode control, is proposed. The linear extended state observer is adopted to approximate unmeasured states and unknown lumped disturbances and achieve model-free control structure. The adaptive super-twisting strategy and fractional-order nonsingular terminal sliding mode control are combined together to achieve good control performance and counteract chattering problem. The Lyapunov method is utilized to prove the overall stability and convergence of the system. Lastly, various visualization simulations and ground experiments are conducted, verifying the effectiveness of our strategy, and all outcomes demonstrate its superiorities over the existing control strategies. KEYWORDSAerial manipulator; cable-driven; adaptive super-twisting; linear extend state observer; fractional-order nonsingular terminal sliding mode Nomenclature M Inertia matrix C Coriolis and centrifugal matrix G Gravitational force vector J Inertia matrix of motors D Damping matrix of motors K s Joint stiffness matrix K d Joint damping matrix q Angular position vector of links θ Angular position vector of motors

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