Adaptive sliding mode control of robot based on fuzzy neural network

Ye, Tianchi; Luo, Zhongbao; Wang, Guiping

doi:10.1007/s12652-020-01809-2

Cited by 24 publications

(18 citation statements)

References 19 publications

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“…The sliding variables of the adaptive controller are identical to those of the robust controller given in Eq. (12). The difference is that the controller gains need not be determined as they are dynamic.…”

Section: B Control Design Using Ast Algorithmmentioning

confidence: 99%

“…First, sliding manifolds are considered as (12). Then, to satisfy sliding mode condition, the access rule is selected as follows:…”

Section: A Redefinition Of Sliding Manifoldsmentioning

confidence: 99%

“…sgn is sign function. By derivation from sliding manifolds (12) and substituting in system model ( 1) the following equations are obtained…”

Section: A Redefinition Of Sliding Manifoldsmentioning

confidence: 99%

“…For example, in [11], a Taylor series constructor approach was used for two-loop adaptive control of non-holonomic mobile robots. In [12], a real-time adaptive control framework was designed to achieve tracking of mobile robots. Based on the fuzzy neural network, an efficient control framework was provided with a combination of neural network controller and compensation controller.…”

Section: Introductionmentioning

confidence: 99%

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WITHDRAWN: Trajectory Tracking of A Mobile Robot Using Adaptive Sliding Mode Control

Rostami

Hosseinabadi

et al. 2021

Preprint

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In this paper, a control system for a mobile four-wheeled robot is designed, whose task is to create stability and achieve proper performance in the execution of commands. Due to the nonlinear and time-varying dynamics, structural and parametric uncertainties of this robot, various control approaches are used in order to achieve stability, proper performance and minimize the effect of uncertainties and modeling errors, etc. The purpose of the control here is to follow a predetermined trajectory by adjusting linear and angular velocities in the presence of external disturbances and parametric uncertainty.In previous articles, the upper band of uncertainties has been assumed known. In this paper, and given that in practice, in many cases it is not possible to know the extent of uncertainties and disturbances in robotic systems, we have assumed that this upper band is unknown. Therefore, the sliding mode control law designed in the paper has been generalized and proved its stability so that by adding an adaptive part to the controller and converting it into a robust-adaptive sliding mode control, the upper band uncertainties are estimated online using these adaptive laws. The results of this typology are expressed in a separate theorem and proved to be stable. The results of simulation with MATLAB software show that the proposed controller ensures optimal performance under external disturbances and parametric uncertainty with less fluctuations.

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Section: B Control Design Using Ast Algorithmmentioning

confidence: 99%

“…First, sliding manifolds are considered as (12). Then, to satisfy sliding mode condition, the access rule is selected as follows:…”

Section: A Redefinition Of Sliding Manifoldsmentioning

confidence: 99%

“…sgn is sign function. By derivation from sliding manifolds (12) and substituting in system model ( 1) the following equations are obtained…”

Section: A Redefinition Of Sliding Manifoldsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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WITHDRAWN: Trajectory Tracking of A Mobile Robot Using Adaptive Sliding Mode Control

Rostami

Hosseinabadi

et al. 2021

Preprint

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“…As is known, inter-symbol interference (ISI) is a major impairment for improvement in capacity or data transmission rate in wireless communication systems (WCS), especially in the field of robot wireless control (Lewis et al, 2020;Ye et al, 2020). Over the past decades, a variety of equalization methods, as well as channel estimation algorithms (Macchi and Eweda, 1984;Johnson et al, 1998;Yang et al, 2002;Chen and Chng, 2004;Ashmawy et al, 2009;Liyi et al, 2009;Yuan and Lin, 2010;Kim et al, 2012;Bhotto and Bajić, 2015;Haykin, 2015;Shah et al, 2017), have been proposed to relieve the ISI effects, thus compensating for channel distortion.…”

Section: Introductionmentioning

confidence: 99%

Concurrent Modified Constant Modulus Algorithm and Decision Directed Scheme With Barzilai-Borwein Method

Xiang

Yang³

et al. 2021

Front. Neurorobot.

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At present, in robot technology, remote control of robot is realized by wireless communication technology, and data anti-interference in wireless channel becomes a very important part. Any wireless communication system has an inherent multi-path propagation problem, which leads to the expansion of generated symbols on a time scale, resulting in symbol overlap and Inter-symbol Interference (ISI). ISI in the signal must be removed and the signal restores to its original state at the time of transmission or becomes as close to it as possible. Blind equalization is a popular equalization method for recovering transmitted symbols of superimposed noise without any pilot signal. In this work, we propose a concurrent modified constant modulus algorithm (MCMA) and the decision-directed scheme (DDS) with the Barzilai-Borwein (BB) method for the purpose of blind equalization of wireless communications systems (WCS). The BB method, which is two-step gradient method, has been widely employed to solve multidimensional unconstrained optimization problems. Considering the similarity of equalization process and optimization process, the proposed algorithm combines existing blind equalization algorithm and Barzilai-Borwein method, and concurrently operates a MCMA equalizer and a DD equalizer. After that, it modifies the DD equalizer's step size (SS) by the BB method. Theoretical investigation was involved and it demonstrated rapid convergence and improved equalization performance of the proposed algorithm compared with the original one. Additionally, the simulation results were consistent with the proposed technique.

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Rehabilitation robot following motion control algorithm based on human behavior intention

et al. 2022

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In response to the current problem of low intelligence of mobile lower limb motor rehabilitation aids. This paper proposes an intelligent control scheme based on human movement behavior in order to control the rehabilitation robot to follow the patient’s movement. Firstly, a multi-sensor data acquisition system is designed according to the rehabilitation needs of the patient and the movement characteristics of the human body. A mathematical model of movement behavior is then established. By analyzing and processing motion data, the change in the center of gravity of the human body and the behavior intention signal are derived and used as a control command for the robot to follow the human body’s movement. Secondly, in order to improve the control effect of rehabilitation robot following human motion, an adaptive radial basis function neural network sliding mode controller (ARBFNNSMC) is designed based on the robot dynamic model. The adaptive adjustment of switching gain coefficient is performed by radial basis function neural network. The controller can overcome the influence caused by the change of robot control system parameters due to the fluctuation of the center of gravity of human body, enhance the adaptability of the system to other disturbance factors, and improve the accuracy of following human body motion. Finally, the motion following experiment of the rehabilitation robot is performed. The experimental results show that the robot can recognize the motion intention of human body and perform the training goal of following different subjects to complete straight lines and curves. The correctness of human motion behavior model and robot control algorithm is verified, which shows the feasibility of the intelligent control method proposed in this paper.

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Adaptive sliding mode control of robot based on fuzzy neural network

Cited by 24 publications

References 19 publications

WITHDRAWN: Trajectory Tracking of A Mobile Robot Using Adaptive Sliding Mode Control

WITHDRAWN: Trajectory Tracking of A Mobile Robot Using Adaptive Sliding Mode Control

Concurrent Modified Constant Modulus Algorithm and Decision Directed Scheme With Barzilai-Borwein Method

Rehabilitation robot following motion control algorithm based on human behavior intention

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