Brain emotional learning impedance control of uncertain nonlinear systems with time delay: Experiments on a hybrid elastic joint robot in telesurgery

Souzanchi-K, Mahdi; Akbarzadeh-T, Mohammad-R.

doi:10.1016/j.compbiomed.2021.104786

Cited by 4 publications

(3 citation statements)

References 36 publications

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“…Wang et al [18] studied the tracking control of uncertain nonlinear systems under neural networks and proposed a new adaptive critical framework. Souzanchi-K and Akbarzadeh-T [19] studied the impedance control of emotional learning in the brain with time delay, integrating emotional learning into an uncertain system. Haddad and Mirkin [20] applied adaptive tracking for uncertain nonlinear systems to urban trafc.…”

Section: Introductionmentioning

confidence: 99%

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A Hierarchical Optimal Control of Uncertain and Time-Varying Knowledge Dissemination Model in Complex Network

Xia

Shen

Mashino³

et al. 2023

Discrete Dynamics in Nature and Society

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In this paper, considering the multifactor influence of the knowledge dissemination process, a new ignorant-knower-spreader-forgetter (IKSF) knowledge dissemination model is proposed, which considers internalization mechanism, degradation mechanism, communication, and willingness, as well as time-varying and uncertain parameters. First, we prove that the knowledge loss equilibrium of the model is globally asymptotically stable when the basic reproduction number R 0 < 1 , and knowledge is permanent when R 0 > 1 . Next, improving the willingness of knower individuals and reducing the knowledge degradation function of spreader individuals can make the best effect of propagation; a hierarchical control strategy is designed. At the upper layer, an effective optimal control mechanism of the IKSF knowledge dissemination model is studied to provide optimal control action and minimization costs. At the lower layer, to guarantee robustness control performance and track the control targets, an intervention optimal guaranteed cost control strategy for the IKSF knowledge dissemination system with uncertain parameters is studied. Converting the controller’s design problem into a minimization problem with linear matrix inequalities, not only the impact of uncertain parameters is reduced but also the propagation effect of the knowledge dissemination model is guaranteed. Simulation results confirm our method.

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Section: Introductionmentioning

confidence: 99%

“…It is easy to show that system (19) has a unique equilibrium E 0 on X. Hence, E 0 is the only equilibrium of system (2) in M z .…”

mentioning

confidence: 97%

A Hierarchical Optimal Control of Uncertain and Time-Varying Knowledge Dissemination Model in Complex Network

Xia

Shen

Mashino³

et al. 2023

Discrete Dynamics in Nature and Society

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“…It is applied in many fields of various industries, such as automotive production, aerospace, education and medical industry etc. [1][2][3]. The PMSM has the characteristics of large starting torque, high power factor and high efficiency [4], which is widely used in the servo control of robot [5,6].…”

Section: Introductionmentioning

confidence: 99%

Neural network dynamic surface position control of n‐joint robot driven by PMSM with unknown load observer

Yang

Meng

et al. 2022

IET Control Theory & Appl

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To solve the problems of low accuracy and poor stability due to modeling error, external disturbance and unknown load, which exist in the position servo control of permanent magnet synchronous motor (PMSM) driven joint robot, this article is to propose the radial basis function (RBF) neural networks dynamic surface control strategy with the Sage-Husa adaptive Kalman filter load torque observer. For the unknown load torque of the robot, the PMSM load torque observer is established by using the Sage-Huga adaptive Kalman filter. The RBF neural network dynamic surface controller is designed using the online approximation capability of the neural network, which is used to approximate the modeling error, external interference and filtering error generated by the dynamic surface control of the joint robot online. Combining the above strategies, the n-joint robot position controller is designed. The stability of this control strategy is demonstrated by stability analysis. Simulations and experiments on the two-joint robot show that the control strategy ensures the accuracy and stability of the joint robot position control.

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Bilateral continuous terminal sliding mode control for teleoperation systems with high-order disturbances

Zhao

Dong

et al. 2022

Nonlinear Dyn

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Brain emotional learning impedance control of uncertain nonlinear systems with time delay: Experiments on a hybrid elastic joint robot in telesurgery

Cited by 4 publications

References 36 publications

A Hierarchical Optimal Control of Uncertain and Time-Varying Knowledge Dissemination Model in Complex Network

A Hierarchical Optimal Control of Uncertain and Time-Varying Knowledge Dissemination Model in Complex Network

Neural network dynamic surface position control of n‐joint robot driven by PMSM with unknown load observer

Bilateral continuous terminal sliding mode control for teleoperation systems with high-order disturbances

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