A PID controller for synchronization between master-slave neurons in fractional-order of neocortical network model

Ghasemi, Mahsa; Foroutannia, Ali; Nikdelfaz, Fatemeh

doi:10.1016/j.jtbi.2022.111311

Cited by 9 publications

(2 citation statements)

References 38 publications

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“…In the case of a trajectory-tracking controller a linear time-varying system is obtained by approximate linearization around the trajectory. The linearization obtained is shown to be controllable as long as the trajectory does not come to a stop, which implies that the system can be asymptotically stabilized by smooth linear or nonlinear feedback (Divya et al, 2022;Ghasemi et al, 2023).…”

Section: Definition Of the Trajectory-tracking Problem And The Error-...mentioning

confidence: 95%

The Feasibility of Trajectory Controller by SS Equation of an Error Model in WMR

Qev

Meshach

2022

IJEC

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There has been an increasing amount of research on WMRs. The WMRs have lots of advantages: their mechanical system is usually simple; the whole movement mostly contains two dependent motors; and their motions in two-dimensional space are quite adaptable. At the same time, the WMRs have better power efficiency. WMRs have been studied from many points of view, such as modelling control, obstacle avoidance, localization, tip-over stability, and so on. This paper discusses the control algorithm. WMRs have nonholonomic constraints. That is, the mobile robot may not be able to reach a specific position and angle in a specific time; however, the robot can reach the target in a different motion or within a limited time. In this paper, an error model based on the WMR is introduced. The model explains the error between the actual position and the ideal or target position in the continuous motion of WMRs. The error model will be transformed into a state-space equation in order to demonstrate that the algorithm that controls the WMR`s movement is controllable. By splitting the inputs into and , the whole equation is transformed into a zero-input state-space system. Then, the errors can be minimized with the optimization of the feedback. The results show that by optimizing the time-varying feedback matrix, the error is asymptotically stable and close to zero. Therefore, by adding this control law to the controller, an approach to making mobile robots follow the planned trajectory is obtained.

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Section: Definition Of the Trajectory-tracking Problem And The Error-...mentioning

confidence: 95%

The Feasibility of Trajectory Controller by SS Equation of an Error Model in WMR

Qev

Meshach

2022

IJEC

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“…However, this controller exploits the user's phase movement to adjust the exoskeleton's torque. A comparative study of different fuzzy fractional PID controllers for a lower limb exoskeleton is conducted in [72]. Findings prove that this controller outperforms the traditional PID controller in terms of tracking accuracy.…”

Section: Introductionmentioning

confidence: 97%

A Robust Fuzzy Fractional Order PID Design Based On Multi-Objective Optimization For Rehabilitation Device Control

Zaway,

Jallouli-Khlif,

Maalej

et al. 2023

Journal of Robotics and Control

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In this context, Fuzzy Fractional Order Proportional Integral Derivative (FOPID-FLC) controllers are emerged as efficient approaches due to their flexibility and ability to handle nonlinearities and uncertainties. This paper proposes the use of a FOPID-FLC controller for a two-degree-of-freedom (2-DOF) lower limb exoskeleton. Our proposal is based on an enhanced control approach that combines fuzzy logic advantages and fractional calculus benefits. Contrary to popular existing methods, that use the FLC to tune the FOPID parameters, the FLC in this work is used to generate the system torque depending on patient morphology. Indeed, our fundamental contribution is to design and implement an enhanced FOPID-FLC that achieves an adequate optimal control based on system rules composed of optimal torques and input data. The fractional calculus is approximated using successive first order filters. Next, a multi-objective optimization is established for the tuning of each FOPID parameters. Finally, the FLC is used to adjust the torque depending on the kid's age. The effectiveness of the proposed controller in various scenarios is validated based on numerical simulations. Extensive analyses prove that the FOPID-FLC outperforms the FOPID with a 90\% of improvement in terms of error performance indices and 20\% of improvement for the control action. Moreover, the controller exhibits improved robustness against uncertainties and disturbances encountered in rehabilitation environments.

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Predicting cortical oscillations with bidirectional LSTM network: a simulation study

Foroutannia

Ghasemi

2023

Nonlinear Dyn

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A PID controller for synchronization between master-slave neurons in fractional-order of neocortical network model

Cited by 9 publications

References 38 publications

The Feasibility of Trajectory Controller by SS Equation of an Error Model in WMR

The Feasibility of Trajectory Controller by SS Equation of an Error Model in WMR

A Robust Fuzzy Fractional Order PID Design Based On Multi-Objective Optimization For Rehabilitation Device Control

Predicting cortical oscillations with bidirectional LSTM network: a simulation study

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