Pinning synchronization control for multi-layer complex networks via adaptive fuzzy logic system

2021 ◽  
Vol 43 (15) ◽  
pp. 3388-3398
Author(s):  
Shixiang Sun ◽  
Tao Ren ◽  
Yanjie Xu
Keyword(s):  
Fuzzy Logic ◽  
Pinning Control ◽  
Fuzzy Logic System ◽  
Reference Trajectory ◽  
Synchronization Problem ◽  
Adaptive Law ◽  
Control Scheme ◽  
Adaptive Fuzzy Logic ◽  
Synchronization Scheme ◽  
Logic System

In this paper, the pinning synchronization problem for the multi-layer networks with dynamic uncertainties is studied. The dynamical uncertainties can be approximated by a fuzzy logic system, based on which, the pinning synchronization scheme is proposed. By using Lyapunov stability theorem, the sufficient condition is given that can ensure that the multi-layer networks can synchronize to the reference trajectory with designed adaptive law. Finally, a numerical example is given to verify the effectiveness of the proposed pinning control scheme.

scholarly journals Robust Tracking Control for Robotic Manipulator via Fuzzy Logic System andH∞Approaches

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Kun Mu ◽  
Cong Liu ◽  
Jinzhu Peng
Keyword(s):  
Fuzzy Logic ◽  
Tracking Control ◽  
Robotic Manipulator ◽  
Fuzzy Logic System ◽  
Torque Control ◽  
Robust Tracking ◽  
Robust Tracking Control ◽  
External Disturbances ◽  
Control Scheme ◽  
Logic System

Based on fuzzy logic system (FLS) andH∞control methodologies, a robust tracking control scheme is proposed for robotic system with uncertainties and external disturbances. FLS is employed to implement the framework of computed torque control (CTC) method via its approximate capability which is used to attenuate the nonlinearity of robotic manipulator. The robustH∞control can guarantee robustness to parametric and dynamics uncertainties and also attenuate the effect of immeasurable external disturbances entering the system. Moreover, a quadratic stability approach is used to reduce the conservatism of the conventional robust control approach. It can be guaranteed that all signals in the closed-loop are bounded by employing the proposed robust tracking control. The validity of the proposed control scheme is shown by simulation of a two-link robotic manipulator.

scholarly journals Fuzzy Adaptation Algorithms’ Control for Robot Manipulators with Uncertainty Modelling Errors

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Yongqing Fan ◽  
Keyi Xing ◽  
Xiangkui Jiang
Keyword(s):  
Fuzzy Logic ◽  
Online Learning ◽  
Reference Model ◽  
Robot Manipulators ◽  
Fuzzy Logic System ◽  
Fuzzy Rules ◽  
Fuzzy Logic Systems ◽  
Control Scheme ◽  
Logic Systems ◽  
Logic System

A novel fuzzy control scheme with adaptation algorithms is developed for robot manipulators’ system. At the beginning, one adjustable parameter is introduced in the fuzzy logic system, the robot manipulators system with uncertain nonlinear terms as the master device and a reference model dynamic system as the slave robot system. To overcome the limitations such as online learning computation burden and logic structure in conventional fuzzy logic systems, a parameter should be used in fuzzy logic system, which composes fuzzy logic system with updated parameter laws, and can be formed for a new fashioned adaptation algorithms controller. The error closed-loop dynamical system can be stabilized based on Lyapunov analysis, the number of online learning computation burdens can be reduced greatly, and the different kinds of fuzzy logic systems with fuzzy rules or without any fuzzy rules are also suited. Finally, effectiveness of the proposed approach has been shown in simulation example.

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