scholarly journals Adaptive Fixed-Time Neural Network Tracking Control of Nonlinear Interconnected Systems

Entropy ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. 1152
Author(s):  
Yang Li ◽  
Jianhua Zhang ◽  
Xinli Xu ◽  
Cheng Siong Chin
Keyword(s):  
Neural Network ◽  
Tracking Control ◽  
Fixed Time ◽  
Convergence Time ◽  
Interconnected Systems ◽  
Adaptive Backstepping ◽  
Step Procedure ◽  
Control Scheme ◽  
Lyapunov Stability Analysis ◽  
Unknown System

In this article, a novel adaptive fixed-time neural network tracking control scheme for nonlinear interconnected systems is proposed. An adaptive backstepping technique is used to address unknown system uncertainties in the fixed-time settings. Neural networks are used to identify the unknown uncertainties. The study shows that, under the proposed control scheme, each state in the system can converge into small regions near zero with fixed-time convergence time via Lyapunov stability analysis. Finally, the simulation example is presented to demonstrate the effectiveness of the proposed approach. A step-by-step procedure for engineers in industry process applications is proposed.

scholarly journals Fixed-Time Trajectory Tracking Control of Autonomous Surface Vehicle with Model Uncertainties and Disturbances

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Jiawen Cui ◽  
Haibin Sun
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Sliding Mode ◽  
Fixed Time ◽  
Convergence Time ◽  
Model Uncertainties ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Integral Sliding Mode ◽  
Control Scheme

The issue of fixed-time trajectory tracking control for the autonomous surface vehicles (ASVs) system with model uncertainties and external disturbances is investigated in this paper. Particularly, convergence time does not depend on initial conditions. The major contributions include the following: (1) An integral sliding mode controller (ISMC) via integral sliding mode surface is first proposed, which can ensure that the system states can follow the desired trajectory within a fixed time. (2) Unknown external disturbances are absolutely estimated by means of designing a fixed-time disturbance observer (FTDO). By combining the FTDO and ISMC techniques, a new control scheme (FTDO-ISMC) is developed, which can achieve both disturbance compensation and chattering-free condition. (3) Aiming at reconstructing the unknown nonlinear dynamics and external disturbances, a fixed-time unknown observer (FTUO) is proposed, thus providing the FTUO-ISMC scheme that finally achieves trajectory tracking of ASVs with unknown parameters. Finally, simulation tests and detailed comparisons indicate the effectiveness of the proposed control scheme.

Region-Reaching Control of a Flexible-Joint Manipulator

2020 ◽  
Vol 142 (11) ◽  
Author(s):  
J. W. Yu ◽  
X. H. Zhang ◽  
J. C. Ji ◽  
J. Y. Tian ◽  
J. Zhou
Keyword(s):  
Control Problem ◽  
Tracking Control ◽  
Control Algorithm ◽  
Objective Functions ◽  
Flexible Joint ◽  
Point Tracking ◽  
Control Scheme ◽  
Lyapunov Stability Analysis ◽  
Flexible Joint Manipulator ◽  
Theoretical Results

Abstract This paper addresses the region-reaching control problem for a flexible-joint robotic manipulator which is formulated by Lagrangian dynamics. An adaptive control scheme is proposed for the manipulator system having two constrained regions which are constructed by selecting appropriate objective functions. The two joints of the flexible-joint manipulator can be, respectively, confined in different regions, and this gives more flexibility than the traditional fixed-point tracking control. By performing a straightforward Lyapunov stability analysis, a simple control algorithm is established to provide a solution for the region-reaching control problem. Finally, numerical simulations are given to validate the theoretical results.

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