Command-filtered compound FAT learning control of fractional-order nonlinear systems with input delay and external disturbances

2022 ◽  
Author(s):  
Javad Keighobadi ◽  
Seyed Mehdi Abedi Pahnehkolaei ◽  
Alireza Alfi ◽  
J. A. Tenreiro Machado
Keyword(s):  
Nonlinear Systems ◽  
Fractional Order ◽  
Learning Control ◽  
Input Delay ◽  
External Disturbances

Compound FAT-based Learning Control of Uncertain Fractional-Order Nonlinear Systems With Disturbance

2021 ◽  
pp. 1-1
Author(s):  
Seyed Mehdi Abedi Pahnehkolaei ◽  
Javad Keighobadi ◽  
Alireza Alfi ◽  
Hamidreza Modares
Keyword(s):  
Nonlinear Systems ◽  
Fractional Order ◽  
Learning Control

Chattering-Free Finite-Time Stability of a Class of Fractional-Order Nonlinear Systems

2019 ◽  
Author(s):  
Bin Wang ◽  
Yangquan Chen ◽  
Ying Yang
Keyword(s):  
Nonlinear Systems ◽  
Sliding Mode Control ◽  
Fractional Order ◽  
Finite Time ◽  
Sliding Mode ◽  
Time Stability ◽  
External Disturbances ◽  
Finite Time Stability ◽  
Mode Control ◽  
Chattering Free

Abstract This paper studies the chattering-free finite-time control for a class of fractional-order nonlinear systems. First, a class of fractional-order nonlinear systems with external disturbances is presented. Second, a new finite-time terminal sliding mode control method is proposed for the stability control of a class of fractional-order nonlinear systems by combining the finite-time stability theory and sliding mode control scheme. Third, by designing a controller with a differential form and introducing the arc tangent function, the chattering phenomenon is well suppressed. Additionally, a controller is developed to resist external disturbances. Finally, numerical simulations are implemented to demonstrate the feasibility and validity of the proposed method.

scholarly journals Almost Disturbance Decoupling for a Class of Fractional-Order Nonlinear Systems with Zero Dynamics

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xiaoping Liu ◽  
Yajing Zhao ◽  
Caiyun Wang ◽  
Huanqing Wang ◽  
Yucheng Zhou
Keyword(s):  
Nonlinear Systems ◽  
Fractional Order ◽  
Initial Conditions ◽  
Design Method ◽  
Tracking Error ◽  
Lyapunov Stability Theory ◽  
External Disturbances ◽  
Output Tracking ◽  
Almost Disturbance Decoupling ◽  
Disturbance Decoupling

The problem of almost disturbance decoupling is addressed for fractional-order nonlinear systems. A new definition for the norm is proposed to describe the effect of disturbances on the output tracking error for fractional-order systems. Based on the Lyapunov stability theory and the backstepping design method, a tracking controller is constructed to make the output tracking error converge to zero without external disturbances and to attenuate the effect of disturbances on the tracking error at zero initial conditions. In order to validate these theoretical results, a numerical example and two practical examples are given.

scholarly journals Lebesgue-p Norm Convergence Analysis of PDα-Type Iterative Learning Control for Fractional-Order Nonlinear Systems

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Lei Li
Keyword(s):  
Nonlinear Systems ◽  
Fractional Order ◽  
Integral Inequality ◽  
Iterative Learning Control ◽  
Learning Control ◽  
Young Inequality ◽  
Second Order ◽  
Iterative Learning ◽  
First Order ◽  
Gronwall Integral Inequality

The first-order and second-order PDα-type iterative learning control (ILC) schemes are considered for a class of Caputo-type fractional-order nonlinear systems. Due to the imperfection of the λ-norm, the Lebesgue-p (Lp) norm is adopted to overcome the disadvantage. First, a generalization of the Gronwall integral inequality with singularity is established. Next, according to the reached generalized Gronwall integral inequality and the generalized Young inequality, the monotonic convergence of the first-order PDα-type ILC is investigated, while the convergence of the second-order PDα-type ILC is analyzed. The resultant condition shows that both the learning gains and the system dynamics affect the convergence. Finally, numerical simulations are exploited to verify the results.

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