Complexity

Iterative Learning and Fractional Order Control for Complex Systems


Publishing date
01 Feb 2019
Status
Published
Submission deadline
21 Sep 2018

Lead Editor

1University of Jijel, Jijel, Algeria

2Benha University, Benha, Egypt

3Aristotle University of Thessaloniki, Thessaloniki, Greece

4Benemérita Universidad Autónoma de Puebla, Puebla, Mexico

5Hanoi University of Science and Technology, Hanoi, Vietnam


Iterative Learning and Fractional Order Control for Complex Systems

Description

Control theory asks how to influence the behavior of a dynamical system with appropriately chosen inputs so that the system’s output follows a desired trajectory or final state. A key notion in control theory is the feedback process: The difference between the actual and desired output is applied as feedback to the system’s input, forcing the system’s output to converge to the desired output. Feedback control has deep roots in physics and engineering.

Indeed, when a system is performing the same task repeatedly, it is advantageous to use the knowledge from the previous iterations of the same task in order to reduce the error on successive trials. An example of such a system is robot arm manipulators, when the reference trajectory is repeated over a given operation time. Using the conventional control algorithms with such systems, the same error is repeated from cycle to cycle. Iterative Learning Control (ILC) is a relatively new addition to the toolbox of control algorithm. It is concerned with the performance of systems that operate in a repetitive manner. ILC differs from most existing control methods in the sense that it exploits every possibility to incorporate past control information, such as tracking errors and control input signals, into the construction of the present control action in order to enable the controlled system to perform progressively better from operation to operation. Since the ILC method was proposed by Uchiyama and presented as a formal theory by Arimoto, this technique has been the centre of interest of many researchers over the last decades.

Fractional order control systems have also received great attention recently, from both an academic and industrial viewpoint, because of their increased flexibility (with respect to integer order systems) which allows a more accurate modelling of complex systems and the achievement of more challenging control requirements.

The aim of this special issue is to present the latest developments, trends, research solutions, and applications of ILC and fractional order control and to explore the more fertile avenues for future research. The breadth of scope for the special issue includes both theoretical research and experimental application.

We welcome original high-quality papers previously unpublished, addressing recent results for complex systems (nonlinear dynamical systems, complex dynamical networks, stochastic systems, chaotic nonlinear systems, complex mechanical structures, robots, etc.).

Potential topics include but are not limited to the following:

  • Applications of fractional order control systems
  • Bifurcation analysis and control
  • Chaos analysis, control, and anticontrol
  • Chaos modelling
  • Chaos synchronization and antisynchronization
  • Chaos-based digital communication
  • Chaos-based secure communication
  • Chaotic neural networks, electronics, and systems
  • Chaotic systems
  • Circuit realization of chaotic systems
  • Control and synchronization of complex networks
  • Control of chaotic systems
  • Fractional order control
  • Fractional order modeling of physical systems
  • Fractional system identification and optimization
  • Fuzzy fractional order controller
  • Hyperchaotic systems
  • ILC of nonlinear dynamical systems
  • ILC of complex dynamical networks
  • Decentralized ILC
  • Adaptive ILC
  • ILC of stochastic systems
  • ILC of chaotic nonlinear systems
  • ILC of complex mechanical structures and robotics
  • ILC of multiagent systems

Articles

  • Special Issue
  • - Volume 2019
  • - Article ID 7958625
  • - Editorial

Iterative Learning and Fractional Order Control for Complex Systems

Farah Bouakrif | Ahmad Taher Azar | ... | Viet-Thanh Pham
  • Special Issue
  • - Volume 2019
  • - Article ID 8948656
  • - Research Article

Results on a Novel Piecewise-Linear Memristor-Based Chaotic System

Bo Wang
  • Special Issue
  • - Volume 2019
  • - Article ID 9367291
  • - Research Article

Evaluating Fractional PID Control in a Nonlinear MIMO Model of a Hydroelectric Power Station

O. A. Rosas-Jaimes | G. A. Munoz-Hernandez | ... | C. A. Gracios-Marin
  • Special Issue
  • - Volume 2018
  • - Article ID 1872943
  • - Research Article

Adaptive Inverse Control Based on Kriging Algorithm and Lyapunov Theory of Crawler Electromechanical System

Guanyu Zhang | Yitian Wang | ... | Chen Chen
  • Special Issue
  • - Volume 2018
  • - Article ID 4019749
  • - Research Article

Complex Dynamics of the Fractional-Order Rössler System and Its Tracking Synchronization Control

Huihai Wang | Shaobo He | Kehui Sun
  • Special Issue
  • - Volume 2018
  • - Article ID 8797314
  • - Research Article

Dynamics Feature and Synchronization of a Robust Fractional-Order Chaotic System

Xuan-Bing Yang | Yi-Gang He | Chun-Lai Li
  • Special Issue
  • - Volume 2018
  • - Article ID 7941012
  • - Research Article

The Unique Existence of Weak Solution and the Optimal Control for Time-Fractional Third Grade Fluid System

Guangming Shao | Biao Liu | Yueying Liu
  • Special Issue
  • - Volume 2018
  • - Article ID 8154230
  • - Research Article

Consensus of Multi-Integral Fractional-Order Multiagent Systems with Nonuniform Time-Delays

Jun Liu | Wei Chen | ... | Ping Li
  • Special Issue
  • - Volume 2018
  • - Article ID 3249720
  • - Research Article

New Iterative Method for the Solution of Fractional Damped Burger and Fractional Sharma-Tasso-Olver Equations

Mohammad Jibran Khan | Rashid Nawaz | ... | Javed Iqbal
  • Special Issue
  • - Volume 2018
  • - Article ID 6570560
  • - Research Article

Robust Fractional-Order PID Controller Tuning Based on Bode’s Optimal Loop Shaping

Lu Liu | Shuo Zhang
Complexity
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CiteScore3.300
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