Complexity

Control Design for Systems Operating in Complex Environments


Publishing date
01 Jan 2019
Status
Published
Submission deadline
17 Aug 2018

Lead Editor

1South China University of Technology, Guangzhou, China

2Portsmouth University, Portsmouth, UK

3Hohai University, Nanjing, China

4National Institute of Advanced Industrial Science and Technology, Tokyo, Japan

5University of Winchester, Hampshire, Elgin, UK


Control Design for Systems Operating in Complex Environments

Description

In the past decade, the technical requirements of control systems have become more stringent to be applicable to many aspects of industrial applications and automation devices, ranging from robots in manufacturing, underwater vehicles, and unmanned aerial vehicles to human–robot interaction. However, these applications and devices always need to operate in a complex environment. The growing number of applications in complex engineering environments, along with the increasing requirements and demands for the system stability, safety, and reliability, is posing new theoretical and technological challenges for the advanced controller design.

One major challenge is the provision of innovative solutions to deal with the complex operation environment. A general and illustrative definition of complex environment could be “a scenario which is dynamic and uncertain” (e.g., unknown environment model, high spatiotemporal complexity, rapid changes of light intensities, and unknown disturbances). The complex and dynamic environment often leads to a rapidly increasing complexity of the control algorithm and then results in difficulties for real-time controllers. Therefore, revealing the properties and behaviors of systems operating in the complex environment could not only bring in novel control designs but also provide solutions for systems operating realistically and efficiently in complex and unmodeled scenarios.

This special issue will present advances in the control design for systems operating in complex environments and will provide a comprehensive overview of future solutions from various computational and engineering aspects. The authors are invited to present mathematical theories, algorithms, frameworks, experiments, and applications aiming at bringing about advanced control techniques for systems working within complex and unpredictable behaviors such as structural/structural uncertainties, unknown nonlinearities, time-varying delays, unknown external disturbances, unpredictable human motions, and uncertain system dynamics.

Potential topics include but are not limited to the following:

  • Robot manipulator control in complex environments
  • Human–robot interaction in complex environments
  • Underwater vehicle control in complex environments
  • Robot motion learning in complex environments
  • Unmanned aerial vehicle control in complex environments
  • Fault-tolerant control in complex environments
  • Robot sensing and exploring technologies in complex environments
  • Disturbance observation based control in complex environments
  • Complex gesture/motion recognition with multimodal information
  • Optimization for systems in complex environments

Articles

  • Special Issue
  • - Volume 2019
  • - Article ID 6723153
  • - Editorial

Control Design for Systems Operating in Complex Environments

Chenguang Yang | Zhaojie Ju | ... | Andy Annamalai
  • Special Issue
  • - Volume 2019
  • - Article ID 8616215
  • - Research Article

Vehicle Text Data Compression and Transmission Method Based on Maximum Entropy Neural Network and Optimized Huffman Encoding Algorithms

Jingfeng Yang | Zhenkun Zhang | ... | Yu Zhang
  • Special Issue
  • - Volume 2019
  • - Article ID 7456031
  • - Research Article

The Action Control Model for Robotic Fish Using Improved Extreme Learning Machine

XueXi Zhang | ShuiBiao Chen | ... | Zefeng Hu
  • Special Issue
  • - Volume 2019
  • - Article ID 5470974
  • - Research Article

A Cooperative Spectrum Sensing Method Based on Empirical Mode Decomposition and Information Geometry in Complex Electromagnetic Environment

Yonghua Wang | Shunchao Zhang | ... | Nan Li
  • Special Issue
  • - Volume 2019
  • - Article ID 7465461
  • - Research Article

Jiles-Atherton Based Hysteresis Identification of Shape Memory Alloy-Actuating Compliant Mechanism via Modified Particle Swarm Optimization Algorithm

Le Chen | Ying Feng | ... | Hui Jiang
  • Special Issue
  • - Volume 2019
  • - Article ID 7438710
  • - Research Article

IHDETBO: A Novel Optimization Method of Multi-Batch Subtasks Parallel-Hybrid Execution Cloud Service Composition for Cloud Manufacturing

Li-Nan Zhu | Peng-Hang Li | Xiao-Long Zhou
  • Special Issue
  • - Volume 2019
  • - Article ID 5262859
  • - Research Article

Learning Force-Relevant Skills from Human Demonstration

Xiao Gao | Jie Ling | ... | Miao Li
  • Special Issue
  • - Volume 2019
  • - Article ID 8030374
  • - Research Article

Adaptive Path Following and Locomotion Optimization of Snake-Like Robot Controlled by the Central Pattern Generator

Zhengcai Cao | Dong Zhang | ... | Jinguo Liu
  • Special Issue
  • - Volume 2019
  • - Article ID 2152014
  • - Research Article

Delay-Range-Dependent Robust Constrained Model Predictive Control for Industrial Processes with Uncertainties and Unknown Disturbances

Huiyuan Shi | Ping Li | ... | Jiangtao Cao
  • Special Issue
  • - Volume 2019
  • - Article ID 5296123
  • - Research Article

Eigen Solution of Neural Networks and Its Application in Prediction and Analysis of Controller Parameters of Grinding Robot in Complex Environments

Shixi Tang | Jinan Gu | ... | Zhengyang Shang
Complexity
 Journal metrics
Acceptance rate37%
Submission to final decision67 days
Acceptance to publication39 days
CiteScore3.200
Impact Factor2.462
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