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 2018
  • - Article ID 4329053
  • - Research Article

Performance Analysis of Switched Control Systems Under Common-source Digital Upsets Modeled by MDHMM

Rui Wang | Yanxiao Li | ... | Yigang Sun
  • Special Issue
  • - Volume 2018
  • - Article ID 4975187
  • - Research Article

Consensus Path-following Control of Multiple Underactuated Unmanned Underwater Vehicles

Yintao Wang | Yao Yao
  • Special Issue
  • - Volume 2018
  • - Article ID 8420294
  • - Research Article

A New Dynamic Path Planning Approach for Unmanned Aerial Vehicles

Chenxi Huang | Yisha Lan | ... | Yonghong Peng
  • Special Issue
  • - Volume 2018
  • - Article ID 2024184
  • - Research Article

Optimization of Heterogeneous Container Loading Problem with Adaptive Genetic Algorithm

Xianbo Xiang | Caoyang Yu | ... | Stuart X. Zhu
  • Special Issue
  • - Volume 2018
  • - Article ID 2763210
  • - Research Article

Iterative Learning Control for Linear Discrete-Time Systems with Randomly Variable Input Trail Length

Yun-Shan Wei | Qing-Yuan Xu
  • Special Issue
  • - Volume 2018
  • - Article ID 3563846
  • - Research Article

Collision-Free Path-Planning for Six-DOF Serial Harvesting Robot Based on Energy Optimal and Artificial Potential Field

Lufeng Luo | Hanjin Wen | ... | Chenglin Wang
  • Special Issue
  • - Volume 2018
  • - Article ID 4358747
  • - Research Article

Robot Motion Planning Method Based on Incremental High-Dimensional Mixture Probabilistic Model

Fusheng Zha | Yizhou Liu | ... | Wei Guo
  • Special Issue
  • - Volume 2018
  • - Article ID 7131562
  • - Research Article

Adaptive Neural Tracking Control of Robotic Manipulators with Guaranteed NN Weight Convergence

Jun Yang | Jing Na | ... | Chao Zhang
  • Special Issue
  • - Volume 2018
  • - Article ID 4573631
  • - Research Article

Intelligent Controllers for Multirobot Competitive and Dynamic Tracking

Mei Liu | Shuai Li | ... | Zhiguan Huang
  • Special Issue
  • - Volume 2018
  • - Article ID 9801240
  • - Research Article

Fuzzy Adaptive Compensation Control for Uncertain Building Structural Systems by Sliding-Mode Technology

Houyao Zhu | Zicong Chen | ... | Huaqi Zhao
Complexity
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Acceptance rate11%
Submission to final decision120 days
Acceptance to publication21 days
CiteScore4.400
Journal Citation Indicator0.720
Impact Factor2.3
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