Full Text:   <258>

Suppl. Mater.: 

CLC number: 

On-line Access: 2019-01-30

Received: 0000-00-00

Revision Accepted: 0000-00-00

Crosschecked: 0000-00-00

Cited: 0

Clicked: 507

Citations:  Bibtex RefMan EndNote GB/T7714

-   Go to

Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2019 Vol.20 No.1 P.1-3

10.1631/FITEE.1910000


Complex system and intelligent control: theories and applications


Author(s):  Jie Chen, Ben M. Chen, Jian Sun

Affiliation(s):  School of Automation, Beijing Institute of Technology, Beijing 100081, China; more

Corresponding email(s):   chenjie@bit.edu.cn

Key Words: 


Share this article to: More |Next Article >>>

Jie Chen, Ben M. Chen, Jian Sun. Complex system and intelligent control: theories and applications[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(1): 1-3.

@article{title="Complex system and intelligent control: theories and applications",
author="Jie Chen, Ben M. Chen, Jian Sun",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="20",
number="1",
pages="1-3",
year="2019",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1910000"
}

%0 Journal Article
%T Complex system and intelligent control: theories and applications
%A Jie Chen
%A Ben M. Chen
%A Jian Sun
%J Frontiers of Information Technology & Electronic Engineering
%V 20
%N 1
%P 1-3
%@ 1869-1951
%D 2019
%I Zhejiang University Press & Springer

TY - JOUR
T1 - Complex system and intelligent control: theories and applications
A1 - Jie Chen
A1 - Ben M. Chen
A1 - Jian Sun
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 20
IS - 1
SP - 1
EP - 3
%@ 1869-1951
Y1 - 2019
PB - Zhejiang University Press & Springer
ER -


Abstract: 
Complex systems are the systems that consist of a great many diverse and autonomous but interacting and interdependent components whose aggregate behaviors are nonlinear. As phased by Aristotle, “the whole is more than the sum of its parts;” properties of complex systems are not a simple summation of their individual parts.
Complex systems are widespread. Typical examples of complex systems can be found in the human brain, flocking formation of migrating birds, power grid, transportation systems, autonomous ve-hicles, social networks, and communication net-works.
Complex systems have some distinct properties, such as highly nonlinear dynamics, emergence, ad-aptation, and self-organization, which are difficult to model precisely. Such properties lead to difficulties in understanding the behaviors of complex systems, to model them accurately, to control them, and to make them work in a specific way we desire.
There is no generally agreed definition of intel-ligent control. Generally speaking, intelligent control is a class of control methods that use artificial intel-ligence techniques, such as fuzzy logic, neural net-works, evolutionary computation, machine learning, and swarming intelligence. Intelligent control tries to borrow ideas from the sciences of physics, mathe-matics, biology, neuroscience, and others to develop a control system to manage a complex process in an uncertain environment. Intelligent control is a kind of interdisciplinary new technology, which integrates the knowledges of control theory, computer science, artificial intelligence, information theory, and other areas. Intelligent control has been shown to be effec-tive in controlling complex systems where traditional control methods can hardly perform well.
In this context, the Chinese Academy of Engi-neering (CAE) organized a special issue on complex system and intelligent control in Frontiers of Infor-mation Technology and Electronic Engineering. This special issue aims to promote research on complex systems and intelligent control and reflect the most recent advances, with emphasis on both theories and applications. After rigorous review process, 11 papers by researchers worldwide have been selected for this special issue, including one survey paper and 10 research papers.
Electric power grid as a typical example of complex systems has brought a great change in our daily lives. An accurate, fast, and robust power sys-tem state estimation is undoubtedly significant. Gang WANG et al. gave a comprehensive review on some of the recent advances in power system state estima-tion with an emphasis on the solvers that can effi-ciently obtain optimal or near-optimal solutions to nonconvex state estimation tasks. Some directions for future research were also discussed.
Motion coverage is an important real-world ap-plication for mobile robots. To deal with the multi- robot coverage motion planning problem, Guan-qiang GAO and Bin XIN proposed an auction-based spanning tree coverage (A-STC) algorithm. Compared with existing methods, this algorithm is effective, time-efficient, and complete, especially in large complex configuration spaces.
A snake robot is a biomorphic robot to imitate snake’s morphology. To make a snake robot as agile as a biological snake, locomotion generation and body motion control are two important issues. Wenjuan OUYANG et al. proposed a biomimetic control approach for steering a snake robot. The proposed method includes an artificial central pattern generator, a cerebellar model articulation controller, and a proportional-derivative controller. Their simulations and experiments demonstrated good performance and adaptability of the method.
Ning-shi YAO et al. presented an autonomous robotic blimp equipped with only one monocular camera, named Georgia Tech Miniature Autonomous Blimp (GT-MAB). It was designed to support human robot interaction experiments in an indoor space. The blimp is capable of effectively detecting the face of a human subject, following the human, and recognizing hand gestures by employing a deep neural network based algorithm. Their experimental results demon-strated that GT-MAB has reliable human-detection and human-following capabilities.
Execution control is a critical task of robot ar-chitecture design, and has important influence on the quality of the final system. Martin MOLINA et al. presented a general method for execution control. The proposed method was integrated in the Aerostack open-source framework. Their experiments demon-strated the validity, feasibility, and effectiveness of the proposed method.
In recent years, multi-agent systems have re-ceived much attention since their wide applications in mobile sensor networks, formation of unmanned flight vehicles, smart grids, etc. Formation control is an important topic in cooperative control for multi- agent systems. Mao-peng RAN et al. considered the time-varying formation tracking problem for multi- agent systems subject to unknown nonlinear dynamics and external disturbances. An extended state observer (ESO) was designed to estimate the total uncertainty of the system. An ESO-based time-varying formation tracking protocol was proposed. Effectiveness of the theoretical results was demonstrated by application to the target enclosing problem of a group of unmanned aerial vehicles (UAVs). Mao-bin LU and Lu LIU studied the leader-following consensus problem of a class of heterogeneous second-order nonlinear multi-agent systems subject to disturbances. A class of distributed control laws that depend on the relative state of the system were proposed to solve the prob-lem.
In recent years, UAVs have been widely applied in many fields, such as reconnaissance, search and rescue, surveillance, environment monitoring, large- accident investigation, parcel delivery, and agricul-ture service. Among all the UAVs, the quadrotor platform is the most popular one. Control and navi-gation of quadrotor UAV has received much attention. Yu-jiang ZHONG et al. presented a reliable active fault-tolerant tracking control method for a quadrotor UAV with model uncertainties and actuator faults. A radial basis function neural network was introduced to estimate the model uncertainties online, modify the reference model adaptively, and incorporate it into the model reference adaptive control scheme. To deal with actuator faults, a fault detection and diagnosis estimator and a fault compensation term were intro-duced into the control law. Shu-peng LAI et al. pro-posed a computationally efficient safe flying corridor navigation method for a quadrotor UAV. This method can generate a jerk-limited trajectory within a safe corridor. Unlike the existing methods, the proposed method can generate a smooth non-stop trajectory with safety guarantee but does not require the vehicle stop at each intersected point of the connected boxes.
A flywheel suspended on active magnetic bear-ings as a kind of complex system has been found to have many applications in energy storage devices. However, the controller design problem for a flywheel system is still challenging. Xujun LYU et al. applied the characteristic model based all-coefficient adaptive control method to active magnetic bearings suspended flywheel systems. An extensive simulation showed that the characteristic model based all-coefficient adaptive control method has considerable robustness with respect to plant uncertainties, external disturbances, and time delay.
Ze-zhi TANG et al. investigated the disturbance rejection problem of active magnetic bearing systems. A disturbance observer based iterative learning con-trol strategy that combines the extended state observer with a classic iterative learning control law was proposed. Their simulation and comparison con-firmed that the proposed method can yield good tracking performance.
The papers included in this special issue cover a broad spectrum of current research topics on complex systems and intelligent control, including formation control of complex multi-agent systems, control and navigation of a quadrotor UAV, robust control of robots, interaction between human and robot, control of systems with model uncertainties and disturbances. We hope that this special issue will benefit the re-searchers in these fields and foster research on com-plex systems and intelligent control.
This special issue would not be possible without the support of many people, including the authors and reviewers. We are indebted to the editorial staff of the journal for their enormous assistances, and to the Editors-in-Chief, Profs. Yun-he PAN and Xi-cheng LU, for this great opportunity.

复杂系统智能控制:理论与应用

概要: 复杂系统是指由多个不同的、自治的且相互作用的子系统组成的系统。正如亚里士多德所说,“整体大于部分之和”,复杂系统的性质并非其子系统性质的简单加和。复杂系统概念非常广泛,包括人脑、鸟类编队飞行、电网、交通系统、社交网络、通讯网络,等等。复杂系统具有高度非线性、涌现性、自适应性、自组织等特征,这些特征使得复杂系统难于精确建模,难于理解,难于控制。
对于智能控制,目前学术界还没有公认的定义。一般来讲,智能控制是指一类应用模糊逻辑、神经网络、进化计算、机器学习、群体智能等人工智能技术的控制方法。智能控制往往从物理、数学、生物学、神经学等领域汲取思想,实现对不确定环境中复杂过程的有效控制。智能控制是一种多学科交叉的前沿技术,综合了控制理论、计算机科学、人工智能、信息论等多个领域的知识。智能控制在传统控制方法不能胜任的领域往往可以取得良好控制效果。
为此,中国工程院院刊《信息与电子工程前沿(英文)》组织了“复杂系统与智能控制”专刊。本期专刊目的在于进一步促进该领域研究,展示该领域最新研究进展,特别是在基础理论与应用方面的成果。经过严格同行评议,精心挑选了11篇来自世界各地的论文,包括1篇综述,10篇研究论文。
电网作为一种典型复杂系统,给人民日常生活带来巨大变革,对电网进行精确、快速且鲁棒的状态估计无疑具有重要意义。王钢等全面深入地综述了电网状态估计的最新研究进展,着重介绍了非凸状态估计问题的最优解或近似最优解求取方法,并展望了未来的研究方向。
区域覆盖是移动机器人非常重要的应用之一。为解决移动机器人区域覆盖的路径规划问题,高冠强与辛斌提出一种基于拍卖机制的生成树覆盖算法。与现有方法相比,对布局复杂的大规模区域,该方法更加有效且用时更短。
蛇形机器人是一种模仿生物蛇运动形态的仿生机器人。为使蛇形机器人像生物蛇一样敏捷,蛇形机器人的步态生成与运动控制是两个需要考虑的重要因素。针对蛇形机器人,欧阳文娟等提出一种仿生控制算法。该算法包括中枢模式发生器、小脑模型神经网络控制器和比例微分(PD)控制器。仿真和实验结果表明该方法具有良好适应性和控制效果。
姚宁诗等展示了一款由佐治亚理工学院研发的气球机器人。该气球机器人被用于支持室内人机交互等方面的实验研究工作。采取基于深度神经网络的算法,可以有效检测人脸,跟踪人的运动并识别人的手势。实验结果表明,该气球机器人具有可靠的检测与跟踪能力。
执行控制是机器人结构设计中的关键环节,对机器人系统最终质量具有重要影响。Martin Molina等提出一种通用执行控制方法。实验结果验证了该方法的正确性、可行性与有效性。
近年来,多智能体系统受到国内外学者广泛关注。编队控制是多智能体协同控制中非常重要的研究方向。冉茂鹏等考虑了具有未知非线性动态与外界扰动的多智能体系统时变队形跟踪控制问题。设计了扩张状态观测器估计系统的总扰动,并提出一种基于扩张状态观测器的队形跟踪协议。将所提算法应用于多无人机目标合围问题,验证了所提理论方法的有效性。吕茂斌和刘璐研究了一类二阶异构非线性多智能体系统的领航—跟随问题,提出一类仅依赖于多智能体相对状态的分布式算法。
近年来,无人机已广泛应用于侦察、搜索与救援、监控、环境监测、包裹快递、农业服务等领域。在所有无人机中,四旋翼无人机最为流行。四旋翼无人机的导航与控制问题受到广泛关注。仲于江等针对四旋翼无人机提出一种可靠的容错跟踪控制方法。该方法应用径向基神经网络算法对模型的不确定性进行精确在线辨识,且自适应地修正参考模型,并在控制率中引入故障检测与诊断滤波器以及故障补偿项,应对执行器故障。赖叔朋等提出一种计算简便的安全飞行通道导航方法,该方法可以产生平滑且不停顿的安全飞行轨迹。
作为一类复杂系统,磁悬浮飞轮在储能装置中得到广泛应用。然而,磁悬浮飞轮的控制器设计问题非常具有挑战性。吕许俊等应用基于特征建模的全系数自适应控制方法对磁悬浮飞轮进行有效控制。仿真结果表明该方法对于模型不确定性、外界扰动和延时具有很强鲁棒性。
唐泽至等研究了主动磁悬浮轴承系统的干扰抑制问题,提出一种具有扰动观测器的迭代学习控制策略,该策略将传统迭代学习方法与扩张状态观测器有机结合。仿真结果表明该策略可以取得良好跟踪效果。
本期专刊涵盖了复杂系统与智能控制领域的多个研究方向,包括多智能体系统编队控制、四旋翼无人机导航与控制、机器人鲁棒控制、人机交互、具有外界扰动与模型不确定性系统的控制等前沿方向。我们希望本期专刊对该领域研究人员有所启发,能够促进该领域研究进一步深入。
本期专刊出版过程中,得到很多人支持,在此深表感谢。特别要感谢编辑部工作人员的大力帮助以及潘云鹤、卢锡城两位主编给予我们这次难得机会。

关键词:

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - Journal of Zhejiang University-SCIENCE