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Parallel system Based Quantitative Assessment and Self-evolution for Artificial Intelligence of Active Power Corrective control

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CSEE Journal of Power and Energy systems 2024年第1期10卷 13-28页

作者： Tianyun Zhang Jun Zhang Feiyue Wang Peidong Xu Tianlu Gao Haoran Zhang Ruiqi Si School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072HubeiChina State Key Laboratory for Management and Control of Complex System Institute of AutomationChinese Academy of SciencesBeijing 100190China

In artificial intelligence(AI)based-complex power system management and control technology,one of the urgent tasks is to evaluate AI intelligence and invent a way of autonomous intelligence ***,there is,currently,nearly no standard technical framework for objective and quantitative intelligence *** this article,based on a parallel system framework,a method is established to objectively and quantitatively assess the intelligence level of an AI agent for active power corrective control of modern power systems,by resorting to human intelligence evaluation *** this basis,this article puts forward an AI self-evolution method based on intelligence assessment through embedding a quantitative intelligence assessment method into automated reinforcement learning(AutoRL)systems.A parallel system based quantitative assessment and self-evolution(PLASE)system for power grid corrective control AI is thereby constructed,taking Bayesian Optimization as the measure of AI evolution to fulfill autonomous evolution of AI under guidance of their intelligence assessment *** results exemplified in the power grid corrective control AI agent show the PLASE system can reliably and quantitatively assess the intelligence level of the power grid corrective control agent,and it could promote evolution of the power grid corrective control agent under guidance of intelligence assessment results,effectively,as well as intuitively improving its intelligence level through selfevolution.

关键词： AI quantitative intelligence assessment and self-evolution automated reinforcement learning Bayesian optimization corrective control parallel system

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PLS-CCA Heterogeneous Features Fusion-based Low-resolution Human Detection Method for Outdoor Video Surveillance

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International Journal of Automation and computing 2017年第2期14卷 136-146页

作者： Hong-Kai Chen Xiao-Guang Zhao Shi-Ying Sun Min Tan State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

In this paper, we focus on low-resolution human detection and propose a partial least squares-canonical correlation analysis （PLS-CCA） for outdoor video surveillance. The analysis relies on heterogeneous features fusion-based human detection method. The proposed method can not only explore the relation between two individual heterogeneous features as much as possible, but also can robustly describe the visual appearance of humans with complementary information. Compared with some other methods, the experimental results show that the proposed method is effective and has a high accuracy, precision, recall rate and area under curve （AUC） value at the same time, and offers a discriminative and stable recognition performance.

关键词： Low-resolution human detection partial least squares canonical correlation analysis heterogeneous features outdoorvideo surveillance.

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An Adaptive RBF Neural Network control Method for a Class of Nonlinear systems

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IEEE/CAA Journal of Automatica Sinica 2018年第2期5卷 457-462页

作者： Hongjun Yang Jinkun Liu State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Automation Science and Electrical Engineering Beihang University Beijing 100083 China

This paper focuses on designing an adaptive radial basis function neural network(RBFNN) control method for a class of nonlinear systems with unknown parameters and bounded disturbances. The problems raised by the unknown functions and external disturbances in the nonlinear system are overcome by RBFNN, combined with the single parameter direct adaptive control method. The novel adaptive control method is designed to reduce the amount of computations *** uniform ultimate boundedness of the closed-loop system is guaranteed by the proposed controller. A coupled motor drives(CMD) system, which satisfies the structure of nonlinear system,is taken for simulation to confirm the effectiveness of the *** show that the developed adaptive controller has favorable performance on tracking desired signal and verify the stability of the closed-loop system.

关键词： Index TermsbAdaptive control neural network (NN) nonlin-ear system radial basis function.

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First attempt of barrier functions for Caputo's fractional-order nonlinear dynamical systems

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Science China(Information Sciences) 2023年第7期66卷 313-314页

作者： Zheren ZHU Pengfei HUANG Xinmin ZHANG Yi CHAI Zhihuan SONG College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology School of Automation Chongqing University Key Laboratory of Complex System Safety and Control(Chongqing University) Ministry of Education

Dear editor, In the past two decades, scholars have begun to use system dynamical models and state motions to study the safety of a system to realize the analysis, diagnosis, and control of system safety. This safety ...

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A survey on fabrication,control,and hydrodynamic function of biomimetic robotic fish

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Science China(Technological Sciences) 2017年第9期60卷 1365-1380页

作者： YU JunZhi WEN Li REN ZiYu State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Mechanical Engineering and Automation Beihang University

Understanding and replicating the locomotion principles offish are fundamental in the development of artificial fishlike robotic systems,termed robotic *** paper has two objectives:(1) to review biological clues on biomechanics and hydrodynamic flow control offish swimming and(2) to summarize design and control methods for efficient and stable swimming in robotic *** review of state-of-the-art research and future-oriented new directions indicates that fish-inspired biology and engineering interact in mutually beneficial *** strong interaction offers an important insight into the design and control of novel fish-inspired robots that addresses the challenge of environmental uncertainty and competing objectives;in addition,it also facilitates refinement of biological knowledge and robotic strategies for effective and efficient swimming.

关键词： fish swimming robots robotic fish hydrodynamics motion control

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Improving performance of robots using human-inspired approaches: a survey

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Science China(Information Sciences) 2022年第12期65卷 5-35页

作者： Hong QIAO Shanlin ZHONG Ziyu CHEN Hongze WANG State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences School of Artifcial Intelligence University of Chinese Academy of Sciences CAS Center for Excellence in Brain Science and Intelligence Technology

Realizing high performance of ordinary robots is one of the core problems in robotic research. Improving the performance of ordinary robots usually relies on the collaborative development of multiple research fields, resulting in high costs and difficulty to complete some high-precision tasks. As a comparison,humans can realize extraordinary overall performance under the condition of limited computational-energy consumption and low absolute precision in sensing and controlling each body unit. Therefore, developing human-inspired robotic systems and algorithms is a promising avenue to improve the performance of robotic systems. In this review, the cutting-edge research work on human-inspired intelligent robots in decisionmaking, cognition, motion control, and system design is summarized from behavior-and neural-inspired aspects. This review aims to provide a significant insight into human-inspired intelligent robots, which may be beneficial for promoting the integration of neuroscience, machinery, and control, so as to develop a new generation of robotic systems.

关键词： human-inspired intelligent robots brain-inspired intelligence decision making visual cognition musculoskeletal robots

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Speed and Accuracy Tradeoff for LiDAR Data Based Road Boundary Detection

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IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1210-1220页

作者： Guojun Wang Jian Wu Rui He Bin Tian State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the Qingdao Academy of Intelligent Industries ShandongChina

Road boundary detection is essential for autonomous vehicle localization and decision-making,especially under GPS signal loss and lane *** road boundary detection in structural environments,obstacle occlusions and large road curvature are two significant ***,an effective and fast solution for these problems has remained *** solve these problems,a speed and accuracy tradeoff method for LiDAR-based road boundary detection in structured environments is *** proposed method consists of three main stages:1)a multi-feature based method is applied to extract feature points;2)a road-segmentation-line-based method is proposed for classifying left and right feature points;3)an iterative Gaussian Process Regression(GPR)is employed for filtering out false points and extracting boundary *** demonstrate the effectiveness of the proposed method,KITTI datasets is used for comprehensive experiments,and the performance of our approach is tested under different road *** experiments show the roadsegmentation-line-based method can classify left,and right feature points on structured curved roads,and the proposed iterative Gaussian Process Regression can extract road boundary points on varied road shapes and traffic ***,the proposed road boundary detection method can achieve real-time performance with an average of 70.5 ms per frame.

关键词： 3D-LiDAR autonomous vehicle object detection point cloud road boundary

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Development and control of Underwater Gliding Robots:A Review

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1543-1560页

作者： Jian Wang Zhengxing Wu Huijie Dong Min Tan Junzhi Yu the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China the State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering ScienceBIC-ESATCollege of EngineeringPeking UniversityBeijing 100871China

As one of the most effective vehicles for ocean development and exploration,underwater gliding robots(UGRs)have the unique characteristics of low energy consumption and strong ***,by borrowing the motion principles of current underwater robots,a variety of novel UGRs have emerged with improving their maneuverability,concealment,and environmental friendliness,which significantly broadens the ocean *** this paper,we provide a comprehensive review of underwater gliding robots,including prototype design and their key *** the perspective of motion characteristics,we categorize the underwater gliding robots in terms of traditional underwater gliders(UGs),hybrid-driven UGs,bio-inspired UGs,thermal UGs,and ***,their buoyancy driven system,dynamic and energy model,and motion control are concluded with detailed ***,we have discussed the current critical issues and future *** review offers valuable insight into the development of next-generation underwater robots well-suited for various oceanic applications,and aims to gain more attention of researchers and engineers to this growing field.

关键词： Buoyancy driven motion control oceanic applications system development underwater gliding robots

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Distributed disturbance-observer-based vibration control for a flexible-link manipulator with output constraints

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Science China(Technological Sciences) 2018年第10期61卷 1528-1536页

作者： YANG HongJun LIU JinKun HE Wei State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences School of Automation Science and Electrical Engineering Beihang University School of Automation and Electrical Engineering University of Science and Technology Beijing

The issue of output constraints is studied for a flexible-link manipulator in the presence of unknown spatially distributed disturbances. The manipulator can be taken as an Euler-Bernoulli beam and its dynamic is expressed by partial differential equations. On account of the uncertainty of disturbances, we present a disturbance observer to estimate infinite dimensional disturbances on the beam. The observer is proven exponentially stable. Considering the problem of output constraints in the practical engineering, we propose a novel distributed vibration controller based on the disturbance observer to fulfill the position regulation of the joint angle and suppress elastic deflections on the flexible link, while confining the regulating errors of output in a suitable scope that we can assign. The closed-loop system is demonstrated exponentially stable based on an integral-barrier Lyapunov function. Simulations validate the effectiveness of the design scheme.

关键词： flexible manipulator distributed vibration control disturbance observer partial differential equation output constraint distributed parameter system

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Policy iteration based Q-learning for linear nonzero-sum quadratic differential games

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Science China(Information Sciences) 2019年第5期62卷 195-213页

作者： Xinxing LI Zhihong PENG Li LIANG Wenzhong ZHA School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System Information Science Academy China Electronics Technology Group Corporation

In this paper, a policy iteration-based Q-learning algorithm is proposed to solve infinite horizon linear nonzero-sum quadratic differential games with completely unknown dynamics. The Q-learning algorithm, which employs off-policy reinforcement learning(RL), can learn the Nash equilibrium and the corresponding value functions online, using the data sets generated by behavior policies. First, we prove equivalence between the proposed off-policy Q-learning algorithm and an offline PI algorithm by selecting specific initially admissible polices that can be learned online. Then, the convergence of the off-policy Qlearning algorithm is proved under a mild rank condition that can be easily met by injecting appropriate probing noises into behavior policies. The generated data sets can be repeatedly used during the learning process, which is computationally effective. The simulation results demonstrate the effectiveness of the proposed Q-learning algorithm.

关键词： adaptive dynamic programming ADP Q-learning reinforcement learning RL linear nonzerosum quadratic differential games policy iteration PI off-policy

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