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Adaptive output consensus for heterogeneous nonlinear multi-agent systems with multi-type input constraints under switching-directed topologies

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Control Theory and Technology 2021年第2期19卷 260-272页

作者： Wei Zhang zhaoxu yu Shugang Li Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and TechnologyShanghai200237China Department of Information Management Shanghai UniversityShanghai200444China

This study concentrates on solving the output consensus problem for a class of heterogeneous uncertain nonstrict-feedback nonlinear multi-agent systems under switching-directed communication topologies,in which all followers are subjected to multi-type input constraints such as unknown asymmetric saturation,unknown dead-zone and their integration.A unified representation is presented to overcome the difficulties originating from multi-agent input ***,the uncertain system functions in a non-lower triangular form and the interaction terms among agents are dealt with by exploiting the fuzzy logic systems and their special ***,by introducing a nonlinear filter to alleviate the problem of“explosion of complexity”during the backstepping design,a distributed common adaptive control protocol is proposed to ensure that the synchronization errors converge to a small neighborhood of the origin despite the existence of multiple input constraints and arbitrary switching communication *** stability analysis and simulation results are conducted to show the effectiveness and performance of the proposed control methodology.

关键词： Nonlinear multi-agent system Output consensus Fuzzy logic system Input constraint Switching topology

Adaptive neural control for pure-feedback nonlinear time-delay systems with unknown dead-zone: a Lyapunov-Razumikhin method

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控制理论与应用（英文版） 2013年第1期11卷 18-26页

作者： zhaoxu yu Jianxu LUO Ji LIU Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

This paper addresses the problem of adaptive neural control for a class of uncertain pure-feedback nonlinear systems with multiple unknown state time-varying delays and unknown dead-zone. Based on a novel combination of the Razumikhin functional method, the backstepping technique and the neural network parameterization, an adaptive neural control scheme is developed for such systems. All closed-loop signals are shown to be semiglobally uniformly ultimately bounded, and the tracking error remains in a small neighborhood of the origin. Finally, a simulation example is given to demonstrate the effectiveness of the proposed control schemes.

关键词： Pure-feedback nonlinear systems Adaptive neural control Razumikhin functional Time-delay Deadzone

Adaptive Neural Output Feedback Control for Nonstrict-Feedback Nonlinear Systems with Quantized Input 36

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Adaptive Neural Output Feedback Control for Nonstrict-Feedba...

第36届中国控制会议

作者： Yan Dong zhaoxu yu Fangfei Li Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology Department of Mathematics East China University of Science and Technology

ISBN: (纸本)9781538629185

This paper focuses on the problem of adaptive output feedback tracking control for a class of nonstrict-feedback nonlinear systems with unknown control coefficients and quantized input. The difficulty from the unknown control direction is solved by using the linear state transformation and the Nussbaum gain function（NGF） approach. Based on the combination of input-driven observer, backstepping technique, neural network（NN） parametrization and variable separation method, a novel adaptive output feedback quantized control scheme involving only one adaptive parameter is developed for such systems. The designed quantized controller ensures that all signals of closed-loop systems are semi-globally uniformly ultimately bounded（SGUUB）, and the tracking error converges to an adjustable neighborhood of the origin. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed control design.

关键词： Nonstrict-feedback systems quantized input signal output feedback adaptive control unknown control direction

Observer-Based Adaptive Output-Feedback Quantized Control for Switched Stochastic Nonlinear Time-Delay Systems

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Observer-Based Adaptive Output-Feedback Quantized Control fo...

第37届中国控制会议

作者： Yekai Yang zhaoxu yu Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education Department of AutomationEast China University of Science and Technology

This paper is concerned with the adaptive output-feedback tracking control problem for switched stochastic nonlinear time-delay systems under arbitrary switching in the presence of input and output *** common Lyapunov-Krasoviskii functional approach,neural network（NN） approximation-based method and backstepping technique,a novel observer-based adaptive output-feedback controller is presented to guarantee that all signals of closed-loop systems are4-moment（or 2-moment） semi-globally uniformly ultimately bounded（SGUUB） and the tracking error can converge to a small neighborhood of the ***,a simulation example is given to verify the effectiveness of the proposed methodology.

关键词： Switched stochastic systems Adaptive quantized control Output-feedback Time-delay Lyapunov-Krasoviskii functional

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污水处理过程的多目标优化

西安交通大学学报 2017年第3期51卷 129-135页

作者：罗健旭彭培培徐颖余昭旭华东理工大学化工过程先进控制和优化技术教育部重点实验室上海200237

为了在保证污水处理厂出水质量达标、控制日常运营成本的同时尽量减少温室气体(GHG)的排放,将温室气体的排放纳入了污水处理的性能评价范畴,并与出水质量(EQI)、操作成本指数(OCI)等传统性能评价指标构成了污水处理过程的多目标优化问... 详细信息

为了在保证污水处理厂出水质量达标、控制日常运营成本的同时尽量减少温室气体(GHG)的排放,将温室气体的排放纳入了污水处理的性能评价范畴,并与出水质量(EQI)、操作成本指数(OCI)等传统性能评价指标构成了污水处理过程的多目标优化问题。为研究此性能指标的多目标优化问题,构建了简化的污水处理仿真平台BSM2-e,此平台包括初沉池、活性污泥反应器、二次澄清池和浓缩单元。针对多目标优化问题的求解,采用多目标进化算法NSGA-II对该算法的精英选择策略做了改进,算法在拥挤距离选择的基础上增加了筛选步骤,以改善算法的分布性,将该算法应用于BSM2-e多目标优化问题,取得了较好的仿真结果。优化结果表明,GHG排放指标与EQI有冲突,提高出水质量可增加温室气体的排放,而GHG排放指标与OCI无冲突,在不增加操作成本的情况下可有效降低温室气体的排放。

关键词：多目标优化温室气体污水处理过程 NSGA-II

Adaptive Neural Control for a Class of Stochastic Nonlinear Pure-feedback Systems with Unknown Control Direction

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Adaptive Neural Control for a Class of Stochastic Nonlinear ...

第三十届中国控制会议

作者： yu zhaoxu,LUO Jianxu,DU Hongbin Department of Automation,East China University of Science and Technology,Shanghai 200237,P.R.China

＜正＞This paper addresses a class of uncertain stochastic nonlinear pure-feedback systems with unknown control direction. With using the decoupled backstepping technique,adaptive neural control schemes are designed to solve the stabilization problem of such *** analysis is presented to guarantee that all the error variables are semi-globally ultimately bounded with desired probability in a compact *** effectiveness of the proposed design is verified by simulation results.

关键词： Adaptive Control Neural Networks(NN) Backstepping Nussbaum Gain Functions(NGFs) Stochastic PureFeedback Systems

On the Stability of a New Congestion Control Algorithm for the Internet

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On the Stability of a New Congestion Control Algorithm for t...

第二十三届中国控制会议

作者： yu zhaoxu Wu Tihua (Department of Automation Shanghai Jiaotong University, Shanghai 200030 Institute of Automation Academic of Science in Hebei Province, Shijiazhuang 050081)

＜正＞ This paper analyzes a decentralized network congestion control algorithm which has dynamic adaptations at both user ends and link ends. We derive sufficient conditions for local stability of this algorithm in a general topology network with heterogeneous round-trip delays. Moreover, we show that this new algorithm can be implemented with minimal changes to TCP and RED. Finally a simulation result justifies our theoretic results by ns2.0.

关键词： Congestion Control Prime-dual Algorithm Generalized Nyquist Criterion Stability Round-trip Delays.

网络攻击下非线性CPSs的事件触发自适应控制

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华东理工大学学报（自然科学版） 2024年第3期50卷 411-417页

作者：陈泽彬余昭旭李树刚华东理工大学能源化工过程智能制造教育部重点实验室上海200237 上海大学信息管理系上海200444

本文研究了网络攻击下一类控制方向未知的非线性信息物理系统(Cyber-Physical Systems,CPSs)的自适应输出反馈控制问题。通过引入合适的线性状态变换,将原系统转化为便于输出反馈控制设计的新系统。采用Nussbaum增益函数方法克服未知的... 详细信息

本文研究了网络攻击下一类控制方向未知的非线性信息物理系统(Cyber-Physical Systems,CPSs)的自适应输出反馈控制问题。通过引入合适的线性状态变换,将原系统转化为便于输出反馈控制设计的新系统。采用Nussbaum增益函数方法克服未知的控制系数和网络攻击所带来的设计困难。基于观测器状态和受攻击的测量输出信号,采用神经网络逼近方法,提出了一种新的事件触发自适应输出反馈控制策略。该控制策略不但大大降低数据的传输量,而且保证闭环系统是半全局一致最终有界的。另外,采用基于非线性滤波器的动态面控制方法可以克服反步法设计中惯有的“复杂性爆炸”问题。最后,通过机械手系统验证所提出控制方法的有效性和实用性。

关键词：非线性CPSs 网络攻击自适应控制动态面控制事件触发

复方麝香注射液联合依达拉奉对颅脑外伤患者凝血和神经功能的影响

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中国药房 2017年第20期28卷 2827-2830页

作者：于朝旭武焕颖孙实安张海军承德市中心医院神经外科河北承德067000

目的:探讨复方麝香注射液联合依达拉奉对颅脑外伤患者凝血功能、神经功能的影响及安全性。方法:选取我院2015年4月-2016年4月收治的颅脑外伤患者84例,按照随机数字表法分为观察组与对照组,各42例。对照组患者给予依达拉奉注射液30 mg加... 详细信息

目的:探讨复方麝香注射液联合依达拉奉对颅脑外伤患者凝血功能、神经功能的影响及安全性。方法:选取我院2015年4月-2016年4月收治的颅脑外伤患者84例,按照随机数字表法分为观察组与对照组,各42例。对照组患者给予依达拉奉注射液30 mg加入0.9%氯化钠注射液100 m L中,bid,ivgtt;观察组在对照组基础上加用复方麝香注射液20 m L加入0.9%氯化钠注射液250 m L中,qd,ivgtt。两组患者均治疗4周。比较两组患者治疗前后神经功能缺损程度(NIHSS)评分、格拉斯昏迷分级(GCS)评分、血清神经元特异性烯醇化酶(NSE)水平、C反应蛋白(CRP)水平、凝血酶原时间(PT)、活化部分凝血活酶时间(APTT)、D-二聚体水平、格拉斯预后分级(GOS)评分及不良反应发生情况。结果:治疗后,两组患者NIHSS评分均较治疗前显著降低,且观察组显著低于对照组,差异有统计学意义(P<0.05);两组患者GCS评分均较治疗前显著增高,且观察组显著高于对照组,差异有统计学意义(P<0.05);两组患者血清NSE、CRP、PT、APTT和D-二聚体水平均较治疗前显著降低,且观察组显著低于对照组,差异有统计学意义(P<0.05);观察组患者GOS评分显著高于对照组,差异有统计学意义(P<0.05)。两组患者治疗期间未见明显不良反应发生。结论:复方麝香注射液联合依达拉奉可改善颅脑外伤患者凝血功能和神经功能,且可减轻患者颅脑损伤严重程度,改善预后。

关键词：复方麝香注射液依达拉奉颅脑外伤凝血功能神经功能