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基于学习自适应估计环的迭代学习控制

仪器仪表学报 2005年第z1期26卷 800-802页

作者：池荣虎侯忠生北京交通大学交通运输学院北京100044 北京交通大学电子与信息工程学院北京100044

针对一类具有强非线性和不确定性的离散时间系统,文章给出了一种基于学习自适应估计环的迭代学习控制方法。在迭代学习控制器的基础上设计了一个学习自适应估计环,用来镇定系统,给出迭代学习控制初始的控制输入值,同时根据估计出的系统... 详细信息

针对一类具有强非线性和不确定性的离散时间系统,文章给出了一种基于学习自适应估计环的迭代学习控制方法。在迭代学习控制器的基础上设计了一个学习自适应估计环,用来镇定系统,给出迭代学习控制初始的控制输入值,同时根据估计出的系统参数来确定迭代学习增益的取值范围。文章基于状态空间描述,分析了迭代学习控制系统的收敛性。仿真研究表明,该控制器能够实现完全跟踪,减少系统的初始输出误差,并加快了收敛速度。

关键词：学习自适应估计迭代学习控制非线性离散系统状态空间

Event-triggered Iterative Learning Control via Fixed Threshold Condition

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Event-triggered Iterative Learning Control via Fixed Thresho...

第32届中国过程控制会议(CPCC2021)

作者： Lin Na chi ronghu School of Automation & Electronic Engineering Qingdao University of Science & Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and Technology

In this paper,an event-triggered iterative learning control method is proposed for a class of nonlinear nonaffine discrete-time ***,a compact form iterative dynamic linearization method is introduced to transform the original nonlinear system into a linear data ***,the event triggering condition based on fixed threshold is *** parameter estimation algorithm and learning control law,only the output information of triggered iteration is used to reduce the sampling *** proposed method is data-driven and does not need any model *** analysis and simulation results verify the effectiveness of the proposed method.

关键词： Iterative learning control Event-triggered control Fixed threshold condition Nonlinear systems

On the Robustness of a Data-driven Optimal ILC method with Data Loss

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On the Robustness of a Data-driven Optimal ILC method with D...

第30届中国控制与决策会议

作者： Yunkai Lv ronghu chi School of Automation ＆ Electronic Engineering Qingdao University of Science ＆ Technology

In this work,the robustness of iterative learning control with random data loss is discussed for a class of general nonlinear *** loss of output data from the system sensor to the controller side is considered,and the data loss is described by Bernoulli random *** design of the system controller is based on the optimal *** strict convergence analysis process is developed with the condition of optimal iterative learning control ***,the validity of the proposed algorithm is verified by numerical simulation.

关键词： Data-driven Data loss Optimal ILC Robustness Analysis

Model-Free Adaptive Control Based on Local Dynamic Linearization

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Model-Free Adaptive Control Based on Local Dynamic Lineariza...

第30届中国控制与决策会议

作者： ronghu chi Shuhua Zhang Yu Hui College of Automation and Electronics Engineering Qingdao University of Science and Technology

Linearization technique is essential for the controller design and analysis of complex nonlinear plants. At least, the linear affine form of the original nonlinear process is required. However, the traditional linearization methods are approximation-based with unmodeled dynamics involved. In this work, a new local dynamic linearization method is proposed using differential mean-value theorem, which can be estimated by using the I/O data only. Then, a new model-free adaptive control is proposed by using the principle of optimality, where the controller design and analysis is data-driven without using any model information. The effectiveness of the proposed method is demonstrated by the simulation results.

关键词： Model free adaptive control Nonlinear discrete-time systems Local dynamic linearization Data-driven control

A New Model-Free Adaptive Control with an Extended State Observer

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A New Model-Free Adaptive Control with an Extended State Obs...

第37届中国控制会议

作者： Yu Hui Shuhua Zhang ronghu chi Xuhui Bu School of Automation & Electronic Engineering Qingdao University of Science & Technology School of Electrical Engineering and Automation Henan Polytechnic University

In this work, a new model-free adaptive control with an extended state observer for a class of nonlinear non-affine system has been proposed. The main feature is that the controller design depends merely on the I/O data, and an ESO has been introduced to deal with the uncertainty and disturbance problem. The effectiveness of the proposed control scheme is demonstrated by a numerical simulation.

关键词： model-free adaptive control extended state observer data driven control uncertainty disturbance

An Iterative Learning Model Predictive Control Strategy for Evaporator

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An Iterative Learning Model Predictive Control Strategy for ...

第37届中国控制会议

作者： Xiaohong Yin Xinli Wang Ximei Liu ronghu chi Mingming Lin Yanni Wang School of Automation & Electronic Engineering Qingdao University of Science & Technology School of Control Science and Engineering Shandong University Information and Communication Academy National University of Defence Technology

superheat degree of evaporator in heating, ventilating, and air-conditioning(HVAC) systems is a crucial variable, which not only maintains the system stability, but also impacts the system efficiency. In this study, an iterative learning model predictive control(ILMPC) strategy for the evaporator in vapor compressor refrigeration cycle(VCC) system is *** of all, a simple model of evaporator has been presented by mechanism knowledge and system identification. Then, based on the iterative learning theory and model predictive control method,an ILMPC controller is proposed to control the superheat ***, a simulation is provided to test the effectiveness of the proposed control strategy.

关键词： vapor compression refrigeration cycle system superheat degree iterative learning model predictive control

Synchronizing Servo Motion and Iterative Learning Control for Automatic High Speed Horizontal Flow Wrapper

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Synchronizing Servo Motion and Iterative Learning Control fo...

第24届中国控制与决策会议

作者： Shao Wei, chi ronghu, Yu Lei College of Automation & Electronic Engineering, Qingdao University of Science & Technology, Qingdao 266042

In this paper, a DSP-based servo motion controller is developed for the horizontal flow wrapper, where the multi-axis servo drives and electronic cam are designed to achieve multi-task and real-time motion control for precise control of the horizontal flow wrapper. An ILC add-on to feedback control method are developed to improve the film cutting accuracy and eliminate the repeatable position error when the product moves into the film former.

关键词： Motion Controller Horizontal Flow Wrapper Iterative Learning Control Electronic Cam Control

基于数据驱动高阶学习律的轮式移动机器人轨迹跟踪控制

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南京信息工程大学学报（自然科学版） 2021年第1期13卷 66-72页

作者：李佳伟林娜池荣虎青岛科技大学自动化与电子工程学院青岛266061

轮式机器人执行巡逻、播种和工业生产等任务是一个强非线性的间歇过程.针对重复运行的轮式机器人轨迹跟踪问题,本文提出了一种基于数据驱动的高阶迭代学习控制算法.首先,对轮式移动机器人的模型进行推导设计,并对推导得到的状态空间形... 详细信息

轮式机器人执行巡逻、播种和工业生产等任务是一个强非线性的间歇过程.针对重复运行的轮式机器人轨迹跟踪问题,本文提出了一种基于数据驱动的高阶迭代学习控制算法.首先,对轮式移动机器人的模型进行推导设计,并对推导得到的状态空间形式的离散时间模型利用基于状态转移的迭代动态线性化方法,将轮式机器人系统转化为线性输入输出数据模型;其次,设计高阶迭代优化目标函数得到控制律,并利用参数更新律估计线性输入输出数据模型中的未知参数.控制器的设计和分析只使用系统的输入输出数据,不包含任何显式的模型信息.通过采用高阶学习控制方法,在控制律中利用更多之前迭代的控制输入信息,提高了控制性能.最后,仿真结果验证了该方法在轮式机器人轨迹跟踪控制中的有效性.

关键词：数据驱动高阶学习律迭代学习轮式机器人

基于遗忘因子的数据驱动最优迭代学习控制算法研究

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南京信息工程大学学报（自然科学版） 2021年第5期13卷 582-588页

作者：李佳伟林娜池荣虎青岛科技大学自动化与电子工程学院青岛266061

针对一类有限时间内重复运行的非线性非仿射离散时间系统,本文提出了一种基于遗忘因子的数据驱动最优迭代学习控制方法.首先,引入一种迭代动态线性化方法,将被控非线性系统等效化为线性输入输出增量形式;其次,分析了最优迭代学习控制方... 详细信息

针对一类有限时间内重复运行的非线性非仿射离散时间系统,本文提出了一种基于遗忘因子的数据驱动最优迭代学习控制方法.首先,引入一种迭代动态线性化方法,将被控非线性系统等效化为线性输入输出增量形式;其次,分析了最优迭代学习控制方法中存在的问题,并针对由历史信息的累积效应所导致的控制输入不能及时响应的问题,设计自适应遗忘因子使算法具有更好的可控性和灵活性.所提出的控制方法是数据驱动的控制方法,设计和分析过程仅依赖于系统的输入输出数据,不包含任何显式模型信息.最后,通过仿真验证了该方法的有效性.

关键词：数据驱动控制遗忘因子动态线性化迭代学习控制