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International Journal of Modelling Identification and Control最新文献

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Data driven optimal control for stochastic systems with non-Gaussian disturbances 非高斯扰动随机系统的数据驱动最优控制
IF 0.7 Q4 AUTOMATION & CONTROL SYSTEMS
International Journal of Modelling Identification and Control
Pub Date : 2021-01-01 DOI: 10.1504/ijmic.2021.10048248
Liping Yin, Tao Li, Yue Hong, Lanlan Lai
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引用次数: 0
Adaptation of deep learning auditory event recognition and detection in audio surveillance systems 音频监控系统中深度学习听觉事件识别与检测的适应性
IF 0.7 Q4 AUTOMATION & CONTROL SYSTEMS
International Journal of Modelling Identification and Control
Pub Date : 2021-01-01 DOI: 10.1504/ijmic.2021.10048115
K. Laabidi, S. Alsubhi, Ahad Alkabsani, Safiah Endargiri
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引用次数: 0
Induction motor current ripple minimisation with PV-based SEPIC-cascaded inverter 基于pv的sepic级联逆变器的感应电机电流纹波最小化
IF 0.7 Q4 AUTOMATION & CONTROL SYSTEMS
International Journal of Modelling Identification and Control
Pub Date : 2020-01-01 DOI: 10.1504/IJMIC.2020.10035278
Walid Emar, Z. Huneiti, Zakaria Al Omari
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引用次数: 1
Adaptive combination synchronisation of unknown chaotic Lorenz, L 未知混沌Lorenz的自适应组合同步
IF 0.7 Q4 AUTOMATION & CONTROL SYSTEMS
International Journal of Modelling Identification and Control
Pub Date : 2020-01-01 DOI: 10.1504/IJMIC.2020.10038189
M. A. Sawalha, Y. Jawarneh, Israr Ahmad, M. Shatnawi
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引用次数: 0
A tracking method for inland river ship based on dual filters 一种基于双滤波器的内河船舶跟踪方法
IF 0.7 Q4 AUTOMATION & CONTROL SYSTEMS
International Journal of Modelling Identification and Control
Pub Date : 2020-01-01 DOI: 10.1504/IJMIC.2020.10036392
Xiaoben Lei, Xu Minghai, Hu Zhongyi
{"title":"A tracking method for inland river ship based on dual filters","authors":"Xiaoben Lei, Xu Minghai, Hu Zhongyi","doi":"10.1504/IJMIC.2020.10036392","DOIUrl":"https://doi.org/10.1504/IJMIC.2020.10036392","url":null,"abstract":"","PeriodicalId":46456,"journal":{"name":"International Journal of Modelling Identification and Control","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77041705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
System identification of proportional solenoid valve dynamics. 比例电磁阀动力学系统辨识。
IF 0.7 Q4 AUTOMATION & CONTROL SYSTEMS
International Journal of Modelling Identification and Control
Pub Date : 2020-01-01 Epub Date: 2020-10-13 DOI: 10.1504/ijmic.2020.10032851
Bakir Hajdarevic, Jacob Herrmann, Andrea Fonseca da Cruz, David W Kaczka

We present a system identification technique for the characterisation of the linearity and dynamic response of a PSOL valve and its corresponding electronic control unit (ECU) using bandlimited white noise, as well as pseudo random "non-sum non-difference" (NSND) waveforms consisting of mutually prime frequencies to mitigate the effects of nonlinear distortions. The parameters of several transfer function models were simultaneously estimated from the voltage-flow frequency response using a nonlinear gradient descent technique. Candidate transfer function models were assessed using the mean squared residual (MSR) criterion and the corrected Akaike information criterion (AICc). The MSR yielded a transfer function consisting of 10 poles and 9 zeros, while the AICc yielded a simpler transfer function consisting of 5 poles and 3 zeros. Monte Carlo analysis demonstrated fragile stability for the MSR-selected model with respect to varying parameter values within estimated uncertainties, yet a robust stability for the AICc-selected model.

我们提出了一种系统识别技术，用于表征PSOL阀及其相应的电子控制单元(ECU)的线性和动态响应，该技术使用限带白噪声以及由互素数频率组成的伪随机“非和非差”(NSND)波形，以减轻非线性失真的影响。采用非线性梯度下降法从电压流频率响应中同时估计出多个传递函数模型的参数。使用均方残差(MSR)准则和修正的赤池信息准则(AICc)评估候选传递函数模型。MSR产生了一个由10个极点和9个零组成的传递函数，而AICc产生了一个由5个极点和3个零组成的更简单的传递函数。蒙特卡罗分析表明，msr选择的模型在估计的不确定性范围内相对于不同的参数值具有脆弱的稳定性，而aicc选择的模型具有稳健的稳定性。
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引用次数: 1
Estimation of inhalation exposure to metals among welders of a steel company using MEASE model: as a screening tool for estimates of occupational exposure 使用MEASE模型估计钢铁公司焊工的金属吸入暴露:作为职业暴露估计的筛选工具
IF 0.7 Q4 AUTOMATION & CONTROL SYSTEMS
International Journal of Modelling Identification and Control
Pub Date : 2020-01-01 DOI: 10.1504/ijmic.2020.10030641
M. Rismanchian, Younes Mehrifar, S. K. Zeverdegani
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引用次数: 1
RBF NN observer based adaptive feedback control for the ABS system under parametric uncertainties and modelling errors 基于RBF神经网络观测器的ABS系统参数不确定性和建模误差自适应反馈控制
IF 0.7 Q4 AUTOMATION & CONTROL SYSTEMS
International Journal of Modelling Identification and Control
Pub Date : 2020-01-01 DOI: 10.1504/IJMIC.2020.10037492
A. Hamou, Rabhi Abdelhamid, Belkheiri Mohammed
An antilock braking (ABS) scheme control is a relatively difficult task due to its uncertain nonlinear dynamics. According to the requirement that the braking process must be fast and robust, we contribute to extending the universal function approximation property of the radial-basis-function (RBF) neural network (NN) to design both: (a) adaptive NN observer to estimate the tracking error dynamics; and (b) intelligent NN output feedback controller (OFC) that will overcome successfully the existing high uncertainties. Notice that the OFC is introduced to linearise the ABS nonlinear system, and the dynamic compensator is involved to stabilise the linearised system. The estimated states are used in the adaptation laws as an error signal. Simulations of the proposed control algorithm based adaptive RBFNN observer are conducted then compared to the Bang-bang controller to demonstrate its practical potential. Furthermore, its efficiency has been successfully confirmed through a robustness test.
防抱死制动(ABS)方案控制由于其非线性动力学的不确定性，是一个比较困难的问题。根据制动过程的快速性和鲁棒性要求，对径向基函数(RBF)神经网络(NN)的通用函数逼近特性进行了扩展，设计了自适应神经网络观测器来估计跟踪误差动态;(b)智能神经网络输出反馈控制器(OFC)，该控制器将成功克服现有的高不确定性。注意，OFC被引入到ABS非线性系统的线性化中，而动态补偿器被用于稳定线性化的系统。估计的状态在自适应律中用作误差信号。通过对基于自适应RBFNN观测器的控制算法进行仿真，并与Bang-bang控制器进行比较，验证了该算法的实际应用潜力。通过鲁棒性检验，验证了该方法的有效性。
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引用次数: 0
Roll angle dynamic control of unicycle robot using backstepping controller and sliding mode controller 基于反步控制器和滑模控制器的独轮车机器人滚转角动态控制
IF 0.7 Q4 AUTOMATION & CONTROL SYSTEMS
International Journal of Modelling Identification and Control
Pub Date : 2020-01-01 DOI: 10.1504/ijmic.2020.10040954
Elkinany Boutaina, Alfidi Mohammed, Chalh Zakaria
The unicycle robot is the most sophisticated and the newest mechanism used in robotics industry regarding its high degree of mobility. It represents an unbalanced, non-holonomic system that can move and stand with only one wheel. Accordingly, it is the best platform for researchers to model and study stability. This paper focuses on the modelling of the unicycle robot using the Lagrangian dynamic formulation. Henceforth, two nonlinear controllers are presented: the sliding mode and the backstepping controllers that were designed to control the roll angle. Both controllers were simulated and the results showed that the stabilisation of the roll angle can achieve a good performance and good robustness using the backstepping controller rather than the sliding mode controller (SMC).
独轮车机器人由于其高度的机动性，是目前机器人工业中应用最精密、最新的机构。它代表了一个不平衡的，非完整的系统，只有一个轮子可以移动和站立。因此，它是研究人员建模和研究稳定性的最佳平台。利用拉格朗日动力学公式对独轮车机器人进行建模。在此基础上，提出了两种非线性控制器:滑模控制器和反步控制器。仿真结果表明，与滑模控制器(SMC)相比，采用反步控制器可以获得较好的横摇角稳定化性能和鲁棒性。
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引用次数: 1
Fuzzy H∞ filtering for nonlinear 2D systems in the Roesser model 二维非线性系统的Roesser模型模糊H∞滤波
IF 0.7 Q4 AUTOMATION & CONTROL SYSTEMS
International Journal of Modelling Identification and Control
Pub Date : 2019-12-31 DOI: 10.1504/ijmic.2019.10026100
Khalid Badie, M. Alfidi, Z. Chalh
This study focuses on the H∞ filtering problem for two-dimensional (2D) discrete Takagi-Sugeno (T-S) fuzzy systems in the Roesser model. The objective is to design a stable filter guaranteeing the asymptotic stability and a prescribed H∞ performance of the filtering error system. By using a new structure of the fuzzy Lyapunov function, and some analysis techniques, the stability and a prescribed H∞ performance index are guaranteed for the overall filtering-error system, such that the coupling between the Lyapunov matrix and the system matrices is removed. In addition, sufficient conditions for the existence of such a filter are established in term of linear matrix inequalities (LMIs). When these LMIs are feasible, the explicit expression of the desired filter can be characterised. An illustrative example is presented to demonstrate the effectiveness of the developed results.
本文主要研究Roesser模型中二维离散Takagi-Sugeno (T-S)模糊系统的H∞滤波问题。目的是设计一个稳定的滤波器，保证滤波误差系统的渐近稳定性和规定的H∞性能。利用一种新的模糊Lyapunov函数结构和一些分析技术，保证了整个滤波误差系统的稳定性和规定的H∞性能指标，从而消除了Lyapunov矩阵与系统矩阵之间的耦合。此外，利用线性矩阵不等式(lmi)建立了该滤波器存在的充分条件。当这些lmi可行时，期望滤波器的显式表达式可以表征。最后通过一个算例说明了所开发结果的有效性。
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引用次数: 0
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