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作者： Grushkovskaya, Victoria Dürr, Hans-Bernd Ebenbauer, Christian Zuyev, Alexander Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart70569 Germany Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg39106 Germany Institute of Applied Mathematics and Mechanics National Academy of Sciences of Ukraine Sloviansk84100 Ukraine

The paper presents a control algorithm that steers a system to an extremum point of a time-varying function. The proposed extremum seeking law depends on values of the cost function only and can be implemented without knowing analytical expression of this function. By extending the Lie brackets approximation method, we prove the local and semi-global practical uniform asymptotic stability for time-varying extremum seeking problems. For this purpose, we consider an auxiliary non-autonomous system of differential equations and propose asymptotic stability conditions for a family of invariant sets. The obtained control algorithm ensures the motion of a system in a neighborhood of the curve where the cost function takes its minimal values. The dependence of the radius of this neighborhood on the bounds of the derivative of a time-varying function is shown. © 2017

关键词： control theory

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Soft sensor for monitoring dynamic changes in cell composition 9

Soft sensor for monitoring dynamic changes in cell compositi...

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9th IFAC Conference on Foundations of systems Biology in Engineering, FOSBE 2022

作者： Espinel-Ríos, Sebastián Morabito, Bruno Bettenbrock, Katja Klamt, Steffen Findeisen, Rolf Laboratory for System Theory and Automatic Control Otto von Guericke University Magdeburg Germany Analysis and Redesign of Biological Networks Max Planck Institute for Dynamics of Complex Technical Systems Germany Control and Cyber-Physical Systems Laboratory TU Darmstadt Germany

ISBN: (纸本)9781713867890

Precise and accurate online monitoring methods are needed to enable smart biomanufacturing and automation. Most of the sensors available focus on process parameters such as metabolite and dissolved gas concentrations, cell density or viability, among other variables like pH, temperature, etc. In this work, we develop a soft sensor algorithm to estimate the cell composition online, a very important aspect often overlooked in the bioprocess monitoring literature. Our strategy is based on full information estimation, an optimization-based estimator that takes into account the dynamics of the cell metabolism and considers all the available measurements from the beginning of the process, thus it has a memory effect. Being able to track dynamic changes in cell composition can open the door to promising applications, e.g., predictive control and automation of biosystems. As a case study, we consider the Escherichia coli's metabolism growing on glycerol under different levels of oxygen supply. We compare the performance of our soft sensor method against resource balance analysis, a previously proposed estimator based on steady-state assumptions. Overall, the presented full information estimator was able to track the dynamic changes in cell composition significantly more accurately. We also discuss how our estimation strategy can be transformed into a moving horizon estimation, where only the available measurements in a fixed and moving window are considered, thereby reducing possible computational burdens. Copyright © 2022 The Authors.

关键词： Metabolism

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Robust, Optimal PI-controller Tuning for Integrator Plus Delay Plants With Varying Parameters Based on Randomised Algorithms

Robust, Optimal PI-Controller Tuning for Integrator Plus Del...

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Conference on control and Fault-Tolerant systems

作者： Tim Konings Jonas Esch Christoph Kandler Steven X. Ding Chris Louen Institute of Automatic Control and Complex Systems (AKS) University of Duisburg-Essen

ISBN: (纸本)9781479928569

In this paper we consider the problem of tuning a PI-controller for robust, optimal performance with an integrator plus delay plant with varying plant parameters. The integrated absolute error for set-point tracking is considered as the performance index to be minimised by tuning. To this end, classical worst case and mean value based techniques for robust, performance optimal controller tuning are discussed. It is shown that these techniques require the consideration of an infinite amount of possible plant parameters in the optimisation step and are thus infeasible. To overcome this, we adopt randomised algorithms that allow an approximation of the original problem with a finite number of plant parameter samples in every step. Furthermore, we show that the minimisation problems to be solved in the randomised algorithm are convex and can thus be solved to their global minimiser, using readily available iterative algorithms. This is shown to introduce convexity of the set of stabilising controller parameters as a necessary condition, which is proven to hold for the problems considered here. Application of the proposed algorithm is shown for the tuning of a level controller in a continuous stirred tank heater demonstrator plant.

关键词： randomized algorithms integrators tuning variable parameter plant parameters PI control level controller Convexity performance indicators original problem

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Data-Driven Quality Monitoring and Fault Detection for Multimode Nonlinear Processes

Data-Driven Quality Monitoring and Fault Detection for Multi...

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IEEE Annual Conference on Decision and control

作者： Adel Haghani Steven X. Ding Jonas Esch Haiyang Hao Institute for Automatic Control and Complex Systems (AKS) University of Duisburg-Essen

ISBN: (纸本)9781467320658

This paper addresses the problem of quality monitoring and fault detection in nonlinear processes which are working in different operating points. For such processes the statistical model which is obtained from process data is different from one operating point to another, due to nonlinearities and set-point changes. Therefore the classical methods for quality monitoring and fault detection, e.g. partial least squares (PLS), may not be suitable. To this end, a new approach is proposed based on the modeling of nonlinear process as a piecewise linear parameter varying system, considering the behavior of the plant in each operating point as linear time invariant with different parameters in each operating point. The expectation-maximization (EM) algorithm is used to model the process as a finite mixture of Gaussian components and based on the identified model a Bayesian inference strategy is developed to detect the faults which influence the product quality. Finally, the usefulness of the proposed method is demonstrated on a laboratory continuous stirred tank heater (CSTH) setup.

关键词： quality monitoring Defect detection Workstations non-linear process time-invariant Set of points Bayesian inference data driven

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Integrated Fault Detection in Multiple Switched systems

Integrated Fault Detection in Multiple Switched Systems

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European control Conference

作者： Ali Abdo Steven X. Ding Jedsada Saijai Waseem Damlakhi Institute for Automatic Control and Complex Systems (AKS) University of Duisburg-Essen

ISBN: (纸本)9781479901890

This paper addresses a new strategy for constructing switched systems. This approach will be used to set an integrated fault detection filter (FDF). The basic idea behind this approach is to switch multiple sub-models with weighting factors that reflect the effect of each local sub-model. The main contributions of this paper are summarized as follows: (1) set a multiple switching technique for describing the system dynamic behavior. (2) integrate residual generation with evaluation and threshold setting. (3) enhance the fault detectability for the switched systems by utilizing available information provided by each local sub-model. (4) relax the stability condition for the switched observers in terms of switched Lyapunov functions (SLF). The proposed approach will be illustrated by lateral vehicle dynamics as an example.

关键词： Switched systems Switches Generators Fault detection Vectors Observers Vehicle dynamics

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Dynamic threshold for fault detection in Lipschitz nonlinear systems

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IFAC Proceedings Volumes 2009年第8期42卷 36-40页

作者： M. Abid S.X. Ding A.Q. Khan Institute of Automatic Control and Complex Systems Duisburg 47057 Germany (Tel: +49-203-3792933)

In this paper, a method of designing dynamic threshold for fault detection is proposed. The class of systems considered is nonlinear systems with Lipschitz nonlinearities and unstructured uncertainties. An inequality for the upper bound on the modulus of error dynamics is derived which is used for designing the dynamic threshold. The effectiveness of the proposed technique is demonstrated by simulation result for an electromechanical positioning system.

关键词： Fault detection dynamic threshold residual generation residual evaluation Lipschitz nonlinear systems

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WiNC – Advanced Experimentation Platform for Wireless Networked control

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IFAC Proceedings Volumes 2009年第8期42卷 995-1000页

作者： C.I. Chihaia O. Bredtmann E. Goldschmidt W. Li S.X. Ding A. Czylwik Institute for Automatic Control and Complex Systems (AKS) University of Duisburg-Essen Department of Communication Systems (NTS) University of Duisburg-Essen

WiNC is an experimentation platform for Wi reless N etworked C ontrol, built with off-the-shelf hardware and open source software. The platform is composed essentially of an application, a driver and a protocol stack optimized for industrial wireless communication. The protocol stack integrates a simplified addressing scheme with a custom packet structure and robust channel coding techniques, thus ensuring deterministic transmission times. The application integrates the communication functionality of organizing the network access by use of a schedule based on timeslots and tailored to the needs of the control system. It implements several control-specific functionalities including fault diagnosis and monitoring.

关键词： networked control systems wireless networks protocols scheduling algorithms

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Fault Detection of Networked control systems Based on Optimal Robust Fault Detection Filter

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自动化学报 2008年第12期34卷 1534-1539页

作者： WANG Yong-Qiang YE Hao DING X. Steven WANG Gui-Zeng Department of Automation Tsinghua University Beijing 100084 P. R. China Institute for Automatic Control and Complex Systems University of Duisburg-Essen Duisburg 47057 Germany

有可能比一个采样时期大的随机、未知的导致网络的延期的联网的控制系统(NCS ) 的差错察觉在这份报纸被学习。首先，导致网络的延期引起的影响被转变成为错误建模组织，然后存在连续时间域基于引用，模型被扩大到分离时间领域并且适用... 详细信息

有可能比一个采样时期大的随机、未知的导致网络的延期的联网的控制系统(NCS ) 的差错察觉在这份报纸被学习。首先，导致网络的延期引起的影响被转变成为错误建模组织，然后存在连续时间域基于引用，模型被扩大到分离时间领域并且适用指责联网的控制系统的察觉的柔韧的差错察觉方法。建议方法能被 Matlab LMI 工具箱容易实现，并且它的表演被一个模拟例子最后评估。

关键词：检测方法网络控制系统最优鲁棒故障检测系统滤波器

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Fault Diagnosis for Linear Discrete Time-Varying systems and Its Applications 1

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1000年

作者： Maiying Zhong Ting Xue Donghua Zhou Steven X. Ding

ISBN: (数字)9789811954382

ISBN: (纸本)9789811954375;9789811954405

This book focuses on fault diagnosis for linear discrete time-varying (LDTV) systems and its applications in modern engineering processes, with more weighting placed on the development of theory and methodologies. A comprehensive and systematic study on fault diagnosis for LDTV systems is provided, covering H∞-optimization-based fault diagnosis, H∞-filtering-based fault diagnosis, parity space-based fault diagnosis, Krein space technique-aided fault detection and fault estimation, and their typical applications in linear/nonlinear processes such as satellite attitude control systems and INS/GPS systems. This book benefits researchers, engineers, and graduate students in the fields of control engineering, electrical and electronic engineering, instrumentation science, and optoelectronic engineering.

关键词： control and systems Theory Mathematical and Computational Engineering systems Theory, control

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OBSERVER DESIGN FOR T-S FUZZY systems WITH MEASUREMENT OUTPUT NOISES

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IFAC Proceedings Volumes 2005年第1期38卷 1-6页

作者： Zhiwei Gao Xiaoyan Shi Steven X. Ding Institute for Automatic Control & Complex Systems University of Duisburg-Essen Department of Automation Tianjin University Tianjin 300072

In this paper, new observer design approaches are presented for Takagi-Sugeno (T-S) fuzzy models with measurement output noises. In order to decouple the measurement noise, an augmented fuzzy descriptor model is first constructed. Then a fuzzy descriptor proportional and derivative (PD) observer is developed. When the fuzzy subsystems have the same output matrices, another fuzzy descriptor observer is designed, which can be transformed into a normal fuzzy observer. Via the proposed two kinds of fuzzy observer design, the state and the output noise can be estimated at the same time. The simulation result shows the satisfactory tracking performance.

关键词： Descriptor system fuzzy systems measurement noises observer TS model

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