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Fuzzy dynamic characteristic model based attitude control of hypersonic vehicle in gliding phase

Science China(Information Sciences) 2011年第3期54卷 448-459页

作者： LUO Xiong 1,2 & LI Jiang 1 1 department of computer Science and Technology, Key Laboratory of Advanced control of Iron and Steel process (Ministry of Education), University of Science and Technology Beijing, Beijing 100083, China 2 National Laboratory of Space Intelligent control, Beijing 100190, China 1. Department of Computer Science and Technology Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) University of Science and Technology Beijing Beijing 100083 China2. National Laboratory of Space Intelligent Control Beijing 100190 China

The intelligent autonomous control of hypersonic vehicles has aroused great interest from the field of spacecraft. To solve the problem of longitudinal attitude control of hypersonic vehicle in gliding phase, a new intelligent controller is proposed in this paper. This new controller is based on the fuzzy dynamic characteristic modeling method. The fuzzy logic is introduced into the characteristic modeling by dividing the whole restriction range into several subspaces. Simulations show that this modification greatly improves the performance of the original method. With the same whole restriction range the fuzzy dynamic characteristic modeling decreases the time of convergence, and at the same time makes the attitude angle tracing more precise and robust. Since the sub-model is a characteristic model that has stronger adaptiveness than a fixed local model, the number of fuzzy rules is greatly reduced. Our model sharply reduces the complexity in constructing a fuzzy dynamic model. Finally, simulation results are given to show the effectiveness of the proposed approach in dealing with the attitude control problem of hypersonic vehicle in gliding phase.

关键词： hypersonic vehicle gliding attitude control fuzzy dynamic characteristic modeling

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Robust H∞output feedback control for a class of uncertain Lur'e systems with time-delays

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2004年第9期 108-117页

作者：曹丰文鲁仁全苏宏业褚健 Zhejiang University Hangzhou 310027 Institute oj Advanced Process Control Suzhou 215011 Suzhou Vocational University Department of Computer and Electron China

In this work, the analysis of robust stability and design of robust H∞ output feedback controllers for a class of Lur’e systems with both time-delays and parameter uncertainties were studied. A robust H∞ output feedback controller based on Linear Matrix Inequalities (LMIs) was developed to guarantee the robust stability and H∞ performance of the resultant closed-loop system. The presented design approach is based on the application of descriptor model transformation and Park’s inequality for the bounding of cross terms and is expected to be less conservative compared to reported design methods. Finally, illustrative examples are advanced to demonstrate the superiority of the obtained method.

关键词： Lur’e systems Robust H∞ control Linear Matrix Inequality (LMI)

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Cost-optimal model predictive scheduling of home appliances

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IFAC-PapersOnLine 2017年第1期50卷 3344-3349页

作者： Bálint R. Magyar A. Hangos K.M. Department of Electrical Engineering and Information Systems Faculty of Information Technology University of Pannonia Veszprém Hungary Process Control Research Group HAS Research Institute for Computer Science and Control Budapest Hungary

A novel heuristic model-based optimal scheduling algorithm is proposed in this paper to operate heating and cooling type home appliances connected to smart grids where the price of the electrical energy is known in advance and temperature constraints are present. The properties and the use of the proposed algorithm are shown using a simple refrigerator model. The accuracy and the computational properties of the proposed method are compared to the schedule generated by the MPT toolbox. The algorithm works well with a relatively short prediction horizon using a fraction of the computing time needed for the MPT-based method. The robustness of the algorithm is also investigated with respect to the load of the refrigerator. It is shown that the designed schedule with an empty refrigerator is always suitable, yet not optimal, for any loaded case. © 2017

关键词： Demand side management Heuristics Model predictive control Scheduling algorithms Smart grids

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GLEm-Net: Unified Framework for Data Reduction with Categorical and Numerical Features

GLEm-Net: Unified Framework for Data Reduction with Categori...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： De Santis, Francesco Giordano, Danilo Mellia, Marco Damilano, Alessia Politenico di Torino Department of Control and Computer Engineering Torino Italy Bitron Electronic Division Quality and Process Digitalization Deparment Grugliasco Italy

ISBN: (纸本)9798350324457

In the era of Big Data, effective data reduction through feature selection is of paramount importance for machine learning. This paper presents GLEm-Net (Grouped Lasso with Embeddings Network), a novel neural framework that seamlessly processes both categorical and numerical features to reduce the dimensionality of data while retaining as much information as possible. By integrating embedding layers, GLEm-Net effectively manages categorical features with high cardinality and compresses their information in a less dimensional space. By using a grouped Lasso penalty function in its architecture, GLEm-Net simultaneously processes categorical and numerical data, efficiently reducing high-dimensional data while preserving the essential information. We test GLEm-Net with a real-world application in an industrial environment where 6 million records exist and each is described by a mixture of 19 numerical and 7 categorical features with a strong class imbalance. A comparative analysis using state-of-the-art methods shows that despite the difficulty of building a high-performance model, GLEm-Net outperforms the other methods in both feature selection and classification, with a better balance in the selection of both numerical and categorical features. © 2023 IEEE.

关键词： categorical features data reduction embeddings feature selection neural network

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Distributed Constrained Online Nonconvex Optimization with Compressed Communication

arXiv

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arXiv 2025年

作者： Zhang, Kunpeng Xu, Lei Yi, Xinlei Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai201210 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents. For a time-varying graph, we propose a distributed online primal–dual algorithm with compressed communication to efficiently utilize communication resources. We show that the proposed algorithm establishes an O(T max{1−θ1,θ1}) network regret bound and an O(T 1−θ1/2) network cumulative constraint violation bound, where T is the number of iterations and θ1 ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints at all iterations), the network cumulative constraint violation bound is reduced to O(T 1−θ1). These bounds are comparable to the state-of-the-art results established by existing distributed online algorithms with perfect communication for distributed online convex optimization with (time-varying) inequality constraints. Finally, a simulation example is presented to validate the theoretical results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

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Delays in Model Reduction of Chemical Reaction Networks

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IFAC-PapersOnLine 2018年第14期51卷 100-105页

作者： Lipták, György Hangos, Katalin M. Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences P.O. Box 63 BudapestH-1518 Hungary Department of Electrical Engineering and Information Systems University of Pannonia Veszprém Hungary

A novel engineering model reduction method is proposed in this paper that can be applied to a chemical reaction network (CRN) with chains of linear reactions. The reduced model is a delayed CRN with possibly different delays but with less state variables than the original model. As the first step of the model reduction, a decomposition method is also developed to transform chains with joint reactions into independent chains of linear reactions. The well known example of McKeithan's network is used as a case study to illustrate the basic concepts and the design method. © 2018

关键词： Reduction

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Dynamical modeling and identification of a GnRH neuron

Dynamical modeling and identification of a GnRH neuron

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作者： Csercsik, Dávid Szederkényi, Gábor Hangos, Katalin M. Farkas, Imre Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Budapest Hungary Department of Endocrine Neurobiology Institute of Experimental Medicine HAS Budapest Hungary

ISBN: (纸本)9783902661494

GnRH neurons, as key elements of the reproductive neuroendocrine system, have important central regulating role in the dynamics of the hormonal cycle. A Hodgkin-Huxley type neural model is proposed in this paper, that takes into account up-to-date biological literature data related to ion channels. The proposed neuron model is highly nonlinear in parameters and the evaluation of the objective function is computationally flexpensive, therefore the asynchronous parallel pattern search (APPS) procedure has been used for identification. The model with high number of estimated parameters provides a qualitatively good fit of both voltage clamp and current clamp traces. © 2009 IFAC.

关键词： Neurons

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Model synthesis identification a Hodgkin-Huxley-type neuron model 10

Model synthesis identification a Hodgkin-Huxley-type neuron ...

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2009 10th European control Conference, ECC 2009

作者： Csercsik, David Szederkenyi, Gabor Hangos, Katalin M. Farkas, Imre Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Budapest Hungary Department of Endocrine Neurobiology Institute of Experimental Medicine HAS Budapest Hungary

ISBN: (纸本)9783952417393

GnRH neurons are key elements of the reproductive neuroendocrine system and play important central regulating role in the dynamics of the hormonal cycle. A conductance-based Hodgkin-Huxley model structure is proposed in this paper in the form of nonlinear ordinary differential equations that is able to take into account up-to-date biological literature data related to ion channels. Measurement data were available for parameter estimation, which are originated from laboratory experiments done in the Institute of Experimental Medicine of the Hungarian Academy of Sciences in the form of whole cell patch-clamp recordings. The proposed neuron model is highly nonlinear in parameters and the evaluation of the objective function is computationally expensive, therefore the asynchronous parallel pattern search (APPS) procedure has been used for identification which is a gradient-free optimization method that can handle linear equality and inequality constraints and has advantageous convergence properties. The model with high number of estimated parameters provides a qualitatively good fit of both voltage clamp and current clamp traces. © 2009 EUCA.

关键词： Parameter estimation

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Robust H∞ control of Average Dwell Time Switching Systems via Non-monotonic Lyapunov Function Approach 3

Robust H∞ Control of Average Dwell Time Switching Systems v...

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2017 3rd IEEE International Conference on control Science and Systems Engineering (ICCSSE)

作者： Yun Xie Jiwei Wen Li Peng Howard Wang Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) School of Internet of Things Engineering Industry Jiangnan University Department of Electrical and Computer Engineering University of Auckland

ISBN: (纸本)9781538604854

This paper develops a non-monotonic Lyapunov function(LF) approach for discrete-time switching linear system with average dwell time(ADT) switching to improve the stability criterion and achieve better H∞ performance. Such an approach allows the LF to increase both at the switching instants and during the running time of subsystems, but guarantees an average decrease on every two sampling steps. Based on the results of stability and H∞ analysis, a robust H∞ controller is further designed. Moreover, the relationship between the time difference of LF and switching rate i.e. the ADT constraint, is revealed. An example is given to demonstrate the validity and potential of the developed results.

关键词： switched systems non-monotonic lyapunov function robust control

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A NEW NON-INVASIVE METHOD FOR VALVE STICTION DECTION USING WAVELET TECHNOLOGY

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Journal of Electronics(China) 2009年第5期26卷 673-680页

作者： Xu Zhanyang Charles Zhan Zhang Shunyi Institute of Information Network Technology Nanjing University of Posts ＆ Telecommunications Nanjing 210003 China Department of Computer Sciences~ Nanjing University of Information Science and Technology Nanjing 210044 China Advanced Process Control Research and Development Group Honeywell Process Solutions Phoenix AZ 85027 USA

In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavelet transform is used to decompose the data at different resolution scales. Based on the Lipschitz regularity theory, wavelet coefficients analysis across scales is performed to detect the jumps in the controlled variables. Adaptive wavelet de-noising is then applied to the data. Features of the valve stiction patterns are extracted from the de-noised data and the valve stiction probability is calculated.

关键词： Valve stiction Wavelet de-noising Jump Features extraction

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