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第43届中国控制会议

作者： Ruifen Dai Fang Wang Lei Guo Data Science Institute Shandong University Key Laboratory of Systems and Control AMSS Chinese Academy of Sciences

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper considers the adaptive identification and prediction problems for finite impulse response(FIR) systems with quantized observations. Although a number of related works are devoted to such problems, persistent excitation(PE)conditions or even stronger statistical assumptions are usually required to ensure strong consistency of parameter estimates,which are difficult to be verified or satisfied for stochastic feedback control systems. In this paper, we construct a projected recursive Quasi-Newton type identification algorithm for FIR systems with quantized observations and varying thresholds, and obtain its global convergence and convergence rate under the weakest possible non-persistent excitation(non-PE) condition by properly using stochastic Lyapunov function method and martingale estimation theory. Moreover, we obtain the accuracy of adaptive predictors by analysing the asymptotic order of the averaged regret without resorting to any excitation condition. All the above results can be considered as a generalization of the recent results for stochastic regression models with binary-valued observations. A classification experiment based on judicial crimes is also provided.

关键词： Adaptive Identification Quantized Observation Non-Persistent Excitation Adaptive Prediction Martingales

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A minimum adequate set of multi-valued logic

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control Theory and Technology 2021年第4期19卷 425-429页

作者： Daizhan Cheng Jun-e Feng Jianli Zhao Shihua Fu Research Center of Semi-tensor Product of Matrices:Theory and Applications Liaocheng UniversityLiaochengChina Key Laboratory of Systems and Control AMSSChinese Academy of SciencesBeijing 100190China School of Mathematics Shandong UniversityJinanChina

An adequate set of k-valued logic is provided,which contains only two *** is also proved that this adequate set is of minimum size。

关键词： k-valued logic Normal form Adequate set(ADS) Structure matrix of logical functions Semi-tensor product of matrices

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PID control of Nonlinear Stochastic systems with Structural Uncertainties ⁎

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IFAC-PapersOnLine 2020年第2期53卷 2189-2194页

作者： Jinke Zhang Lei Guo Key Laboratory of Systems and Control AMSS Chinese Academy of Sciences Beijing 100190 China School of Mathematical Science UCAS Beijing 100049 China

It is widely known that the classical PID (proportional-integral-derivative) controller still plays a dominating role in engineering control systems, and that most of the theoretical studies on PID control focus on linear deterministic systems. In this paper, we will extend the authors recent theoretical investigation by considering additional uncertainties in the input channel, and try to establish a theoretical foundation on the PID control for a class of high-dimensional nonlinear stochastic systems with structural uncertainties consisting of dynamics uncertainty, diffusion uncertainty and input channel uncertainty. We will construct a three dimensional parameter set based on the available information, so that under the classical PID control, the closed-loop control system can be globally stabilized with regulation error tending to zero in the mean square sense, as long as the three PID parameters are chosen from this set. We will further show that global stabilization and asymptotic regulation of a class of multi-agent uncertain nonlinear stochastic systems can also be achieved by uncoupled PID controllers of the agents.

关键词： PID control nonlinear systems random noises

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Matrix expression of finite boolean-type algebras

arXiv

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arXiv 2019年

作者： Cheng, Daizhan Feng, Jun-e Zhao, Jianli Fu, Shihua STP Center Liaocheng University Liaocheng Shangdong Province Key Laboratory of Systems and Control AMSS Chinese Academy of Sciences School of Mathematics Shandong University China

Boolean-type algebra (BTA) is investigated. A BTA is decomposed into Boolean-type lattice (BTL) and a complementation algebra (CA). When the object set is finite, the matrix expressions of BTL and CA (and then BTA) are presented. The construction and certain properties of BTAs are investigated via their matrix expression, including the homomorphism and isomorphism, etc. Then the product/decomposition of BTLs are considered. A necessary and sufficient condition for decomposition of BTA is obtained. Finally, a universal generator is provided for arbitrary finite universal algebras. Copyright © 2019, The Authors. All rights reserved.

关键词： Matrix algebra

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Convergence of Self-Tuning Regulators under Conditional Heteroscedastic Noises 36

Convergence of Self-Tuning Regulators under Conditional Hete...

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第36届中国控制会议

作者： Yaqi Zhang Lei Guo Key Laboratory of Systems and Control AMSSChinese Academy of Sciences

ISBN: (纸本)9781538629185

Traditional convergence theory of self-tuning regulators requires boundedness of the conditional variances of the systems noise processes. However, this requirement cannot be satisfied for many practical models such the well-known ARCH(Autoregressive Conditional Heteroscedasticity) model in economic systems. The aim of this paper is to provide a convergence theory of self-tuning regulators for linear uncertain systems with conditional heteroscedastic noises, where the conditional variance is unbounded. To be specific, we consider weighted least-squares-based self-tuning regulators, and establish both the global stability and the optimality of tracking under some natural conditions on the system models as well as on the conditional heteroscedastic noises. To the best of the authors’ knowledge, this is the first paper that investigates this kind of problems with a convergence theory, and makes the self-tuning regulators applicable to systems with noised modeled by ARCH.

关键词： Self-Tuning Regulator Conditional Heteroscedasticity ARCH Model Weighted Least-Squares Algorithm Convergence

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Two New Results on STP-based Algebraic Structures

Two New Results on STP-based Algebraic Structures

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第35届中国控制会议

作者： Yupeng Qiao Daizhan Cheng College of Automation Science and Engineering South China University of Technology Key Laboratory of Systems and Control AMSS Chinese Academy of Sciences

In this paper we consider two semi-tensor product(STP) based algebraic structures. First, the set of matrices of arbitrary dimensions(including scalars as 1 × 1 dimensional matrices) is considered. It is shown that under STP they form a monoid. Some useful submonoids are also investigated. Second. the set of static logical systems(SLSs) is investigated. Using the antecedence and consequence solutions, a lattice structure is posed to the set of SLSs. Certain properties are investigated.

关键词： Semi-tensor product of matrices Monoid Static logical systems Antecedence/consequence solution Lattice

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A fast and compact saliency score regression network based on fully convolutional network

arXiv

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arXiv 2017年

作者： Xi, Xuanyang Luo, Yongkang Li, Fengfu Wang, Peng Qiao, Hong State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai200031 China Research Center of Precision Sensing and Control Institute of Automation Chinese Academy of Sciences Beijing100190 China LSEC Institute of Applied Mathematics AMSS Chinese Academy of Sciences Beijing100190 China

Visual saliency detection aims at identifying the most visually distinctive parts in an image, and serves as a pre-processing step for a variety of computer vision and image processing tasks. To this end, the saliency detection procedure must be as fast and compact as possible and optimally processes input images in a real time manner. It is an essential application requirement for the saliency detection task. However, contemporary detection methods often utilize some complicated procedures to pursue feeble improvements on the detection precession, which always take hundreds of milliseconds and make them not easy to be applied practically. In this paper, we tackle this problem by proposing a fast and compact saliency score regression network which employs fully convolutional network, a special deep convolutional neural network, to estimate the saliency of objects in images. It is an extremely simplified end-to-end deep neural network without any pre-processings and post-processings. When given an image, the network can directly predict a dense full-resolution saliency map (image-to-image prediction). It works like a compact pipeline which effectively simplifies the detection procedure. Our method is evaluated on six public datasets, and experimental results show that it can achieve comparable or better precision performance than the state-of-the-art methods while get a significant improvement in detection speed (35 FPS, processing in real time). Copyright © 2017, The Authors. All rights reserved.

关键词： Deep neural networks

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Recursive Identification of Hammerstein With Noisy Observations

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IFAC-PapersOnLine 2015年第28期48卷 1017-1022页

作者： Mu, Biqiang Han-Fu, Chen Wang, Le Yi Yin, George Key Laboratory of Systems and Control Institute of Systems Science AMSS Chinese Academy of Sciences Beijing100190 China Department of Electrical and Computer Engineering Wayne State University Detroit MI48202 United States Department of Mathematics Wayne State University Detroit MI48202 United States

The paper considers the recursive identification of Hammerstein systems with noisy output, while its input may or may not be corrupted by noise. The system in the latter case is usually called as EIV system. The conditions required in this paper are considerably weaker than those used in previous works, e.g., the orders of the linear subsystem are allowed to be unknown and no additional conditions are imposed on its moving average part. The nonlinearity is general in the sense that a certain class of functions is out of consideration in some previous papers. In the paper, the almost sure convergence together with convergence rate are established for the estimates for coefficients of the linear part, and then the almost sure convergence for the estimates for the nonlinearity at any given points are derived by using kernel functions. The convergence rate for the nonlinearity is also obtained for the case where the system input is available without noise. A numerical example is provided, and the simulation results are consistent with the theoretical analysis. © 2015

关键词： control nonlinearities Nonlinear systems Numerical methods Almost sure convergence Convergence rates Errors in variables Hammerstein system Kernel function Linear subsystems Noisy observations Recursive identification

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Stability of diffusion adaptive filters 19

Stability of diffusion adaptive filters

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Chen, Chen Liu, Zhixin Guo, Lei Key Laboratory of Systems and Control Institute of Systems Science AMSS Beijing100190 China

ISBN: (纸本)9783902823625

In this paper, we consider the diffusion adaptive filters where a set of sensors is required to collectively estimate time-varying signals (or parameters) from noisy measurements in a way of information diffusion. We will establish the stability of the diffusion least mean square (DLMS) algorithm, without requiring stationarity, independency, and boundedness assumptions of the system signals, which means that our results can be applied to more general and practical class of stochastic systems than those studied in the literature. We will present theoretical results concerning stability and bounds on the mean square error (MSE) of the filtering. We will also show that the network of sensors can cooperate to guarantee the stability of the filtering, even though any single sensor does not have such a capability. This clearly reveals the advantages of the DLMS algorithm vs. standard least mean square (LMS) algorithm. Numerical simulations will also be presented to support the theoretical justifications. © IFAC.

关键词： Adaptive filters

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Stability of Diffusion Adaptive Filters

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IFAC Proceedings Volumes 2014年第3期47卷 10409-10414页

作者： Chen Chen Zhixin Liu Lei Guo Key Laboratory of Systems and Control Institute of Systems Science AMSS Chinese Academy of Sciences Beijing 100190 China

In this paper, we consider the diffusion adaptive filters where a set of sensors is required to collectively estimate time-varying signals (or parameters) from noisy measurements in a way of information diffusion. We will establish the stability of the diffusion least mean square (DLMS) algorithm, without requiring stationarity, independency, and boundedness assumptions of the system signals, which means that our results can be applied to more general and practical class of stochastic systems than those studied in the literature. We will present theoretical results concerning stability and bounds on the mean square error(MSE) of the filtering. We will also show that the network of sensors can cooperate to guarantee the stability of the filtering, even though any single sensor does not have such a capability. This clearly reveals the advantages of the DLMS algorithm vs. standard least mean square (LMS) algorithm. Numerical simulations will also be presented to support the theoretical justifications.

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