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Identification of the gain system with quantized observations and bounded persistent excitations

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Science China(Information Sciences) 2014年第1期57卷 217-231页

作者： GUO Jin zhao yanlong Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems ScienceChinese Academy of Sciences

System identification with quantized observations and persistent excitations is a fundamental and difcult *** the first step,this paper takes the gain system for example to investigate the identification with quantized observations and bounded persistently exciting ***,the identification with single threshold quantization is considered.A projection recursive algorithm is proposed to estimate the unknown *** use of the conditional expectation of quantized observations with respect to the estimates,the algorithm is shown to be both mean-square and almost surely *** upper bound of the convergence rate is also obtained,which has the same order as the one of the optimal estimation in the case where the system output is exactly ***,for the multi-threshold quantization,the identification algorithm is similarly constructed and its asymptotic property is *** a multi-linear transformation,the optimal scheme of quantization values and thresholds is given.A numerical example is simulated to demonstrate the efectiveness of the algorithms and the main results obtained.

关键词： system identification quantized observation bounded persistent excitation binary-valued output multi-threshold quantization convergence convergence rate

Iterative parameter estimate with batched binary-valued observations

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Science China(Information Sciences) 2016年第5期59卷 158-175页

作者： yanlong zhao Wenjian BI Ting WANG Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of Sciences

In this paper, we consider linear system identification with batched binary-valued *** constructed an iterative parameter estimate algorithm to achieve the maximum likelihood(ML) *** first interesting result was that there exists at most one finite ML solution for this specific maximum likelihood problem, which was induced by the fact that the Hessian matrix of the log-likelihood function was negative definite under binary data and Gaussian system noises. The global concave property and local strongly concave property of the log-likelihood function were obtained. Under mild conditions on the system input, we proved that the ML function has a unique maximum point. The second main result was that the ML estimate was consistent under persistent excitation inputs, which infers the effectiveness of ML estimate. Finally, the proposed iterative estimate algorithm converged to a fixed vector with an exponential rate that was proved by constructing a Lyapunov function. A more interesting result was that the limit of the iterative algorithm achieved the maximization of the ML function. Numerical simulations are illustrated to support the theoretical results obtained in this paper well.

关键词： Binary-valued observation maximum likelihood estimate strongly convex system identification exponential rate

FIR system identification with set-valued and precise observations from multiple sensors

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Science China(Information Sciences) 2019年第5期62卷 179-194页

作者： Hang ZHANG Ting WANG yanlong zhao Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences

This paper considers the system identification problem for FIR(finite impulse response) systems with set-valued and precise observations received from multiple sensors. A fusion estimation algorithm based on some suitable identification algorithms for different types of observations is proposed. In particular, least square method is chosen for FIR systems with precise observations, while empirical measure method and EM algorithm are chosen for FIR systems with set-valued observations in the cases of periodic and general system inputs, respectively. Then, the quasi-convex combination estimator(QCCE) fusing the two different estimators by a linear combination with appropriate weights is constructed. Furthermore, the convergence properties are theoretically analyzed in terms of strong consistency and asymptotic efficiency. The fused estimator QCCE is proved to achieve the Cram′er-Rao(CR) lower bound asymptotically under periodic inputs. Extensive numerical simulations validate the superiority of the fusion estimation algorithm under both periodic and general inputs.

关键词： system identification FIR system set-valued precise fusion estimation quasi-convex combination estimator

Distributed Recursive Projection Identification with Binary-Valued Observations

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Journal of Systems Science & Complexity 2021年第5期34卷 2048-2068页

作者： WANG Ying zhao yanlong ZHANG Ji-Feng Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China.

This paper investigates a distributed recursive projection identification problem with binaryvalued observations built on a sensor network,where each sensor in the sensor network measures partial information of the unknown parameter only,but each sensor is allowed to communicate with its neighbors.A distributed recursive projection algorithm is proposed based on a specific projection operator and a diffusion *** authors establish the upper bound of the accumulated regrets of the adaptive predictor without any requirement of excitation ***,the convergence of the algorithm is given under the bounded cooperative excitation condition,which is more general than the previously imposed independence or persistent excitations on the system regressors and maybe the weakest one under binary observations.A numerical example is supplied to demonstrate the theoretical results and the cooperative effect of the sensors,which shows that the whole network can still fulfill the estimation task through exchanging information between sensors even if any individual sensor cannot.

关键词： Adaptive predictor binary-valued observations cooperative excitations distributed parameter estimation

Consensus Control With a Constant Gain for Discrete-time Binary-valued Multi-agent Systems Based on a Projected Empirical Measure Method

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IEEE/CAA Journal of Automatica Sinica 2019年第4期6卷 1052-1059页

作者： Ting Wang Min Hu yanlong zhao IEEE the Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China the School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100149China

This paper studies the consensus control of multiagent systems with binary-valued *** algorithm alternating estimation and control is *** agent estimates the states of its neighbors based on a projected empirical measure method for a holding *** on the estimates,each agent designs the consensus control with a constant gain at some skipping *** states of the system are updated by the designed control,and the estimation and control design will be *** the estimation,the projected empirical measure method is proposed for the binary-valued *** algorithm can ensure the uniform boundedness of the estimates and the mean square error of the estimation is proved to be at the order of the reciprocal of the holding time(the same order as that in the case of accurate outputs).For the consensus control,a constant gain is designed instead of the stochastic approximation based gain in the existing literature for binary-valued ***,there is no need to make modification for control since the uniform boundedness of the estimates ensures the uniform boundedness of the agents’***,the systems updated by the designed control are proved to achieve consensus and the consensus speed is faster than that in the existing *** are given to demonstrate the theoretical results.

关键词： Binary-valued observations consensus control constant gain convergence rate multi-agent systems projected empirical measure method

Decision-implementation complexity of cooperative game systems

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Science China(Information Sciences) 2017年第11期60卷 180-197页

作者： Changbao XU yanlong zhao Ji-Feng ZHANG Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences

This paper focuses on the decision-implementation complexity(DIC) of cooperative games. The complexity of a control law is a fundamental issue in practice because it is closely related to control cost. First,we formulate implementation measures of strategies as system control protocols. Then, for a class of cooperative games, a decision-implementation system model is established, and an energy-based DIC index is given as the energy expectation under Nash equilibrium strategies. A definition of DIC is presented to describe the optimal values of the DIC index. DIC is calculated by the exhaust algorithm in some specific cases, whereas the one for general cases is too complex to be calculated. In order to obtain a general calculation method, the problem is described in the form of matrices; an analytical expression describing DIC is obtained by using the properties of matrix singular values. Furthermore, when only partial information of actions is shared among players, DIC can be reduced and an improved protocol can be designed as a two-phase protocol. A numerical example is given to show that the DIC obtained in this study is the same as the one obtained by the exhaust algorithm, and that the calculation complexity of the proposed algorithm is much lower.

关键词： cooperative game distributed protocol optimal control decision-implementation complexity two phase protocol

ADAPTIVE TRACKING OF A CLASS OF FIRST-ORDER SYSTEMS WITH BINARY-VALUED OBSERVATIONS AND FIXED THRESHOLDS

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Journal of Systems Science & Complexity 2012年第6期25卷 1041-1051页

作者： Jin GUO Ji-Feng ZHANG yanlong zhao Institute of Systems Science Academy of Mathematics and Systems ScienceChinese Academy of Sciences

This paper considers the adaptive tracking problem for a class of first-order systems with binary-valued observations generated via fixed thresholds. A recursive projection algorithm is proposed for parameter estimation based on the statistical properties of the system noise. Then, an adaptive control law is designed via the certainty equivalence principle. By use of the conditional expectations of the innovation and output prediction with respect to the estimates, the closed-loop system is shown to be stable and asymptotically optimal. Meanwhile, the parameter estimate is proved to be both almost surely and mean square convergent, and the convergence rate of the estimation error is also obtained. A numerical example is given to demonstrate the efficiency of the adaptive control law.

关键词： Adaptive control binary-valued observation optimal tracking parameter estimation,stochastic system.

Information Security Protocol Based System Identification with Binary-Valued Observations

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Journal of Systems Science & Complexity 2018年第4期31卷 946-963页

作者： XU Changbao zhao yanlong ZHANG Ji-Feng Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing 100049 China

Traditional control does not pay much attention to information security problems in system identification enough, which are important in practical applications. This paper focuses on the security problem of input information in a class of system identification problems with noise and binary-valued observations, presents a cryptography based security protocol, and improves it in the range of allowed errors. During solving the identification problem, the improved security protocol can ensure that the input information is not leaked, and thus, can deal with passive attacks effectively. Besides, a quantitative relationship among the input information, the public key in encryption and the number of partieipailts in the improved protocol is shown. Finally, the simulation results show that, the identification algorithm can still achieve the estimation accuracy by adding the improved security protocol. However, compared with the original identification algorithm, the time complexity of the algorithm with the improved security protocol increases.

关键词： Cryptography identification algorithm information security passive attacks security protocol time complexity

Adaptive control with saturation-constrainted observations for drag-free satellites——a set-valued identification approach

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Science China(Information Sciences) 2021年第10期64卷 182-193页

作者： Shuping TAN Jin GUO yanlong zhao Jifeng ZHANG Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering School of Automation and Electrical Engineering University of Science and Technology Beijing Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of Sciences

The high-accuracy drag-free control is one of the key technologies for gravity gradient *** the range of the gravity gradiometer is limited, the measurement is subject to the saturation *** paper introduces a design method of the adaptive drag-free control law by employing the set-valued identification approach. By inserting several thresholds in the constrained interval, the output observation is transformed into the set-valued information under different thresholds, based on which and the weighted optimization technique the identification algorithm for the unknown parameter is constructed. The adaptive drag-free control law is designed via the certainty equivalence principle. It is shown that the identification algorithm is strongly convergent and the convergence rate of the estimation error is obtained. The performance of the closed-loop system is analyzed, and the asymptotic optimality of the adaptive controller is proved. The numerical simulation is included to verify the effectiveness of the main results.

关键词： drag-free satellite saturation constraint adaptive control set-valued identification