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Efficient LQG control for wireless networked control systems without packet acknowledgement

INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2024年第4期55卷 571-589页

作者： Dong, Jianhuai Dong, Zhixuan Fujian Jiangxia Univ Sch Elect Informat Sci Fuzhou Peoples R China Fudan Univ Sch Microelect Shanghai Peoples R China

This paper studies the linear quadratic Gaussian (LQG) control problem for wireless networked control systems (WNCSs) without packet acknowledgement. In WNCSs, packets may be randomly lost in both control and observation channels, and non-acknowledgement (non-ACK) mechanisms (e.g. UDP-like protocols) are generally adopted to achieve real-time control and reduce energy consumption. For general non-ACK systems, it is well known that the optimal controller is not yet available, and the performance of existing suboptimal controllers is poor because they either adopt a fixed control law or rely on a poorly performing filter. By using a moment-preserving Gaussian approximation approach, an efficient filter is proposed to approximately estimate system states. Based on the approximate state estimates of the proposed filter, an approximate optimal controller with a time-varying control gain for WNCSs is further designed by using a dynamic programming approach. The proposed controller has excellent performance and becomes the optimal controller under special system parameters. Numerical simulations show the correctness and effectiveness of the obtained results.

关键词： Wireless networked control systems packet losses filtering algorithm stability LQG control

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FAST OPTIMIZATION OF THE EXACT LIKELIHOOD OF AR AND ARMA PROCESSES

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COMPUTATIONAL STATISTICS & DATA ANALYSIS 1994年第1期17卷 51-63页

作者： LUCENO, A UNIV WISCONSIN CTR QUAL & PROD IMPROVEMENTMADISONWI 53706

A convenient expression for the likelihood function of a stationary autoregressive-moving average process for a given series is obtained by modifying the algorithm of Ansley (Biometrika 66, 1979). The same modification is also advantageous in connection with the filtering algorithm of Pearlman (Biometrika 67, 1980) and Melard (Applied Statistics 33, 1984). This approach provides, not only the log-likelihood function, but also its gradient vector and its Hessian matrix with respect to the autoregressive parameters, using less operations than the direct application of the algorithms of Ansley or Pearlman. The new expression should be used when maximizing the log-likelihood function with a modified Newton-Raphson method, and it shows that it is advantageous to maximize first with respect to the set of autoregressive parameters conditioned to the current values of the set of moving-average parameters, and then to maximize with respect to the latter.

关键词： filtering algorithm MAXIMUM LIKELIHOOD ESTIMATES NEWTON-RAPHSON OPTIMIZATION TIME SERIES ESTIMATION

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Trajectory-based anomalous behaviour detection for intelligent traffic surveillance

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IET INTELLIGENT TRANSPORT SYSTEMS 2015年第8期9卷 810-816页

作者： Cai, Yingfeng Wang, Hai Chen, Xiaobo Jiang, Haobin Jiangsu Univ Automot Engn Res Inst Zhenjiang 212013 Peoples R China Jiangsu Univ Sch Automot & Traff Engn Zhenjiang 212013 Peoples R China

This study proposes an efficient anomalous behaviour detection framework using trajectory analysis. Such framework includes the trajectory pattern learning module and the online abnormal detection module. In the pattern learning module, a coarse-to-fine clustering strategy is utilised. Vehicle trajectories are coarsely grouped into coherent clusters according to the main flow direction (MFD) vectors followed by a three-stage filtering algorithm. Then a robust K-means clustering algorithm is used in each coarse cluster to get fine classification by which the outliers are distinguished. Finally, the hidden Markov model (HMM) is used to establish the path pattern within each cluster. In the online detection module, the new vehicle trajectory is compared against all the MFD distributions and the HMMs so that the coherence with common motion patterns can be evaluated. Besides that, a real-time abnormal detection method is proposed. The abnormal behaviour can be detected when happening. Experimental results illustrate that the detection rate of the proposed algorithm is close to the state-of-the-art abnormal event detection systems. In addition, the proposed system provides the lowest false detection rate among selected methods. It is suitable for intelligent surveillance applications.

关键词： intelligent transportation systems video surveillance learning (artificial intelligence) road vehicles hidden Markov models traffic engineering computing trajectory based anomalous behaviour detection intelligent traffic surveillance trajectory analysis trajectory pattern learning module online abnormal detection module coarse-to-fine clustering strategy vehicle trajectories main flow direction MFD vectors filtering algorithm robust K-means clustering algorithm coarse cluster hidden Markov model HMM path pattern online detection module vehicle trajectory MFD distributions motion patterns abnormal behaviour intelligent surveillance applications

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Model for accurate speed measurement using double-loop detectors

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2006年第4期55卷 1094-1101页

作者： Ki, Yong-Kul Baik, Doo-Kwon Korea Univ Dept Comp Sci & Engn Seoul 136701 South Korea

Vehicle speed is an important parameter in measurements of road traffic. At present, double-loop detectors are generally used for vehicular speed measurement. However, these detectors incur errors caused by scanning time, spacing between double-loops, irregular vehicle trajectories, and the presence of multiple vehicles in the detection zone. This paper suggests a new model that uses an error-filtering algorithm to improve the accuracy of speed measurements. In the field tests, all percent errors of the vehicular speeds measured by the proposed model were within the error tolerance limit (5%). Furthermore, the variance of percent errors was reduced. Therefore, it can be concluded that the proposed model significantly improves vehicle-speed-measuring accuracy.

关键词： double-loop detectors filtering algorithm irregular driving vehicles (IDVs) loop design multiple vehicles in the detection zone (MVDZs)

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Design of RLS-FIR filter using covariance information in linear continuous-time stochastic systems

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APPLIED MATHEMATICS AND COMPUTATION 2013年第17期219卷 9598-9608页

作者： Nakamori, Seiichi Kagoshima Univ Fac Educ Dept Technol Kagoshima 8900065 Japan

This paper addresses anew design method of recursive least-squares (RLS) and finite impulse response (FIR) filter, using covariance information, in linear continuous-time stochastic systems. The signal process is observed with additive white noise. It is assumed that the white observation noise is independent of the signal process. The auto-covariance function of the signal is expressed in the semi-degenerate kernel form. The RLS-FIR filter uses the following information: 1. The auto-covariance function of the signal expressed in the semi-degenerate kernel form. 2. The variance of the white observation noise process. 3. The observed values. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Continuous-time stochastic system FIR filter RLS filter Signal estimation filtering algorithm

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Design of RLS Wiener FIR filter using covariance information in linear discrete-time stochastic systems

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DIGITAL SIGNAL PROCESSING 2010年第5期20卷 1310-1329页

作者： Nakamori, S. Kagoshima Univ Fac Educ Dept Technol Kagoshima 8900065 Japan

This paper addresses a new design method of recursive least-squares (RLS) finite impulse response (FIR) filter, using the covariance information of the signal and observation noise, and RLS Wiener FIR filter in linear discrete-time stochastic systems. The signal is observed with additive white noise. The signal is assumed to be independent of the white observation noise. The RLS Wiener FIR filter uses the following information: (1) The observation matrix for the signal, (2) the system matrix for the state vector, (3) the variance of the state vector. (C) 2010 Elsevier Inc. All rights reserved.

关键词： Discrete-time stochastic system FIR filter RLS Wiener filter Signal estimation filtering algorithm

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State estimation of discrete-time systems with arbitrarily correlated noises

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INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING 2014年第10期28卷 949-970页

作者： Liu, Wei Henan Polytech Univ Sch Elect Engn & Automat Jiaozuo 454003 Peoples R China

In this paper, the state estimation problem for discrete-time systems is considered where the noises affecting such systems do not require any constraint condition for the correlation and distribution, that is, the noises can be arbitrarily correlated and arbitrarily distributed random vector. For this, two filtering algorithms based on the criterion of linear minimum mean-square error are proposed. The first algorithm is an optimal algorithm that can exactly compute the linear minimum mean-square error estimate of system states. The second algorithm is a suboptimal algorithm that is proposed to reduce the computation and storage load of the proposed optimal algorithm. Computer simulations are carried out to evaluate the performance of the proposed algorithms. Copyright (C) 2013 John Wiley & Sons, Ltd.

关键词： state estimation discrete time arbitrarily correlated noise filtering algorithm

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CROSS cyclic resource-constrained scheduling solver

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ARTIFICIAL INTELLIGENCE 2014年第1期206卷 25-52页

作者： Bonfietti, Alessio Lombardi, Michele Benini, Luca Milano, Michela Univ Bologna I-40136 Bologna Italy

Cyclic scheduling problems consist in ordering a set of activities executed indefinitely over time in a periodic fashion, subject to precedence and resource constraints. This class of problems has many applications in manufacturing, embedded systems and compiler design, production and chemical systems. This paper proposes a Constraint Programming approach for cyclic scheduling problems, based on modular arithmetic: in particular, we introduce a modular precedence constraint and a global cumulative constraint along with their filtering algorithms. We discuss two possible formulations. The first one (referred to as CROSS) models a pure cyclic scheduling problem and makes use of both our novel constraints. The second formulation (referred to as CROSS*) introduces a restrictive assumption to enable the use of classical resources constraints, but may incur a loss of solution quality. Many traditional approaches to cyclic scheduling operate by fixing the period value and then solving a linear problem in a generate-and-test fashion. Conversely, our technique is based on a non-linear model and tackles the problem as a whole: the period value is inferred from the scheduling decisions. Our approach has been tested on a number of non-trivial synthetic instances and on a set of realistic industrial instances. The method proved to effective in finding high quality solutions in a very short amount of time. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Cyclic scheduling problem Cumulative constraint filtering algorithm Constraint programming

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A practical comparison between filtering algorithms for enhanced RFID localization in smart environments

A practical comparison between filtering algorithms for enha...

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International Conference on Information, Intelligence, Systems and Applications

作者： Jean-Sébastien Bilodeau Dany Fortin-Simard Sebastien Gaboury Bruno Bouchard Abdenour Bouzouane LIARA Lab. Univ. du Quebec a Chicoutimi Chicoutimi QC Canada

ISBN: (纸本)9781467393126

The rapid adoption of wireless technologies has increased the interest of many laboratories about the field of Wireless Sensor Network (WSN) or the Radio-Frequency Identification (RFID) technology which has emerged as a winning combination for the implementation of an advanced assistance system within smart environments. To fulfill the important mission of a technological assistance, an algorithm first had to identify the ongoing activities of its user by tracking everyday life objects in real time using, for example, passive RFID tags. To increase the quality of information extracted from the objects localization by properly using the Received Signal Strength Indicator (RSSI), this paper explores Kalman filter, particle filter and few others filtering algorithm that enhances the tracking performance. It also discusses three of the most interesting methods that can be applied for the localization of objects in smart environments without requiring the installation of references tags everywhere. Finally, to increase the value, we include experiments that were conducted within a real smart home infrastructure to review the positive and negative elements of each method.

关键词： Smart environment Support service filtering algorithm Kalman Particle filter Objects localization Trilateration Pattern matching RFID Wireless sensor network Received Signal Strength

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Time-series unmanned aerial vehicle photogrammetry monitoring method without ground control points to measure mining subsidence

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JOURNAL OF APPLIED REMOTE SENSING 2021年第2期15卷

作者： Lian, Xugang Liu, Xiaoyu Ge, Linlin Hu, Haifeng Du, Zheyuan Wu, Yanru Taiyuan Univ Technol Sch Min Engn Taiyuan Peoples R China Univ New South Wales Sch Civil & Environm Engn Sydney NSW Australia

Surface subsidence and its secondary effects caused by underground coal mining continually threaten the safety and property of residents in mining areas. The commonly used total station and leveling approach is time-consuming and laborious, and the spatial range is limited. In this study, an FEIMA D2000 quadrotor unmanned aerial vehicle (UAV) was used to conduct 4-cm/pixel photogrammetry in four trial periods over a surface influence area (3.75 km(2)) of a working mine face. The performance comparison experiments from five point-cloud filtering algorithms in two sub-regions of the study area show that the ATIN algorithm provides the best filtering for this study area. Coal mining subsidence monitoring in mountainous area based on time-series UAV photogrammetry technology is proposed. Using this approach, the ATIN algorithm was used to filter the overall point cloud data in the study area to obtain the digital elevation model (DEM). The surface dynamic subsidence basin was determined with two phases of DEM subtraction. The results show that, compared with the measured leveling data in the field in the same period, the average root mean square error is 165 mm, and the maximum subsidence monitoring accuracy reaches 98%. (C) 2021 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： unmanned aerial vehicle photogrammetry subsidence monitoring filtering algorithm surface subsidence basin

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