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A Hybrid Sliding Mode Control Scheme of Markovian Jump Systems via Transition Rates Optimal Design

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2021年第12期51卷 7752-7763页

作者： Cao, Zhiru Niu, Yugang Lam, James Song, Xiaoqi East China Univ Sci & Technol Key Lab Adv Control & Optimizat Chem Proc Minist Educ Shanghai 200237 Peoples R China Univ Hong Kong Dept Mech Engn Hong Kong Peoples R China

This article investigates the hybrid sliding mode control problem for the uncertain Markovian jump systems (MJSs) via the transition rates optimal design. The stability condition for the transition rates is first established to ensure the exponential mean-square (EMS) stability of the unforced uncertain MJSs. Then the hybrid design strategy on the sliding mode controller and transition rate matrix is presented to ensure the EMS stability of the controlled system. Moreover, the iterative optimization algorithms are developed to acquire the desirable transition rates, control gain, and decay rate sigma. Finally, some numerical simulation results are provided.

关键词： Hybrid design scheme iterative optimization algorithm Markovian jump systems (MJSs) sliding mode control (SMC) transition rate synthesis

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Robust stability analysis and controller synthesis for uncertain impulsive positive systems under L1-gain performance

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ISA TRANSACTIONS 2019年 93卷 55-69页

作者： Zhu, Baolong Zhang, Jie Suo, Mingliang Chen, Liangming Zhang, Yanquan Li, Shunli Qilu Univ Technol Sch Elect Engn & Automat Shandong Acad Sci Jinan 250353 Shandong Peoples R China Shandong Univ Dept Nutr Shandong Prov Hosp Jinan 250021 Shandong Peoples R China Shandong Univ Sch Publ Hlth Dept Biostat Jinan 250012 Shandong Peoples R China Beihang Univ Sch Reliabil & Syst Engn Beijing 100191 Peoples R China Harbin Inst Technol Sch Astronaut Harbin 150001 Heilongjiang Peoples R China

This paper addresses the problems of robust stability analysis and L-1-gain controller synthesis for uncertain impulsive positive systems. First, by employing the idea of impulse interval partitioning, an impulse-time-dependent discretized copositive Lyapunov function is proposed to analyze the robust stability and L-1-gain performance of the considered system without control inputs, and several stability conditions and L-1-gain criteria are respectively derived. Subsequently, a sufficient condition is formulated for the existence of state-feedback controllers with which not only the positivity and robust uniform asymptotic stability of the resulting closed-loop system are guaranteed, but also a prescribed L-1-gain performance is satisfied simultaneously. Furthermore, to make the controller synthesis problem numerically tractable, we propose an iterative convex optimization algorithm to compute the desired controller parameters. Finally, three numerical examples and two realistic examples are presented to show the effectiveness and applicability of the proposed methodology. (C) 2019 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Impulsive systems Positive systems Robust stability Stabilization Interval uncertainty L-1-gain iterative optimization algorithm

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Full Dynamic Compound Inverse Method: Extension to General and Rayleigh damping

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COMPUTATIONAL MECHANICS 2017年第4期59卷 539-553页

作者： Pioldi, Fabio Rizzi, Egidio Univ Bergamo Dipartimento Ingn & Sci Appl Viale G Marconi 5 I-24044 Dalmine BG Italy

The present paper takes from the original outputonly identification approach named Full Dynamic Compound Inverse Method (FDCIM), recently published on this journal by the authors, and proposes an innovative, much enhanced version, in the description of more general forms of structural damping, including for classically adopted Rayleigh damping. This has led to an extended FDCIM formulation, which offers superior performance, on all the targeted identification parameters, namely: modal properties, Rayleigh damping coefficients, structural features at the element-level and input seismic excitation time history. Synthetic earthquake-induced structural response signals are adopted as input channels for the FDCIM approach, towards comparison and validation. The identification algorithm is run first on a benchmark 3-storey shear-type frame, and then on a realistic 10-storey frame, also by considering noise added to the response signals. Consistency of the identification results is demonstrated, with definite superiority of this latter FDCIM proposal.

关键词： Full Dynamic Compound Inverse Method (FDCIM) iterative optimization algorithm Structural and modal dynamic identification Element-level system identification Estimated unknown seismic input

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Massively parallel processing approach to fractal image compression with near-optimal coefficient quantization

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JOURNAL OF SYSTEMS ARCHITECTURE 1999年第10期45卷 765-779页

作者： Palazzari, P Coli, M Lulli, G CR Casaccia ENEA HPCN Project I-00060 S Maria Di Galeria Italy Univ La Sapienza Dept Elect Engn I-00184 Rome Italy

In recent years Image Fractal Compression techniques (IFS) have gained more interest because of their capability to achieve high compression ratios while maintaining very good quality of the reconstructed image. The main drawback of such techniques is the very high computing time needed to determine the compressed code. In this work, after a brief description of IFS theory, we introduce the coefficient quantization problem, presenting two algorithms for its solution: the first one is based on Simulated Annealing while the second refers to a fast iterative algorithm. We discuss IFS parallel implementation at different level of granularity and we show that Massively Parallel Processing on SIMD machines is the best way to use all the large granularity parallelism offered by the problem. The results we present are achieved implementing the proposed algorithms for IFS compression and coefficient quantization on the MPP APE100/Quadrics machine. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： IFS coding simulated annealing quantization iterative optimization algorithm massively parallel processing

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A Full Dynamic Compound Inverse Method for output-only element-level system identification and input estimation from earthquake response signals

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COMPUTATIONAL MECHANICS 2016年第2期58卷 307-327页

作者： Pioldi, Fabio Rizzi, Egidio Univ Bergamo Dipartimento Ingn & Sci Appl Viale G Marconi 5 I-24044 Dalmine BG Italy

This paper proposes a new output-only element-level system identification and input estimation technique, towards the simultaneous identification of modal parameters, input excitation time history and structural features at the element-level by adopting earthquake-induced structural response signals. The method, named Full Dynamic Compound Inverse Method (FDCIM), releases strong assumptions of earlier element-level techniques, by working with a two-stage iterative algorithm. Jointly, a Statistical Average technique, a modification process and a parameter projection strategy are adopted at each stage to achieve stronger convergence for the identified estimates. The proposed method works in a deterministic way and is completely developed in State-Space form. Further, it does not require continuous- to discrete-time transformations and does not depend on initialization conditions. Synthetic earthquake-induced response signals from different shear-type buildings are generated to validate the implemented procedure, also with noise-corrupted cases. The achieved results provide a necessary condition to demonstrate the effectiveness of the proposed identification method.

关键词： Structural identification iterative optimization algorithm Modal dynamic identification Estimated unknown seismic input Element-level system identification

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Local PurTree Spectral Clustering for Massive Customer Transaction Data

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IEEE INTELLIGENT SYSTEMS 2017年第2期32卷 37-44页

作者： Chen, Xiaojun Peng, Si Huang, Joshua Zhexue Nie, Feiping Ming, Yong Shenzhen Univ Coll Comp Sci & Software Shenzhen Peoples R China

The clustering of customer transaction data is very important to retail and e-commerce companies. The authors propose a local PurTree spectral clustering algorithm for massive customer transaction data that uses a purchase tree to represent customer transaction data and a PurTree distance to compute the distance between two trees. The new method learns a data similarity matrix from the local distances and the level weights in the PurTree distance simultaneously. An iterative optimization algorithm is proposed to optimize the proposed model. The authors conducted experiments to compare their method with four commonly used clustering method for transaction data on six real-life datasets. The experimental results show that the new method outperformed other clustering algorithms.

关键词： Spectral clustering Clustering algorithms optimization Big Data Sparse matrices Data mining Genetic algorithms INSPEC: Controlled Indexing consumer behaviour iterative methods marketing data processing matrix algebra optimisation pattern clustering purchasing transaction processing trees (mathematics) INSPEC: Non-Controlled Indexing local PurTree spectral clustering massive customer transaction data purchase tree data similarity matrix local distances PurTree distance level weights iterative optimization algorithm customer purchase behaviors Author Keywords data mining customer segmentation transaction data spectral clustering intelligent systems

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Use of Modified Gaussian Beams to Optimize Shaped Reflectors

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IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS 2003年 2卷 14-17页

作者： Schott, P. Pascal, O. Lemaitre, F. Univ Paul Sabatier UPS F-31000 Toulouse France Off Natl Etud & Rech Aeronaut ONERA F-31000 Toulouse France Ecole Polytech Univ Nantes CNRS IRCCyN SETRA UMR 6597 F-44000 Nantes France UPS AD2M F-31500 Toulouse France Off Natl Etud & Rech Aerosp DEMR F-31500 Toulouse France

An efficient electromagnetic method for the optimization of shaped reflectors is presented. The repeated computation of scattering from reflector surface at each iteration, using the conventional numerical techniques of either physical optics (PO) or aperture integration (AI), usually makes iterative procedures very inefficient for the synthesis of large reflectors. Recently, an asymptotic Gaussian beam (GB) technique was developed and applied successfully to the fast analysis of reflector antennas of various shapes. This GB technique completely avoids numerical integration and thus makes the analysis very efficient. Our method uses the GB technique, coupled with a local description of the primary source and the reflector. The primary source radiation is expanded using a modified Gaussian beams basis. An antenna pattern calculation is demonstrated on a reflector that is described by local parameters in a novel way. By virtue of these local properties and the use of a steep step descent algorithm, a basic display of antenna pattern optimization is presented to illustrate the effectiveness of our method.

关键词： Antenna pattern antenna theory asymptotic Gaussian beam (GB) technique contoured beam applications GB approach Gaussian processes iterative optimization algorithm propagation shaped reflector antenna steepest descent method

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Matrix-Inverse-Free Deep Unfolding of the Weighted MMSE Beamforming algorithm

IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY

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IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY 2022年 3卷 65-81页

作者： Pellaco, Lissy Bengtsson, Mats Jalden, Joakim KTH Royal Inst Technol Sch Elect Engn & Comp Sci Div Informat Sci & Engn S-10044 Stockholm Sweden

Downlink beamforming is a key technology for cellular networks. However, computing beamformers that maximize the weighted sum rate (WSR) subject to a power constraint is an NP-hard problem. The popular weighted minimum mean square error (WMMSE) algorithm converges to a local optimum but still exhibits considerable complexity. In order to address this trade-off between complexity and performance, we propose to apply deep unfolding to the WMMSE algorithm for a MU-MISO downlink channel. The main idea consists of mapping a fixed number of iterations of the WMMSE into trainable neural network layers. However, the formulation of the WMMSE algorithm, as provided in Shi et al., involves matrix inversions, eigendecompositions, and bisection searches. These operations are hard to implement as standard network layers. Therefore, we present a variant of the WMMSE algorithm i) that circumvents these operations by applying a projected gradient descent and ii) that, as a result, involves only operations that can be efficiently computed in parallel on hardware platforms designed for deep learning. We demonstrate that our variant of the WMMSE algorithm convergences to a stationary point of the WSR maximization problem and we accelerate its convergence by incorporating Nesterov acceleration and a generalization thereof as learnable structures. By means of simulations, we show that the proposed network architecture i) performs on par with the WMMSE algorithm truncated to the same number of iterations, yet at a lower complexity, and ii) generalizes well to changes in the channel distribution.

关键词： Complexity theory Array signal processing Neural networks Downlink Approximation algorithms Network architecture Base stations Deep unfolding downlink beamforming iterative optimization algorithm weighted MMSE algorithm neural network

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Availability simulation and transfer prediction for bike sharing systems based on discrete event simulation

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SOCIO-ECONOMIC PLANNING SCIENCES 2024年 94卷

作者： Zhou, Yu Chen, Yang Liu, Shenyan Kou, Gang Inner Mongolia Univ Coll Econ & Management Hohhot 010021 Inner Mongolia Peoples R China Sichuan Univ Coll Architecture & Environm Chengdu 610000 Sichuan Peoples R China Xiangjiang Lab Changsha 410205 Hunan Peoples R China

To improve the operational efficiency of Bike Sharing Systems (BSSs), predicting users' real demand plays an essential role. Previous demand predictions have heavily relied on the historical rides (explicit demand) recorded in the BSS management information system. Since there are no bikes available for rent, users' unfulfilled ride expectations (implicit demand) cannot be captured in the system. This paper presents an approach for simulating station-level availability and predicting transfers for BSS. Firstly, the (s, S) inventory strategy combined with an iterative optimization-seeking algorithm to improve the existing simulation model. Then, the K-means method is used to cluster the similarity among stations. The transfer prediction uses source data to aid the learning of target data quickly. Finally, a real case study is conducted to validate the practicability. The simulation experiment indicates that it is possible to estimate the maximum percentage of underestimation of real demand at a station. Through regression analysis, this paper investigates the complex nonlinear relationship between the percentage underestimation of real demand and the easily accessible implicit demand influencing factors. In practical applications, managers can use this method to optimize the number of bikes placed for BSSs.

关键词： Implicit demand Availability simulation Bike sharing system Transfer prediction iterative optimization algorithm

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Analysis and optimization of Dynamic and Static Characteristics of the Compliant-Amplifying Mechanisms

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MICROMACHINES 2023年第8期14卷 1502-1502页

作者： Wang, Jin Jing, Zijian Xie, Zongliang Ning, Zongqi Qi, Bo Chinese Acad Sci Key Lab Opt Engn Chengdu 610209 Peoples R China Chinese Acad Sci Natl Key Lab Opt Field Manipulat Sci & Technol Chengdu 610209 Peoples R China Chinese Acad Sci Inst Opt & Elect Chengdu 610209 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

Compliant amplifying mechanisms are used widely in high-precision instruments driven by piezoelectric actuators, and the dynamic and static characteristics of these mechanisms are closely related to instrument performance. Although the majority of existing research has focused on analysis of their static characteristics, the dynamic characteristics of the mechanisms affect their response speeds directly. Therefore, this paper proposes a comprehensive theoretical model of compliant-amplifying mechanisms based on the multi-body system transfer matrix method to analyze the dynamic and static characteristics of these mechanisms. The effects of the main amplifying mechanism parameters on the displacement amplification ratio and the resonance frequency are analyzed comprehensively using the control variable method. An iterative optimization algorithm is also used to obtain specific parameters that meet the design requirements. Finally, simulation analyses and experimental verification tests are performed. The results indicate the feasibility of using the proposed theoretical compliant-amplifying mechanism model to describe the mechanism's dynamic and static characteristics, which represents a significant contribution to the design and optimization of compliant-amplifying mechanisms.

关键词： compliant-amplifying mechanisms multi-body system transfer matrix method displacement amplification ratio resonance frequency iterative optimization algorithm

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