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ADAPTIVE CONTROLLER FOR A TURBOGENERATOR SYSTEM

IEE PROCEEDINGS-D CONTROL THEORY AND APPLICATIONS 1988年第1期135卷 35-42页

作者： WU, QH HOGG, BW Department of Electrical & Electronic Engineering Queen's University of Belfast Belfast UK

The paper describes the derivation, design and evaluation of a parameter-adaptive integrated controller for a turbogenerator. The control strategy is to minimise the variances between the outputs of the turbogenerator and the outputs of a linear optimal predictor under all operating conditions. The design of the controller is based on an autoregressive moving-average model, and does not require any information about the parameters of the turbogenerator. A nonlinear feedback approach to the control strategy is achieved by a simple recursive algorithm, which can be implemented as an online real-time computer control scheme for a turbogenerator without persistent excitation of inputs. The performance of the adaptive controller depends on the successful design of the optimal predictor, which can be achieved by choosing suitable pole values. Results obtained using a detailed nonlinear simulation of a turbogenerator are presented.

关键词： Self-adjusting control systems Control of electric power systems linear optimal predictor nonlinear feedback turbogenerator a.c. machines parameter-adaptive integrated controller control system synthesis turbogenerators recursive algorithm autoregressive moving-average model time series online real-time computer control Control system analysis and synthesis methods adaptive controller Other topics in statistics adaptive control

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Asymptotic normality of the recursive M-estimators of the scale parameters

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ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS 2007年第2期59卷 367-384页

作者： Miao, Baiqi Wu, Yuehua Liu, Donghai Tong, Qian York Univ Dept Math & Stat Toronto ON M3J 1P3 Canada Univ Sci & Technol China Dept Stat & Finance Hefei 230026 Anhui Peoples R China

In this paper, the limit distributions of the recursive M-estimators of scatter parameters in a multivariate linear model setting are studied. Under some mild conditions, the asymptotic normality of the recursive M-esimtators is established. Some Monte Carlo simulation results are presented to illustrate the performance of the recursive M-estimators.

关键词： M-estimation multivariate linear regression model recursive algorithm robust estimation scatter parameter diffusion process strong consistency asymptotic normality

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Time delay Chebyshev functional link artificial neural network

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NEUROCOMPUTING 2019年 329卷 153-164页

作者： Lu, Lu Yu, Yi Yang, Xiaomin Wu, Wei Sichuan Univ Sch Elect & Informat Engn Chengdu 610065 Sichuan Peoples R China Southwest Univ Sci & Technol Sch Informat Engn Mianyang 621010 Peoples R China

In real applications, a time delay in the parameter update of the neural network is sometimes required. In this paper, motivated by the Chebyshev functional link artificial neural network (CFLANN), a new structure based on the time delay adaptation is developed for nonlinear system identification. Particularly, we present a new CFLANN-delayed recursive least square (CFLANN-DRLS), as an online learning algorithm for parameter adaptation in CFLANN. The CFLANN-DRLS algorithm exploits the time delayed error signal with the gain vector delayed by D cycles to form the weight increment term, which provides potential implementation in the filter with pipelined structure. However, it suffers from the instability problems under imperfect network delay estimate. To overcome this problem, we further propose a modified CFLANN-DRLS (CFLANN-MDRLS) algorithm by including a compensation term to the error signal. We analyze the stability and convergence of the proposed algorithm. Simulations in nonlinear system identification contexts reveal that the newly proposed CFLANN-MDRLS algorithm can effectively compensate the time delay of system and it is even superior to the algorithm without delay in some cases. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Functional link artificial neural network (FLANN) Chebyshev polynomials Time delay recursive algorithm Nonlinear system identification

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Internal field distribution of a radially inhomogeneous droplet illuminated by an arbitrary shaped beam

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JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER 2018年 210卷 19-34页

作者： Wang, Jia Jie Wriedt, Thomas Han, Yi Ping Maedler, Lutz Jiao, Yong Chang Xidian Univ Sch Phys & Optoelect Engn Xian 710071 Shaanxi Peoples R China Univ Bremen Dept Prod Engn Leibniz Inst Werkstofforientierte Technol IWT Badgasteiner Str 3 D-28359 Bremen Germany Xidian Univ Sch Elect Engn Xian 710071 Shaanxi Peoples R China

Light scattering of a radially inhomogeneous droplet, which is modeled by a multilayered sphere, is investigated within the framework of Generalized Lorenz-Mie Theory (GLMT), with particular efforts devoted to the analysis of the internal field distribution in the cases of shaped beam illumination. To circumvent numerical difficulties in the computation of internal field for an absorbing/non-absorbing droplet with pretty large size parameter, a recursive algorithm is proposed by reformulation of the equations for the expansion coefficients. Two approaches are proposed for the prediction of the internal field distribution, namely a rigorous method and an approximation method. The developed computer code is tested to be stable in a wide range of size parameters. Numerical computations are implemented to simulate the internal field distributions of a radially inhomogeneous droplet illuminated by a focused Gaussian beam. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Mie scattering Multilayered sphere Internal field Shaped laser beam recursive algorithm

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Numerical stability of fast computation algorithms of Zernike moments

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APPLIED MATHEMATICS AND COMPUTATION 2008年第1期195卷 326-345页

作者： Papakostas, G. A. Boutalis, Y. S. Papaodysseus, C. N. Fragoulis, D. K. Democritus Univ Thrace Dept Elect & Comp Engn GR-67100 Xanthi Greece Natl Tech Univ Athens Sch Elect & Comp Engn GR-15773 Athens Greece

A detailed, comparative study of the numerical stability of the recursive algorithms, widely used to calculate the Zernike moments of an image, is presented in this paper. While many papers, introducing fast algorithms for the computation of Zernike moments have been presented in the literature, there is not any work studying the numerical behaviour of these methods. These algorithms have been in the past compared to each other only according to their computational complexity, without been given the appropriate attention, as far as their numerical stability is concerned, being the most significant part of the algorithms' reliability. The present contribution attempts to fill this gap in the literature, since it mainly demonstrates that the usefulness of a recursive algorithm is defined not only by its low computational complexity, but most of all by its numerical robustness. This paper exhaustively compares some well known recursive algorithms for the computation of Zernike moments and sets the appropriate conditions in which each algorithm may fall in an unstable state. The experiments show that any of these algorithms can be unstable under some conditions and thus the need to develop more stable algorithms is of major importance. (C) 2007 Elsevier Inc. All rights reserved.

关键词： Zernike moments recursive algorithm finite precision error numerical stability

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A recursive APPROACH FOR ENUMERATING MINIMAL CUTSETS IN A NETWORK

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IEEE TRANSACTIONS ON RELIABILITY 1994年第3期43卷 383-388页

作者： YAN, L TABA, HA LANDERS, TL University of Arkansas Fayetteville USA

This paper presents a new recursive labeling algorithm for determining all minimal cutsets in a directed network, using an approach adapted from dynamic programming algorithms for the classical shortest route problem. The algorithm produces all minimal cutsets, and uses comparison logic to eliminate any redundant cutsets. Computational experience shows that: 1) the time per cutset varies linearly with the number of nodes but decreases exponentially with the density of the graph;and 2) whereas the algorithm's performance with regard to 'change in the time per cutset vs the number of nodes' is similar to other algorithms, it appears to exhibit superior performance where the time/cutset is compared to the density of the graph.

关键词： DIRECTED NETWORK UNDIRECTED NETWORK CUTSET recursive algorithm DYNAMIC PROGRAMMING

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A dynamic unreliability assessment and optimal maintenance strategies for multistate weighted k-out-of-n:F systems

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APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY 2016年第4期32卷 485-493页

作者： Khorshidi, Hadi Akbarzade Gunawan, Indra Ibrahim, Yousef Monash Univ Fac Sci Melbourne Vic Australia Univ Adelaide Entrepreneurship Commercialisat & Innovat Ctr Adelaide SA Australia Federat Univ Australia Sch Engn & Informat Technol Churchill Vic Australia

In this paper, a dynamic evaluation of the multistate weighted k-out-of-n:F system is presented in an unreliability viewpoint. The expected failure cost of components is used as an unreliability index. Using failure cost provides an opportunity to employ financial concepts in system unreliability estimation. Hence, system unreliability and system cost can be compared easily in order to making decision. The components' probabilities are computed over time to model the dynamic behavior of the system. The whole system has been assessed by recursive algorithm approach. As a result, a bi-objective optimization model can be developed to find optimal decisions on maintenance strategies. Finally, the application of the proposed model is investigated via a transportation system case. Matlab programming is developed for the case, and genetic algorithm is used to solve the optimization model. Copyright (c) 2016 John Wiley & Sons, Ltd.

关键词： multistate weighted k-out-of-n:F system dynamic assessment unreliability evaluation bi-objective optimization failure cost recursive algorithm

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recursive minimum component algorithms for parameter estimation of dynamic systems

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NEUROCOMPUTING 2016年第0期186卷 251-257页

作者： Li, Huxiong Mu, Bingxian Zuo, Lei Zhejiang Univ Media & Commun Sch New Media Xiasha Higher Educ Zone 998 Xueyuan St Hangzhou 310018 Peoples R China Univ Victoria Dept Mech Engn Stn CSC POB 1700 Victoria BC V8W 2Y2 Canada Northwestern Polytech Univ Sch Marine Sci & Technol 127 West Youyi Rd Xian 710072 Peoples R China

Minimum component analysis is an elegant and promising approach to system identification. This paper focuses on developing related recursive algorithms. Two algorithms are presented. In the first approach, rank-one modification is used to get an accurate and quickly convergent algorithm. However, its drawback is low computational efficiency. Therefore, the second algorithm is proposed to realize faster computation. The simulation results verify the effectiveness of both algorithms. (C) 2016 Published by Elsevier B.V.

关键词： System identification Minimum component analysis recursive algorithm

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A two-stage Bayesian framework for rapid dynamics identification in industrial robots

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 2024年第16期34卷 10867-10890页

作者： Qiao, Xuechun Yang, Liren Liu, Xing Wang, Yasen Cheng, Cheng Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Mech Sci & Engn Wuhan Peoples R China MOE Engn Res Ctr Autonomous Intelligent Unmanned Wuhan Peoples R China

Accurate dynamic models that update in real-time are vital for industrial robots to adapt flexibly and robustly to evolving environments and tasks, enabling precise model-based control, motion planning and disturbance estimation. However, the identification of a dynamic robot model involves multiple challenges. First, existing friction models cannot accurately characterize torque variance during prolonged robot operations. Second, traditional offline identification methods such as the least squares (LS) method, suffer from over-fitting when the inertia parameters are unknown a priori. Furthermore, existing online identification approaches, such as sliding LS, fail to meet the accuracy and real-time requirements of industrial robots. To address these challenges, this article proposes a two-stage Bayesian framework for rapid offline identification and online updating of industrial robot dynamics. In the offline stage, we developed a recursive sparse Bayesian learning (RSBL) method to select the dominant parameters and discover a thermal-related nonlinear dynamic friction model from data, which was then used to find a sparser and simpler inertia model. The obtained friction and inertia models were used as prior knowledge for online updating. The RSBL method significantly reduces the computational complexity and runtime, while it also accelerates online model updating. Experimental results for a 6-DOF medium-load robot validate dual offline improvements in prediction accuracy and model sparsity, along with higher online prediction accuracy and shorter computational time.

关键词： dynamic model identification friction model industrial robot recursive algorithm sparse Bayesian learning

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recursive kinematics and dynamics for parallel structured closed-loop multibody systems

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MECHANICS OF STRUCTURES AND MACHINES 2001年第2期29卷 143-175页

作者： Saha, SK Schiehlen, WO Indian Inst Technol Delhi Dept Mech Engn New Delhi 110016 India Univ Stuttgart Inst Mech B D-7000 Stuttgart Germany

A kinematic formulation for the parallel structured closed-loop multibody mechanical systems, such as Stewart Platform and Hexapod machine tools, is presented in this paper, which is recursive in nature. This also leads to the minimum order representation of the dynamic equations of motion. The recursive algorithms are known for their efficiency when a system is large. They also provide many physical interpretations. On the other hand, the minimum order dynamic equations of motion are desired in control and simulation. For the latter a minimum set of dynamic equations of motion leads to a numerically stable integration algorithm that does not violate the kinematic constraints. Two recursive algorithms, one for the inverse and another for the forward dynamics, are proposed. The overall complexity of either problem is O(n) + nO(m), where n and in are the number of legs and the total number of rigid bodies in each leg, respectively. Hence the proposed formulation exploits the advantages of both minimum order representation and recursive algorithms, which earlier were available only for the open-loop systems such as serial manipulators. The method is illustrated with three examples: a one-degree-of-freedom (DOF) slider-crank mechanism, four-bar linkage, and a two-DOF five-bar planar parallel manipulator.

关键词： parallel structure closed loop dynamics recursive algorithm

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