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Real-time localisation of a low-cost mobile robot with poor ultrasonic data

CONTROL ENGINEERING PRACTICE 1998年第8期6卷 925-934页

作者： Hoppenot, P Colle, E CEMIF F-91020 Evry France

In order to open the field of autonomous mobile robotics to new applications such as the provision of assistance to disabled people, the research is being focused upon low-cost solutions. That implies the use of poor perception systems and low computing power. In such a context, the algorithms used have to be simple, if they are to be executed in real time, and proof against the weaknesses of the sensing systems. The localisation approach presented here is based on the fact that the higher the localisation algorithm speed is, the lower the error in the position and the orientation, due to the odometry. Any systematic errors in the relative localisation using odometry are corrected on-line by using a limited set of ultrasonic data. If a non-systematic error occurs, a more complex procedure is necessary. Both simulation and experimentation show that the systematic odometric errors become bounded, thanks to those algorithms. Moreover, they are robust to a high rate of false ultrasonic measures. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.

关键词： mobile robots medical robotics ultrasonic transducers range data least-squares algorithm localisation estimation localisation errors

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THE least-squares IDENTIFICATION OF FIR SYSTEMS SUBJECT TO WORST-CASE NOISE

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SYSTEMS & CONTROL LETTERS 1994年第5期23卷 329-338页

作者： AKCAY, H HJALMARSSON, H Department of Electrical Engineering Link?ping University S-58183 Link?ping Sweden

The least-squares identification of FIR systems is analyzed assuming that the noise is a bounded signal and the input signal is a pseudo-random binary sequence. A lower bound on the worst-case transfer function error shows that the least-square estimate of the transfer function diverges as the order of the FIR system is increased. This implies that, in the presence of the worst-case noise, the trade-off between the estimation error due to the disturbance and the bias error (due to unmodeled dynamics) is significantly different from the corresponding trade-off in the random error case: with a worst-case formulation, the model complexity should not increase indefinitely as the size of the data set increases.

关键词： WORST-CASE IDENTIFICATION FIR SYSTEMS least-squares algorithm

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Bias compensation-based parameter and state estimation for a class of time-delay non-linear state-space models

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IET CONTROL THEORY AND APPLICATIONS 2020年第15期14卷 2176-2185页

作者： Gu, Ya Zhu, Quanmin Nouri, Hassan Changshu Inst Technol Sch Elect Engn & Automat Changshu 215500 Jiangsu Peoples R China Univ West England Dept Engn Design & Math Bristol BS16 1QY Avon England

This study presents, based on bias compensation, an integrated parameter and state estimation algorithm for a class of time-delay non-linear systems which are described by canonical observable state-space model. In technical development, the state-space system model is transformed into an input-output representation/realisation by eliminating the state variables, which is accordingly used as a feasible identification model. With such an input-output structure, directly data measurable to accommodate the estimation bias, an augmented least-squares algorithm (by adding the bias correction terms into the estimates) is proposed for estimating the parameters and states interactively. Regarding the estimator properties, the proposed algorithm is proved unbiased. The simulation results show that the proposed algorithm has good performance in estimating the parameters of state-space systems.

关键词： observers state-space methods parameter estimation delays linear systems least squares approximations nonlinear control systems state estimation time-delay nonlinear state-space models bias compensation integrated parameter state estimation algorithm time-delay nonlinear systems canonical observable state-space model state-space system model state variables feasible identification model input-output structure estimation bias least-squares algorithm bias correction estimator properties state-space systems

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Vibration modelling with fast Gaussian wavelet algorithm

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ADVANCES IN ENGINEERING SOFTWARE 2002年第4期33卷 191-197页

作者： Luo, GY Osypiw, D Irle, M Buckinghamshire Chilterns Univ Coll Fac Technol High Wycombe HP11 1JZ Bucks England

Vibration signals are considered as nonstationary signals with transients, Conventional harmonic Fourier analysis finds it difficult to model the vibration signals. In this paper, a novel approach using the global Fourier transforms and local wavelet analysis is presented for vibration analysis and modelling. Time-frequency wavelet analysis has been proven a useful tool for the detection of vibration transients. However, current algorithms with discrete or continuous wavelet transforms for vibration analysis are either low resolution of features or very time consuming. We developed a fast Gaussian wavelet algorithm with very narrow band-pass filtering technique. The time-frequency maps with high frequency resolution enable us to observe the evolution in time of significant frequencies identified by global Fourier analysis, so that the transients and the regular signals can be distinguished. These regular significant frequencies are selected to be the basis of vibration modelling. The coefficients of the model are identified by a least-squares algorithm, which ensures that the error is minimised. To demonstrate this approach a machine spindle vibration signal is analysed. and the main features of the vibration signal are extracted, which are useful for system monitoring and further analysis. (C) 2002 Elsevier Science Ltd. All rights reserved.

关键词： vibration modelling Fourier transform wavelet algorithm time-frequency analysis least-squares algorithm

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Input estimation for nonlinear systems

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INVERSE PROBLEMS IN SCIENCE AND ENGINEERING 2010年第5期18卷 673-689页

作者： Lin, Dong-Cherng Diwan Coll Management Dept Ind Management Tainan 721 Taiwan

A novel input estimation inverse methodology of determining the time-varying exciting forces, named as the input, in a nonlinear system is presented. These forces are estimated from the measured dynamic response data of a nonlinear system using the approach. The algorithm includes the extended Kalman filter (KF) with a recursive estimator. The extended KF generates the residual innovation sequences. The estimator uses a least-squares algorithm, which employs the residual innovation sequences to evaluate the magnitudes and, therefore, the onset time histories of the exciting forces. Numerical simulations of a nonlinear system, an air-damped isolator model, demonstrate the accuracy of the proposed approach.

关键词： input estimation approach extended Kalman filter least-squares algorithm exciting force estimation

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DECENTRALIZED ADAPTIVE SYNCHRONIZATION OF A STOCHASTIC DISCRETE-TIME MULTIAGENT DYNAMIC MODEL

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SIAM JOURNAL ON CONTROL AND OPTIMIZATION 2009年第2期48卷 859-880页

作者： Ma, Hong-Bin Natl Univ Singapore Temasek Labs Singapore 117508 Singapore

A decentralized adaptive synchronization problem for a simple yet nontrivial discrete-time stochastic model of network dynamics is investigated, which also illustrates a general framework for a class of adaptive control problems for complex systems with uncertainties. To describe synchronization phenomena in noisy environments, several new definitions of synchronization for stochastic systems are given and applied in our model. In the framework proposed, we prove that in four different cases on local goals, including "deterministic tracking," "center-oriented tracking," " loose tracking," and " tight tracking," under mild conditions on noise sequence and communication limits, the agents in the considered model can achieve global synchronization in sense of mean by using local estimators and controllers based on a least-squares (LS) algorithm. These results show that agents in a complex system disturbed by noise with communication limits can autonomously achieve the global goal of synchronization by using local LS-based adaptive controllers while they are pursuing for their local goals.

关键词： adaptive control decentralized adaptive synchronization network dynamics least-squares algorithm complex system discrete-time stochastic model coupling uncertainties

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Learning Error Feedback Design of Direct Adaptive Fuzzy Control Systems

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2012年第3期20卷 536-545页

作者： Hsueh, Yao-Chu Su, Shun-Feng Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei 106 Taiwan

In the paper, based on the finite L-2-gain property, a way of estimating learning errors for direct adaptive fuzzy control systems is proposed, and then, a novel adaptive law with this estimated learning error is further proposed to improve the learning performance of the system in the sense of Lyapunov. In the literature, there is no direct way of estimating learning errors for direct adaptive fuzzy control systems. Based on the robust control approach proposed in our previous study, a way of estimating learning errors for direct adaptive fuzzy control can be derived, and as shown in our simulation, it can be found that such estimation is effective, as expected. It can be found that by incorporating this estimated learning error into the adaptive law, the proposed approach indeed can have much better learning performance. Besides, owing to good learning capability, the proposed control scheme can also have better tracking control performance. Simulation results clearly demonstrated the effectiveness of the proposed design.

关键词： Adaptive fuzzy control fuzzy control systems learning error feedback least-squares algorithm L-2-gain based control

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An effective online delay estimation method based on a simplified physical system model for real-time hybrid simulation

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SMART STRUCTURES AND SYSTEMS 2014年第6期14卷 1247-1267页

作者： Wang, Zhen Wu, Bin Bursi, Oreste S. Xu, Guoshan Ding, Yong Harbin Inst Technol Key Lab Struct Dynam Behav & Control Minist Educ Harbin 150090 Peoples R China Harbin Inst Technol Sch Civil Engn Harbin 150090 Peoples R China Univ Trento Dept Civil Environm & Mech Engn I-38123 Trento Italy

Real-Time Hybrid Simulation (RTHS) is a novel approach conceived to evaluate dynamic responses of structures with parts of a structure physically tested and the remainder parts numerically modelled. In RTHS, delay estimation is often a precondition of compensation;nonetheless, system delay may vary during testing Consequently, it is sometimes necessary to measure delay online Along these lines, this paper proposes an online delay estimation method using least-squares algorithm based on a simplified physical system model, i.e., a pure delay multiplied by a gain reflecting amplitude errors of physical system control. Advantages and disadvantages of different delay estimation methods based on this simplified model are firstly discussed. Subsequently, it introduces the least-squares algorithm in order to render the estimator based on Taylor series more practical yet effective. As a result, relevant parameter choice results to be quite easy. Finally in order to verify performance of the proposed method, numerical simulations and RTHS with a buckling-restrained brace specimen are carried out. Relevant results show that the proposed technique is endowed with good convergence speed and accuracy, even when measurement noises and amplitude errors of actuator control are present.

关键词： real-time hybrid simulation delay compensation online delay estimation least-squares algorithm

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Comparative study on several blind deconvolution algorithms applied to underwater image restoration

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OPTICAL REVIEW 2010年第3期17卷 123-129页

作者： Fan, Fan Yang, Kecheng Xia, Min Li, Wei Fu, Bo Zhang, Wei Huazhong Univ Sci & Technol Wuhan Natl Lab Optoelect Sch Optoelect Sci & Engn Wuhan 430074 Peoples R China

Although the use of blind deconvolution of image restoration is a widely known concept, only few reports have discussed in detail its application to solving problem of restoration of underwater range-gated laser images. A comparative study of underwater image restoration using the Richardson-Lucy algorithm, the least-squares algorithm, and the multiplicative iterative algorithm for blind deconvolution is presented. All the deconvolution approaches use denoised underwater images and Wells' small angle approximation theory of derived point spread function as the initial object and degradation guess, respectively. Owing the underwater no-reference imaging environment, image quality judgment based on the blur metric method is incorporated in our comparison to determine the appropriate deconvolution iteration number for each algorithm, which objectively evaluates the image restoration results. The performance of the three algorithms applied to underwater image restoration is discussed and reported.

关键词： underwater imaging image restoration blind deconvolution Richardson-Lucy algorithm least-squares algorithm multiplicative iterative algorithm

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Analysis of least-squares mixed finite element methods for nonlinear nonstationary convection-diffusion problems

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MATHEMATICS OF COMPUTATION 2000年第231期69卷 929-963页

作者： Yang, DP Shandong Univ Dept Math Jinan 250100 Peoples R China

Some least-squares mixed finite element methods for convection-diffusion problems, steady or nonstationary, are formulated, and convergence of these schemes is analyzed. The main results are that a new optimal a priori L-2 error estimate of a least-squares mixed finite element method for a steady convection-diffusion problem is developed and that four fully-discrete least-squares mixed finite element schemes for an initial-boundary value problem of a nonlinear nonstationary convection-diffusion equation are formulated. Also, some systematic theories on convergence of these schemes are established.

关键词： least-squares algorithm mixed finite element nonlinear convection-diffusion problem convergence analysis

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