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COMPARISON OF DAILY STREAMFLOW estimation TECHNIQUES

CANADIAN JOURNAL OF CIVIL ENGINEERING 1993年第3期20卷 480-489页

作者： BENNIS, S BRUNEAU, P HYDRO QUEBEC DIV HYDROLSERV HYDRAULMONTREAL H2L 4P5PQCANADA

The aim of the first part of our research, described in this paper, was to compare daily streamflow estimation techniques and models. A general application software named DebEst was developed for the purpose. The Saint-Francois River basin was used as a physical test area because of the availability of several hydrometric stations in this region. All techniques and models used gave good results. However, principal component analysis and multiple regression applied to deterministic models gave better results than ARIMA models. The least square recursive algorithm was more flexible than the other techniques, although discrepancies sometimes appeared because of incorrect weighting of measuring and modelling noise. Results improved significantly when seasonal models were used and when the variation of parameters was taken into account as a function of flow. All techniques described yielded autocorrelated residuals, at least for the first three time lags. The amplitude of the residual autocorrelation function was reduced by seasonal models although it still remained high. In the second part of our research, the Kalman filter technique will be used in conjunction with the methods described above to extract residual information and generate truly independent residuals.

关键词： MISSING STREAMFLOW RECORD PRINCIPAL COMPONENTS LEAST SQUARES recursive parameter estimation RESIDUAL AUTOCORRELATION

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A heuristic reference recursive recipe for adaptively tuning the Kalman filter statistics part-2: real data studies

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SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES 2016年第12期41卷 1491-1507页

作者： Mohan, M. Shyam Naik, Naren Gemson, R. M. O. Ananthasayanam, M. R. Indian Inst Technol Kanpur Uttar Pradesh India Indian Inst Technol Dept Elect Engn Kanpur Uttar Pradesh India Hindustan Aeronaut Ltd Bangalore Karnataka India Indian Inst Sci Dept Aerosp Engn Bangalore Karnataka India

In part-1 of this paper an adaptive filtering based on a reference recursive recipe (RRR) was developed and tested on a simulated dynamics of a spring, mass and damper with a weak nonlinear spring. In this paper the above recipe is applied to a more involved case of three sets of airplane data that have a larger number of state, measurements and unknown parameters. The flight tests cannot always be conducted in an ideal situation of the process noise and the measurement noises being white Gaussian as is generally assumed in the Kalman filter. The measurements may not be available with respect to the center of gravity and possess scale and bias factors, which will have to be modelled and estimated as well. The coupling between the longitudinal and lateral motion brings in added difficulty but makes the problem more interesting. It turns out that even a parameter that strongly affects the airplane dynamics is estimated which vary widely among the approaches. The RRR has been shown to be better than the earlier approaches in estimating the unknowns. The generalized cost functions that are introduced in the present work help identify definitive results from deceptive results.

关键词： Adaptive EKF longitudinal and lateral flight dynamics recursive parameter estimation Cramer Rao bound

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Closed-Loop System Identification with recursive Modifications of the Instrumental Variable Method

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INFORMATICA 2011年第2期22卷 165-176页

作者： Atanasov, Nasko Ichtev, Alexandar Tech Univ Varna Dept Automat Varna 9010 Bulgaria Tech Univ Sofia Dept Automat Sofia 1000 Bulgaria

The instrumental variable (IV) method is one of the most renowned methods for parameter estimation. Its bigger advantage is that it is applicable for open-loop as well as for closed-loop systems. The main difficulty in closed-loop identification is due to the correlation between the disturbances and the control signal induced by the loop. In order to overcome this problem, additional excitation signal is introduced. Non-recursive modifications of the instrumental variable method for closed-loop system identification on the base of a generalized IV method have been developed (Atanasov and Ichtev, 2009;Gilson and Van den Hof, 2001;Gilson and Van den Hof, 2003). In this paper, recursive algorithms for theses modifications are proposed and investigated. A simulation is carried out in order to illustrate the obtained results.

关键词： closed-loop system identification prediction error instrumental variable method recursive parameter estimation observations

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Modeling, Identification, and Predictive Control of a Driver Steering Assistance System

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IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS 2017年第5期47卷 700-710页

作者： Ercan, Ziya Carvalho, Ashwin Gokasan, Metin Borrelli, Francesco Istanbul Tech Univ Dept Control & Automat Engn TR-34467 Istanbul Turkey Univ Calif Berkeley Dept Mech Engn Berkeley CA 94720 USA

This paper presents the design of a driver steering assistance system, which provides a corrective torque in order to guide the driver. While designing such a system, it is important to consider the interactions since the driver modifies the transfer function from the control input to the output of interest during a shared steering task. The novelty of our approach lies in the formulation of the predictive controller, which employs amodel of the driver-in-the-loop steering dynamics, where an online parameter identification scheme is proposed to track the time-varying parameters of the process. An optimal guidance torque is calculated with respect to the level of interaction using the updated model. We validate the proposed approach by performing an experimental study with five participants in a guided lane, keeping task under different interaction behaviors of participants. The results show the system capability to adapt the control input based on the driver's acceptance on the torque intervention.

关键词： Haptic guidance systems human-machine interaction model predictive control (MPC) motor driven power steering system (MDPS) recursive parameter estimation

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Hidden Markov processes

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IEEE TRANSACTIONS ON INFORMATION THEORY 2002年第6期48卷 1518-1569页

作者： Ephraim, Y Merhav, N George Mason Univ Dept Elect & Comp Engn Fairfax VA 22030 USA Technion Israel Inst Technol Dept Elect Engn IL-32000 Haifa Israel

An overview of statistical and information-theoretic aspects of hidden Markov processes (HMPs) is presented. An HMP is a discrete-time finite-state homogeneous Markov chain observed through a discrete-time memoryless invariant channel. In recent years, the work of Baum and Petrie on finite-state finite-alphabet HMPs was expanded to HMPs with finite as well as continuous state spaces and a general alphabet. In particular, statistical properties and ergodic theorems for relative entropy densities of HMPs were developed. Consistency and asymptotic normality of the maximum-likelihood (ML) parameter estimator were proved under some mild conditions. Similar results were established for switching autoregressive processes. These processes generalize HMPs. New algorithms were developed for estimating the state, parameter, and order of an HMP, for universal coding and classification of HMPs, and for universal decoding of hidden Markov channels. These and other related topics are reviewed in this paper.

关键词： Baum-Petrie algorithm entropy ergodic theorems finite-state channels hidden Markov models identifiability Kalman filter maximum-likelihood (ML) estimation order estimation recursive parameter estimation switching autoregressive processes Ziv inequality

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Development of adaptive dual predictive control schemes based on Wiener-Hammerstein models

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JOURNAL OF PROCESS CONTROL 2022年 119卷 68-85页

作者： Kumar, Kunal Patwardhan, Sachin C. Noronha, Santosh Indian Inst Technol Syst & Control Engn Mumbai India Indian Inst Technol Dept Chem Engn Mumbai 400076 India

Adaptive MPC schemes often employ local linear approximation of the system dynamics, which may not be adequate to capture the dynamic behavior of systems exhibiting strongly nonlinear dynamics. In particular, it is challenging to control a system exhibiting input multiplicity behavior at its optimum operating point as the steady-state gain matrix can smoothly become singular at the optimum operating point. In this work, with the aim of controlling systems with fading memory that exhibit such strongly nonlinear dynamics, a novel adaptive dual nonlinear MPC (ADNMPC) formulation is developed based on discrete-time block-oriented models. The block-oriented models are parameterized using the generalized orthonormal basis filters (GOBF). The nonlinear black-box model is further used to formulate a stochastic optimal control problem. A deterministic approximation to the stochastic optimal control problem is then systematically derived. Subsequently, an ADNMPC scheme is developed using the deterministic approximation as a basis. The efficacy of the proposed approach is demonstrated by simulating the problem of controlling a continuously operated fermenter system at its optimum operating point. Analysis of the simulation study shows that in contrast to the conventional nonlinear MPC (NMPC), the proposed ADNMPC scheme injects perturbation to the process whenever a model update is needed while meeting the control objectives. Moreover, with reference to a non -adaptive NMPC controller, the proposed ADNMPC schemes achieve better servo control performance while controlling the fermenter at the singular optimum operating point. (c) 2022 Elsevier Ltd. All rights reserved.

关键词： Adaptive control Dual control Nonlinear model predictive control recursive parameter estimation Block-oriented model Orthogonal basis filters

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Robust recursive impedance estimation for automotive lithium-ion batteries

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JOURNAL OF POWER SOURCES 2016年 304卷 33-41页

作者： Fridholm, Bjorn Wik, Torsten Nilsson, Magnus Volvo Car Corp Gothenburg Sweden Viktoria Swedish ICT Gothenburg Sweden Chalmers Univ Technol Dept Signals & Syst Automat Control S-41296 Gothenburg Sweden

recursive algorithms, such as recursive least squares (RLS) or Kalman filters, are commonly used in battery management systems to estimate the electrical impedance of the battery cell. However, these algorithms can in some cases run into problems with bias and even divergence of the estimates. This article illuminates problems that can arise in the online estimation using recursive methods, and lists modifications to handle these issues. An algorithm is also proposed that estimates the impedance by separating the problem in two parts;one estimating the ohmic resistance with an RLS approach, and another one where the dynamic effects are estimated using an adaptive Kalman filter (AKF) that is novel in the battery field. The algorithm produces robust estimates of ohmic resistance and time constant of the battery cell in closed loop with SoC estimation, as demonstrated by both in simulations and with experimental data from a lithium-ion battery cell. (C) 2015 Elsevier B.V. All rights reserved.

关键词： recursive parameter estimation Kalman filter Adaptive estimation Battery impedance estimation Robustness Lithium-ion battery

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CDM-based design and performance evaluation of a robust AQM method for dynamic TCP/AQM networks

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COMPUTER COMMUNICATIONS 2009年第1期32卷 213-229页

作者： Bigdeli, N. Haeri, M. Sharif Univ Technol Dept Elect Engn Advance Control Syst Lab Tehran 111559363 Iran Imam Khomeini Int Univ Dept Elect Engn Linear Control Syst Lab Qazvin Iran

A new robust AQM strategy for dynamically varying TCP/AQM networks is proposed and its performance is investigated through computer simulations in MATLAB and ns-2 environments. The developed AQM is designed based on coefficient diagram method (CDM), which is a new indirect pole placement method that considers the speed, stability and robustness of the closed loop system in terms of time domain specifications. Simulation results indicate that the new method (CDM-AQM) performs very well for network variations both in topology and traffic. Besides, a new adaptive controller based on CDM as an AQM method is introduced. In the developed adaptive AQM (ACDM), the output feedback pole placement is implemented in an indirect model reference adaptive control (MRAC) scheme, in which the closed loop characteristic polynomial is determined by CDM and the system parameters are estimated using a modified recursive gradient method. This method preserves the existing features of CDM controller in the control of networks with unknown or time-varying parameters. Simulation results illustrate high capability of the controller in coping with the network variations. (C) 2008 Elsevier B.V. All rights reserved.

关键词： Active queue management Coefficient diagram method Model reference adaptive control recursive parameter estimation

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Modelling and prediction of machining errors using ARMAX and NARMAX structures

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APPLIED MATHEMATICAL MODELLING 2003年第8期27卷 611-627页

作者： Fung, EHK Wong, YK Ho, HF Mignolet, MP Hong Kong Polytech Univ Dept Mech Engn Kowloon Hong Kong Peoples R China Hong Kong Polytech Univ Dept Elect Engn Kowloon Hong Kong Peoples R China Arizona State Univ Dept Mech & Aerosp Engn Tempe AZ 85287 USA

Forecasting compensatory control, which was first proposed by Wu [ASME J. Eng. Ind. 99 (1977) 708], has been successfully employed to improve the accuracy of workpieces in various machining operations. This low-cost approach is based on on-line stochastic modelling and error: compensation. The degree of error improvement depends very much on the accuracy of the modelling technique, which can only be performed on-line in a real-time recursive manner. In this study, the effect of the control input (i.e. the cutting force) is considered in the development of the error models, and the formulation of recursive exogenous autoregressive moving average (ARMAX) models becomes necessary. The nonlinear ARMAX or NARMAX model is also used to represent this nonlinear process. ARMAX and NARMAX models of different autoregressive (AR), moving average (MA) and exogenous (X) orders are proposed and their identifications are based on the recursive extended least square (RELS) method and the neural network (NN) method, respectively. An analysis of the computational results has confirmed that the NARMAX model and the NN method are superior to the ARMAX model and the RELS method in forecasting future machining errors, as indicated by its higher combined coefficient of efficiency. (C) 2003 Elsevier Inc. All rights reserved.

关键词： ARMAX and NARMAX models recursive parameter estimation recursive extended least square neural networks machine error compensation forecasting

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RECENT RESULTS ON LEAST SQUARES-BASED ADAPTIVE-CONTROL OF LINEAR STOCHASTIC-SYSTEMS IN WHITE-NOISE

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SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES 1990年第4期15卷 397-404页

作者： WEI, R KUMAR, PR Coordinated Science Laboratory University of Illinois Urbana USA

Recently, progress has been made on establishing the stability and performance of linear stochastic systems when they are adaptively controlled in a certainty equivalent fashion using least squares-or extended least squares-based parameter estimates. Here we provide an overview of these results. We consider first the case of white gaussian noise, where the convergence of the parameter estimates can be established for generically all systems. Then we provide an account of the stability and performance of certainty equivalent controllers for which parameter convergence has been established. Next we turn to the white non-gaussian case, and obtain upper bounds for the parameter error and the normalized prediction error. Finally we exploit these bounds for the self-tuning regulator when "b0" is known and the delay equals one.

关键词： ADAPTIVE CONTROL SYSTEM IDENTIFICATION recursive parameter estimation LEAST-SQUARES ESTIMATES STOCHASTIC ADAPTIVE CONTROL

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