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Robust delay-dependent LPV synthesis for blood pressure control with real-time Bayesian parameter estimation

IET CONTROL THEORY AND APPLICATIONS 2020年第10期14卷 1334-1345页

作者： Tasoujian, Shahin Salavati, Saeed Franchek, Matthew A. Grigoriadis, Karolos M. Univ Houston Dept Mech Engn Houston TX 77204 USA

Mean arterial blood pressure (MAP) dynamics estimation and its automated regulation could benefit the clinical resuscitation of patients in critical conditions. To address the variability and complexity of the MAP response of patients to vasoactive drug infusion, a parameter-varying model with a varying delay is considered to describe such dynamics. The estimation of the varying parameters and delay is performed via a Bayesian-based multiple-model square-root cubature Kalman filtering (MMSRCKF) approach. The estimation results substantiate the effectiveness of the utilized identification method using experimental data. Next, an automated drug delivery scheme to regulate the real-time MAP response of patients is developed via time-delay linear parameter-varying (LPV) control techniques. To this end, a gain-scheduled outputfeedback LPV controller is designed to track a desired reference MAP target and guarantee robustness against norm-bounded uncertainties and disturbances in terms of the closed-loop system induced L-2-norm. Parameter-dependent Lyapunov-Krasovskii functionals (LKFs) are used to derive sufficient conditions in the convex linear matrix inequality (LMI) constraint framework for the robust stabilization of LPV systems with arbitrarily varying delay. Finally, to evaluate the performance of the proposed MAP regulation approach, closed-loop simulations are conducted, and the results confirm the effectiveness of the proposed method against various simulated clinical scenarios.

关键词： closed loop systems pressure control time-varying systems robust control control system synthesis feedback parameter estimation Kalman filters delays Lyapunov methods uncertain systems linear systems linear matrix inequalities blood pressure measurement medical control systems robust delay-dependent LPV synthesis blood pressure control real-time Bayesian parameter estimation mean arterial blood pressure dynamics estimation automated regulation critical conditions vasoactive drug infusion parameter-varying model MAP dynamics drugs varying parameters Bayesian-based multiple-model square-root random-walk dynamics identification method estimation algorithm automated drug delivery scheme time-delay linear parameter-varying control techniques LPV gain-scheduled output-feedback controller MAP response performance requirements parameter-dependent Lyapunov-Krasovskii functionals general LPV system arbitrarily varying time delay MAP regulation approach control method

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Accelerated adaptive super twisting sliding mode observer-based drive shaft torque estimation for electric vehicle with automated manual transmission

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IET INTELLIGENT TRANSPORT SYSTEMS 2019年第1期13卷 160-167页

作者： Lin, Cheng Sun, Shengxiong Yi, Jiang Walker, Paul Zhang, Nong Beijing Inst Technol Sch Mech Engn 5 South Zhongguancun St Beijing Peoples R China Univ Technol Sydney Fac Engn & IT 15 Broadway Sydney NSW Australia

The suddenly released torque that accumulated in the elastic drive shaft will bring torsional vibration and jerking feel at the shifting moment. A novel sliding mode observer is proposed to estimate the torque in drive shaft for a motor-transmission integrated powertrain system. Non-linear external characteristics of a driving motor and non-linear drag torque are considered in the electric powertrain system. In order to attenuate the chatting problem, the second-order super twisting sliding mode algorithm with an adaptive gain is adopted. Furthermore, a term system damping' is introduced to accelerate the estimation error convergence. The proposed estimation algorithm is tested on test rig for typical operating conditions. The results show that the torque in drive shaft can be estimated satisfactorily and the tracking error converges to 0 in a short time.

关键词： power transmission (mechanical) variable structure systems observers torque control vibrations shafts electric vehicles adaptive control estimation theory size 0 0 A chatting problem test rig system damping adaptive gain nonlinear drag torqu nonlinear external characteristics torque estimation shifting moment estimation algorithm estimation error convergence second-order super twisting sliding mode algorithm electric powertrain system driving motor motor-transmission integrated powertrain system jerking feel torsional vibration elastic drive shaft automated manual transmission electric vehicle accelerated adaptive super twisting sliding mode observer-based drive shaft torque estimation

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Fuzzy controller design by means of genetic optimization and NFN-based estimation technique

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INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 2004年第3期2卷 362-373页

作者： Oh, SK Rho, SB Kim, HK Wonkwang Univ Dept Elect Elect & Informat Engn Iksan 570749 Chonbuk South Korea Univ Suwon Dept Elect Engn Hwanseong 445743 Gyeonggi Do South Korea

In this study, we introduce a noble neurogenetic approach to the design of the fuzzy controller. The design procedure dwells on the use of Computational Intelligence (CI), namely genetic algorithms and neurofuzzy networks (NFN). The crux of the design methodology is based on the selection and determination of optimal values of the scaling factors of the fuzzy controllers, which are essential to the entire optimization process. First, tuning of the scaling factors of the fuzzy controller is carried out, and then the development of a nonlinear mapping for the scaling factors is realized by using GA based NFN. The developed approach is applied to an inverted pendulum nonlinear system where we show the results of comprehensive numerical studies and carry out a detailed comparative analysis.

关键词： Computational Intelligence (CI) estimation algorithm fuzzy controller genetic algorithms neurofuzzy networks (NFN) optimization process scaling factors

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Motor threshold in transcranial magnetic stimulation:: comparison of three estimation methods

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NEUROPHYSIOLOGIE CLINIQUE-CLINICAL NEUROPHYSIOLOGY 2006年第1期36卷 1-7页

作者： Tranulis, C Guéguen, B Pham-Scottez, A Vacheron, MN Cabelguen, G Costantini, A Valero, G Gatinovski, A Ctr Hosp St Anne Serv Neurophysiol Clin F-75014 Paris France Ctr Hosp St Anne Serv Hosp Univ Sante Mentale & Therapeut Pr H Loo F-75014 Paris France Ctr Hosp St Anne Clin Malad Mentales & Encephale F-75014 Paris France Ctr Hosp St Anne Psychiat Serv Secteur 13 F-75014 Paris France

Aims. - Motor threshold (MT) is an important parameter for the practice of transcranial magnetic stimulation. Our goat was to compare three methods to estimate MT in a clinical setting. Methods. - Comparison of three MT estimation algorithms: 1) the Rossini-Rothwell method consists in lowering stimulus intensity until only five positive responses out of 10 trials are recorded, defining MT;2) the Mills-Nithi method considers the MT as the mean of an upper threshold (10 positive out of 10 trials) and a lower threshold (0 out of 10 trials);3) the supervised parametric method estimates the MT by fitting (mathematically and graphically) a sigmoid function on raw data obtained by stimulation at variable intensities. Six MT estimations (two per method) were recorded in a single session in 10 healthy subjects. Results. - The within-subject variation of MT (expressed as % of the mean MT +/- standard deviation) during a single session was of 8.5 +/- 7.2% for the Rossini-Rothwell method, 8.7 +/- 5.7% for the Mills-Nithi method and 9.5 +/- 4.0% for the supervised parametric method. No significant differences in variability of MT estimation were found between the methods, but the Rossini-Rothwell method was significantly shorter (half the number of stimuli compared to the two other methods). Conclusion. - In our setting, Rossini-Rothwelt method was superior to the two other methods. The variability of MT estimation measured in our study is important, yet acceptable for clinical applications. However, this variability can be a source of considerable errors in excitability studies and should be a focus of future research. (c) 2006 Elsevier SAS. All rights reserved.

关键词： motor threshold transcranial magnetic stimulation estimation algorithm Rossini-Rothwell algorithm Mitts-Nithi algorithm

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estimation of Quasiperiodic Texture Lattice Node Coordinates with the Use of Two-Dimensional Local Spectra Characteristics

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OPTOELECTRONICS INSTRUMENTATION AND DATA PROCESSING 2016年第3期52卷 217-222页

作者： Gruzman, I. S. Petrova, K. Yu. Novosibirsk State Tech Univ Pr Karla Marksa 20 Novosibirsk 630073 Russia Novosibirsk State Tech Univ Ul Dvintsev 12Korp 1 Moscow 127018 Russia Dept Samsung Elect Co Ltd Ul Dvintsev 12Korp 1 Moscow 127018 Russia

An algorithm is proposed for estimating the coordinates of nodes of deformed lattices of quasiperiodic textures without preliminary detection of typical texture elements. Examples are provided to demonstrate high accu... 详细信息

关键词： estimation algorithm quasiperiodic texture lattice nodes texture element local two-dimensional spectrum Bravais lattice

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Towards robust sensor fusion for state estimation in airborne applications using GNSS and IMU

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IFAC-PapersOnLine 2017年第1期50卷 13264-13269页

作者： Girrbach, Fabian Hol, Jeroen D. Bellusci, Giovanni Diehl, Moritz are with Xsens Technologies B.V. EnschedePR7521 Netherlands Georges-Koehler-Allee 102 Freiburg79110 Germany

Precise estimation of position, velocity, and orientation is crucial for robust control in airborne applications such as the fast maneuvering power kites for airborne wind energy generators. In this paper we present a sensor fusion approach for the measurements of a global navigation satellite system receiver and an inertial measurement unit, using methods from direct optimal control. The resulting optimization problem is based on the minimization of the weighted squared residuals between model predictions and measurements and solved using a direct collocation discretization strategy. The framework allows the formulation of a batch and filter estimator which include beside the estimation of the navigational states the identification of sensor parameters such as biases of the inertial measurement unit. The results of the algorithms are evaluated against a reference trajectory of a maneuvering single propeller aircraft and achieve root mean squared errors below 1 m in position, 0.4 ms-1in velocity, and 0.5 deg in orientation for the batch estimator. The contribution in this paper is a first step towards the required robustness of state estimation for airborne applications. © 2017

关键词： Parameter estimation Air navigation Collision avoidance Crystal orientation Fighter aircraft Global positioning system Mean square error Navigation Robust control State estimation Tracking (position) Wind power estimation algorithm Global Navigation Satellite Systems Inertial measurement unit Inertial navigations Moving horizon estimation Optimal estimations Reference trajectories Root mean squared errors

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Identifiability and Parameter estimation of Linear Continuous-time Systems under Irregular and Random Sampling

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IFAC-PapersOnLine 2015年第28期48卷 332-337页

作者： Mu, Biqiang Guo, Jin Wang, Le Yi Yin, George Xu, Lijian Zheng, Wei Xing Key Laboratory of Systems and Control Chinese Academy of Sciences Beijing100190 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Department of Electrical and Computer Engineering Wayne State University DetroitMI48202 United States Department of Mathematics Wayne State University DetroitMI48202 United States Department of Electrical and Computer Engineering Technology Farmingdale State College State University of New York FarmingdaleNY11735 United States School of Computing Engineering and Mathematics University of Western Sydney PenrithNSW2751 Australia

This paper considers the problem of identifiability and parameter estimation of single-input-single-output, linear, time-invariant, stable, continuous-time systems under irregular and random sampling schemes. Conditions for system identifiability are established under inputs of exponential polynomial types and a tight bound on sampling density. Identification algorithms of Gauss-Newton iterative types are developed to generate convergent estimate sequences. When the sampled output is corrupted by observation noises, input design, sampling times, and convergent algorithms are intertwined. Persistent excitation (PE) conditions for strongly convergent algorithms are derived. Unlike the traditional identification, the PE conditions under irregular and random sampling involve both sampling times and input values. Under the given PE conditions, iterative and recursive algorithms are developed to estimate the original continuous-time system parameters. The corresponding convergence results are obtained. Several simulation examples are displayed to verify the theoretical results. © 2015

关键词： Continuous time systems Iterative methods Lyapunov methods Nonlinear control systems Parameter estimation Sampling convergence and asymptotical normality estimation algorithm Identifiability Irregular sampling Linear continuous time system Non linear least squares

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Inertia estimation of Power Grid with VSC-MTDC System

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IFAC-PapersOnLine 2018年第28期51卷 197-202页

作者： Hu, Liujun Li, Yong Wang, Weiyu Tan, Yi Cao, Yijia Lee, Kwang Y. College of Electrical and Information Engineering Hunan University Changsha410000 China Department of Electrical and Computer Engineering Baylor University WacoTX76798-7356 United States

The increase of renewable energy generations and HVDC links with low or zero inertia will affect the dynamic behavior of power systems and stability margins. The inertia characteristics of power system is a critical factor for the analysis of the system dynamic stability when subjected to disturbances. To meet the increasing integration level of the renewable energy resources in the future, this paper proposes an inertia estimation algorithm to analyze both the regional and global inertia characteristics of power systems. It is found that the inertia estimation results are highly related to several factors, such as the grid structure, the inertia time constant of synchronous generators and the grid-interface location of the electronics, which also reveal the impact of a multi-terminal DC (MTDC) system connection. The effectiveness of the proposed method is verified and demonstrated for three networks by the simulations in the DigSILENT/PowerFactory environment. © 2018

关键词： Electric power transmission networks Phasor measurement units Renewable energy resources System stability estimation algorithm estimation results Frequency deviation Inertia Integration levels Power system stability Renewable energy generation Renewable generation

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To the Problem of Adaptive Guaranteed estimation

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IFAC-PapersOnLine 2018年第32期51卷 717-722页

作者： Khadanovich, Dina V. Shiryaev, Vladimir I. Chelyabinsk Russia Chelyabinsk Russia

The article deals with linear dynamical system state estimation problem under uncertainty when disturbance and measurement error statistics are unknown but the sets of their possible values are available. The approach to adaptive algorithm development of guaranteed estimation is proposed. The approach is based on the processing of innovation sequence values in the Kalman filter under conditions of a small number of available measurements. The Kalman filter implementation is performed for measurement data preprocessing the result of which is the mathematical model development and refining the estimates of unknown measurement errors. © 2018

关键词： Kalman filters Adaptive algorithms Adaptive filtering Adaptive filters Dynamical systems Error statistics estimation Forecasting Linear control systems Mathematical models Measurement errors Uncertainty analysis algorithm development estimation algorithm estimation problem Guaranteed estimation Innovation sequence Linear dynamical systems Measurement data Measurement Noise

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Effects of Differential Pressure Measurement Characteristics on Low Pressure-EGR estimation Error in Si-Engines

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IFAC-PapersOnLine 2016年第11期49卷 722-729页

作者： Kiwan, Rani Stefanopoulou, Anna G. Martz, Jason Surnilla, Gopichandra Ali, Imtiaz Joseph Styles, Daniel University of Michigan Ann ArborMI4-8109 United States Ford Motor Company DearbornMI United States

With proper control, cooled LP-EGR can be used for knock mitigation in SI engines, enabling fuel economy improvements through more optimal combustion phasing and lower fuel-enrichment at high loads. In addition, it can allow more aggressive downsizing and boosting. Due to the inherent pressure pulsations and low differential pressures across the EGR valve, however, estimating the LP-EGR within the inducted charge can be problematic. The accuracy of this estimation, based on a pressure differential (ΔP) measurement and the steady compressible flow orifice equation is investigated for various ΔP sensor response speeds and sampling rates using a GT-Power model of a modified Ford 1.6 L EcoBoost engine. In addition, an unsteady compressible flow orifice equation that accounts for flow inertia is derived and used to estimate LP-EGR for the case of a fast response ΔP sensor. Errors in the estimated EGR percentage using the steady compressible orifice equation with averaged ΔP measurement can be as high as 30%, and errors within ±1% require a ΔP of at least 10 kPa. These two measures can be improved up to a maximum EGR estimation error of 10% and a minimum ΔP of 4 kPa respectively through the use of crank-angle resolved ΔP measurement. Further improvements are possible with the new unsteady orifice equation, where all errors are reduced roughly to within ±1%. The effect of inertia, however, can be mimicked in the steady orifice equation with a realistic sampling rate and a slower sensor with an appropriately selected response speed, resulting in a maximum error of 5% and errors within ±1% for ΔP exceeding 1 kPa. © 2016

关键词： Errors Combustion Combustion knock Compressible flow Error analysis estimation Exhaust gas recirculation Fuel economy Orifices Pressure measurement Differential pressures estimation algorithm Low pressures Measurement characteristics Pressure differential Pulsating flow Steady compressible flows Unsteady compressible flow

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