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A fast moving horizon estimation algorithm based on nonlinear programming sensitivity

JOURNAL OF PROCESS CONTROL 2008年第9期18卷 876-884页

作者： Zavala, Victor M. Laird, Carl D. Biegler, Lorenz T. Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

Moving horizon estimation (MHE) is an efficient optimization-based strategy for state estimation. Despite the attractiveness of this method, its application in industrial settings has been rather limited. This has been mainly due to the difficulty to solve, in real-time, the associated dynamic optimization problems. In this work, a fast MHE algorithm able to overcome this bottleneck is proposed. The strategy exploits recent advances in nonlinear programming algorithms and sensitivity concepts. A detailed analysis of the optimality conditions of MHE problems is presented. As a result, strategies for fast covariance information extraction from general nonlinear programming algorithms are derived. It is shown that highly accurate state estimates can be obtained in large-scale MHE applications with negligible on-line computational costs.. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： estimation algorithms Real-time Large-scale Nonlinear programming Sensitivity analysis

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Intelligent Robotic Multisensorial System to Build Metallic Structures

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IFAC Proceedings Volumes 2008年第3期41卷 133-138页

作者： J.A. Corrales G.J. García P. Gil J. Pomares S.T. Puente F. Torres Physics Systems Engineering and Signal Theory Department University of Alicante PO Box 99 03080 Alicante. Spain

This paper describes a multisensorial system employed in a robotic application developed to automatically construct metallic structures. The proposed system has the novelty of a high degree of flexibility with an intelligent multisensorial system. This sensorial system is composed of a visual-force control system, a time of flight 3D-camera, an inertial motion capture system and an indoor localization system. These two last sensors are used to avoid possible collisions between the human operator and the robots working in the same workspace.

关键词： visual servoing force control sensor fusion estimation algorithms robot vision

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Position Tracking Control with Velocity from Accelerometer and Encoder

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IFAC Proceedings Volumes 2008年第2期41卷 14828-14833页

作者： Wen-Hong Zhu Tom Lamarche Spacecraft Engineering Canadian Space Agency 6767 route de l'Aeroport Saint-Hubert QC Canada J3Y 8Y9 (Tel: 450-926-5177

Being widely used in industrial systems and manufacturing lines, precision position control systems need to use high feedback control gains to reject disturbances. However, phase-lag in velocity estimation resulting from encoder measurement imposes a limitation on maximum allowable feedback gains, when system stability and control smoothness are concerned. In this paper, use of velocities derived from both acceleration and position measurements is suggested. The derived velocity possesses a much higher bandwidth without having theoretical phase-lag. Experimental results reveal that the use of velocities derived from practical accelerometers and encoders allows a typical position control system to substantially increase its feedback gains without compromising stability and control smoothness. It in turn results in much smaller tracking errors, compared to scenarios when velocities are created from position sensors only.

关键词： Velocity estimation, Accelerometer Control precision Position control Motion control High-gain feedback High accuracy pointing Manufacturing plant control Data-fusion Multi-sensor systems estimation algorithms

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Spherical Simplex Sigma-Point Kalman Filters: A comparison in the inertial navigation of a terrestrial vehicle

Spherical Simplex Sigma-Point Kalman Filters: A comparison i...

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2008 American Control Conference (ACC), vol.9

作者： Juan G. Castrejon Lozano Luis R. Garca Carrillo Alejandro Dzul Rogelio Lozano División de Estudios de Posgrado e Investigación of the Instituto Tecnológico de la Laguna Blvd. Revolución y Cuauhtémoc 27000 Torreón Coahuila Mexico División de Estudios de Posgrado e Investigación Instituto Tecnológico de la Laguna Torreon Coahuila Mexico Heudiasyc UMR-CNRS 6599 Centre de Recherches de Royallieu Université de Technologie de Compiégne Compiegne France

To determine the position of a mobile robot continues being a complex and interesting challenge in localization algorithms, whose solution requires the use of estimation techniques of nonlinear systems, a well selection of sensors that fulfill the restrictions imposed by the characteristics of the system, and the selection of the suitable algorithm of navigation. In this article, the performance of three variants of Sigma Point Kalman Filter (SPKF) are analyzed and compared, where the selection strategy of spherical simplex sigma points is used in order to improve its performance for real time execution. The analyzed filters are applied to an inertial navigation system that is used for the localization of a terrestrial mobile vehicle. The obtained results of the comparative analysis are illustrated by some simulations.

关键词： Kalman filters mobile robots estimation algorithms inertial navigation estimation of position

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Quantized consensus

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AUTOMATICA 2007年第7期43卷 1192-1203页

作者： Kashyap, Akshay Basar, Tamer Srikant, R. Univ Illinois Dept Elect & Comp Engn Urbana IL 61801 USA

We study the distributed averaging problem on arbitrary connected graphs, with the additional constraint that the value at each node is an integer. This discretized distributed averaging problem models several problems of interest, such as averaging in a network with finite capacity channels and load balancing in a processor network. We describe simple randomized distributed algorithms which achieve consensus to the extent that the discrete nature of the problem permits. We give bounds on the convergence time of these algorithms for fully connected networks and linear networks. (c) 2007 Elsevier Ltd. All rights reserved.

关键词： sensor fusion quantization distributed detection estimation algorithms stochastic systems random processes clock synchronization

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Design of robust output predictors under scarce measurements with time-varying delays

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AUTOMATICA 2007年第2期43卷 281-289页

作者： Sanchis, Roberto Penarrocha, Ignacio Albertos, Pedro Univ Jaume 1 Dept Engn Sistemes Ind & Disseny Castellon de La Plana Spain Univ Politecn Valencia Dept Engn Sistemes & Automat Valencia Spain

In this paper, the design of an output predictor for systems with scarce irregular measurements with time varying delays is addressed. A model based predictor that takes into account the past measured outputs is used. Robustness of the predictor to the time varying delays and data availability as well as disturbance attenuation is dealt with via H-infinity performance. A design strategy is proposed based on the available disturbances information. (C) 2006 Elsevier Ltd. All rights reserved.

关键词： unconventional sampling missing-data linear matrix inequalities time delay estimation algorithms prediction methods

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ON-LINE estimation FOR PROCESS CONTROL AND OPTIMIZATION APPLICATIONS

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IFAC Proceedings Volumes 2007年第5期40卷 19-28页

作者： Tor Steinar Schei Cybernetica AS

Design of Kalman filter type and moving horizon estimators for on-line estimation applications based on first principles models is reviewed. Important design issues are discussed, such as: model development; choice of process noise model and selection of model parameters for on-line estimation; use of asynchronous and delayed measurements; and off-line estimation of fixed but uncertain model parameters. The main conclusion, which is substantiated through application examples, is that robust and reliable estimation applications based on first principles models of considerable complexity, can be designed and implemented for use in an industrial environment.

关键词： State estimation Parameter estimation estimation algorithms Kalman filters Moving horizon estimation On-line estimation Industrial applications

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THE HYBRID estimation ALGORITHM FOR WASTEWATER TREATMENT PLANT ROBUST MODEL PREDICTIVE CONTROL PURPOSES AT MEDIUM TIME SCALE

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IFAC Proceedings Volumes 2007年第9期40卷 280-285页

作者： T. Rutkowski M.A. Brdys Faculty of Electrical and Control Engineering Gdansk University of Technology ul. G. Narutowicza 11/12 80 952 Gdansk Poland School of Engineering Department of Electronic Electrical and Computer Engineering The University of Birmingham Birmingham B15 2TT UK

The paper proposes an approach to designing the hybrid estimation algorithm/module (HEA) with moving measurements window for Wastewater Treatment Plant (WWTP) Robust Model Predictive Control (RMPC) purposes at medium time scale. The RMPC uses a dedicated grey-box model of biological reactor for the system outputs prediction purposes. The grey-box model parameters are dependant on the plant operating point. Hence, these parameters and grey-box model state should be estimated according to the current operating plant condition. The needed parameters and state estimates at medium time scale are provided by the HEA algorithm. The HEA consist of the set-bounded parameter and state estimation algorithm cooperated with the Extended Kalman Filter (EKF) algorithm. The HEA algorithm is used to ensure robustness of grey-box model parameter and state estimates in situation of limited amount of hard measurements on the WWTP. The state estimates provided by the EKF are used as pseudo measurements of the states and the set-bounded estimation algorithm produce sets bounding the grey-box model parameters and states. There are two hybrid estimation algorithms presented and described in the paper: algorithm of explicit method and algorithm of implicit method. Both hybrid estimation algorithms are validated by simulation base on real data records and calibrated model of Kartuzy WWTP in northern Poland.

关键词： biotechnology hierarchical control systems model predictive control robust control estimation algorithms bounding method uncertainty

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estimation OF THE CYLINDER PRESSURE OFFSET AND POLYTROPIC EXPONENT USING EXTENDED KALMAN FILTER

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IFAC Proceedings Volumes 2007年第10期40卷 175-182页

作者： Philipp Klein Matthias Schmidt Otmar Loffeld DaimlerChrysler AG Group Research GR/EEP Stuttgart Germany Center for Sensorsystems (ZESS) University of Siegen Germany

The cylinder pressure information offers an increasing potential for the control of internal combustion engines. The pressure sensors measure a relative cylinder pressure signal only. For the determination of the absolute cylinder pressure, the measured cylinder pressure data, during the pre-combustion compression, is fitted to a polytropic curve. The polytropic exponent, which defines the polytropic curve, is not known and varies during the compression stroke. Therefore, a potential improvement to using predetermined polytropic exponent could be accomplished by using an estimated value. The estimation of the cylinder pressure offset and the polytropic exponent may be obtained by a nonlinear optimization. For the solution of this optimization problem an Extended Kalman Filter with a Markov-2 Process is proposed.

关键词： Extended Kalman Filters Markov models State estimation Filter design Observers Engine control Pressure transducers estimation algorithms

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A FAST COMPUTATIONAL FRAMEWORK FOR LARGE-SCALE MOVING HORIZON estimation

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IFAC Proceedings Volumes 2007年第5期40卷 19-28页

作者： Victor M. Zavala Carl D. Laird Lorenz T. Biegler Chemical Engineering Department Carnegie Mellon University Pittsburgh PA USA 15213

Moving Horizon estimation (MHE) is an efficient optimization-based strategy for state estimation. Despite the attractiveness of this method, its application in industrial settings has been rather limited. This has been mainly due to the difficulty to solve, in real-time, the associated dynamic optimization problems. In this work, a fast MHE algorithm able to overcome this bottleneck is proposed. The framework exploits the advantages of simultaneous collocation- based formulations and makes use of large-scale nonlinear programming algorithms and sensitivity concepts. The approach is demonstrated on a full-scale polymer process, where accurate state estimates are obtained and on-line calculation times are reduced dramatically.

关键词： estimation algorithms real-time discretization finite elements nonlinear programming sensitivity analysis

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