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21st IFAC World Congress on Automatic Control - Meeting Societal Challenges

作者： Onesto, L. Corno, M. Franceschetti, L. Hokka, E. Savaresi, S. M. Politecn Milan Dipartimento Elettron Informaz & Bioingn Via G Ponzio 34-5 I-20133 Milan Italy TTControl GmbH Ensuring Reliable Networks FN 246 Handelsgericht Wien Vienna Austria

This paper presents an obstacle detection system for snow groomers. The system is based on a 2D solid-states LiDAR sensor mounted on the top of the cabin. The measurements describe the surrounding environment through an Occupancy Grid framework, which is extended for this particular case study. The proposed approach set the occupancy probability of the surrounding environment based on the expected height of the obstacle. The method is extensively analyzed through experimental test on a snow groomer. Copyright (C) 2020 The Authors.

关键词： Robot navigation estimation algorithms Navigation system Obstacle detection

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Space-based IR tracking bias removal using background star observations

Space-based IR tracking bias removal using background star o...

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Conference on Sensors and Systems for Space Applications III

作者： Clemons, T. M., III Chang, K. C. George Mason Univ Dept Syst Engn & Operat Res Fairfax VA 22030 USA

ISBN: (纸本)9780819475961

This paper provides the results of a proposed methodology for removing sensor bias from a space-based infrared (IR) tracking system through the use of stars detected in the background field of the tracking sensor. The tracking system consists of two satellites flying in a lead-follower formation tracking a ballistic target. Each satellite is equipped with a narrow-view IR sensor that provides azimuth and elevation to the target. The tracking problem is made more difficult due to a constant, non-varying or slowly varying bias error present in each sensor's line of sight measurements. As known stars are detected during the target tracking process, the instantaneous sensor pointing error can be calculated as the difference between star detection reading and the known position of the star. The system then utilizes a separate bias filter to estimate the bias value based on these detections and correct the target line of sight measurements to improve the target state vector. The target state vector is estimated through a Linearized Kalman Filter (LKF) for the highly non-linear problem of tracking a ballistic missile. Scenarios are created using Satellite Toolkit c for trajectories with associated sensor observations. Mean Square Error results are given for tracking during the period when the target is in view of the satellite IR sensors. The results of this research provide a potential solution to bias correction while simultaneously tracking a target.

关键词： Missile Defense estimation Extended Kalman Filter Linearized Kalman Filter estimation algorithms bias error bias correction space tracking

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GLOBAL OPTIMIZATION OF STATISTICAL FUNCTIONS WITH SIMULATED ANNEALING

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JOURNAL OF ECONOMETRICS 1994年第1-2期60卷 65-99页

作者： GOFFE, WL FERRIER, GD ROGERS, J UNIV ARKANSAS FAYETTEVILLEAR 72701 MEMPHIS STATE UNIV MEMPHISTN 38152

Many statistical methods rely on numerical optimization to estimate a model's parameters. Unfortunately, conventional algorithms sometimes fail. Even when they do converge, there is no assurance that they have found the global, rather than a local, optimum. We test a new optimization algorithm, simulated annealing, on four econometric problems and compare it to three common conventional algorithms. Not only can simulated annealing find the global optimum, it is also less likely to fail on difficult functions because it is a very robust algorithm. The promise of simulated annealing is demonstrated on the four econometric problems.

关键词： SIMULATED ANNEALING GLOBAL OPTIMIZATION estimation algorithms

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Inventory Control for a Manufacturing System under Uncertainty: Adaptive Approach

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IFAC-PapersOnLine 2017年第1期50卷 10154-10159页

作者： Azarskov V.N. Zhiteckii L.S. Solovchuk K.Y. Sushchenko O.A. Lupoi R.O. National Aviation University Kiev 03058 Ukraine Int. Centre of Inform. Technologies & Systems Institute of Cybernetics MSP Kiev 03680 Ukraine

This paper deals with controlling the in-process inventories for the manufacturing system of a typical machine-building enterprise which includes the machining, the transport, the storage bunker and the assembly line. The decision-making is implemented under uncertainty associated with the absence of exact machining model assuming that machine failures are also possible. To cope with this uncertainty, the adaptive control approach is proposed. Within this approach, a new adaptive reorder policy which makes it possible to improve the performance of the inventory control system is developed. Simulation experiments are conducted to demonstrate the advantage of this policy. © 2017

关键词： Adaptation estimation algorithms identifiers inventory control production planning scheduling uncertainty

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Pitch Dynamics Analysis for an Agricultural Tractor with Image Processing Validation through an Off-Board Camera 9th

Pitch Dynamics Analysis for an Agricultural Tractor with Ima...

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9th IFAC International Symposium on Advances in Automotive Control (AAC)

作者： Onesto, L. Corno, M. Savaresi, S. Politecn Milan Dipartimento Elettron Informaz & Bioingn Via G Ponzio 34-5 I-20133 Milan Italy

This work proposes an analysis of the pitch dynamics of a heavy-duty vehicle, namely an agricultural tractor. Considering maneuvers performed on a flat-asphalt surface, the analysis is performed through an image processing approach. The analysis focuses on the cabin displacement and on the vehicle body displacement. Moreover, the tires compression and the vehicle longitudinal slip are evaluated. The analysis shows how the cabin and the body displacements change in function of the vehicle longitudinal acceleration and how, due to the tires compression, the cabin and the body can oscillate, at the end of a braking maneuver. The results are used to evaluate the feasibility of a road gradient estimator based on the inertial measurement of a mono axial accelerometer installed in the cabin. In particular, the cabin displacement needs to be considered and an additional sensor which measures the cabin speed is required to avoid a drop of performance. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Vehicle dynamics Pitch estimation algorithms Kalman Filters Image Processing

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Effective recursive parallelotopic bounding for robust output-feedback control

Effective recursive parallelotopic bounding for robust outpu...

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18th IFAC Symposium on System Identification (SYSID)

作者： Sharma, Udit Thangavel, Sakthi Mukkula, Anwesh Reddy Gottu Paulen, Radoslav Tech Univ Dortmund Proc Dynam & Operat Grp Dortmund Germany Slovak Univ Technol Bratislava Fac Chem & Food Technol Bratislava Slovakia

In this paper an approach is studied to guaranteed (set-membership) state estimation for robust output-feedback model predictive control (MPC) with hard input and state constraints. Uncertainties are assumed to arise in a dynamic system from unknown initial conditions of state variables and due to unknown-but-bounded measurement noise. The uncertainty in the state variables is represented as a parallelotopic set. The employed state-estimation algorithm recursively outbounds the feasible set that is given by an intersection of model predictions with obtained measurement information. Along with the well-known minimum-volume criterion for parallelotopic outbounding, three alternative criteria are proposed and studied. The aim is to identify the best outbounding approach for improving performance of the robust MPC. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： state estimation estimation algorithms output feedback robust control

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Multi-agent Localization of A Common Reference Coordinate Frame: An Extrinsic Approach 8th

Multi-agent Localization of A Common Reference Coordinate Fr...

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8th IFAC Workshop on Distributed estimation and Control in Networked Systems (NECSYS)

作者： Quoc Van Tran Ahn, Hyo-Sung Gwangju Inst Sci & Technol Sch Mech Engn Gwangju South Korea

This paper studies the problem of multi-agent cooperative localization of a common reference coordinate frame in R-3. Each agent in a system maintains a body-fixed coordinate frame and its actual frame transformation (translation and rotation) from the global coordinate system is unknown. The mobile agents aim to determine their trajectories of rigid-body motions (or the frame transformations, i.e., rotations and translations) with respect to the global coordinate frame up to a common frame transformation by using local measurements and information exchanged with neighbors. We present two frame localization schemes which compute the rigid-body motions of the agents with asymptotic stability and finite-time stability properties, respectively. Under both localization laws, the estimates of the frame transformations of the agents converge to the actual frame transformations almost globally and up to an unknown constant transformation bias. Finally, simulation results are provided. Copyright (C) 2019. The Authors. Published by Elsevier Ltd. All rights reserved.

关键词： Multi-agent systems Frame Localization Distributed computation estimation algorithms Sensor networks Measurement and instrumentation

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Methodology for Handling Missing Data in Nonlinear Mixed Effects Modelling

Methodology for Handling Missing Data in Nonlinear Mixed Eff...

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作者： ASA M. JOHANSSON Uppsala University

学位级别：博士

To obtain a better understanding of the pharmacokinetic and/or pharmacodynamic characteristics of an investigated treatment, clinical data is often analysed with nonlinear mixed effects modelling. The developed models can be used to design future clinical trials or to guide individualised drug treatment. Missing data is a frequently encountered problem in analyses of clinical data, and to not venture the predictability of the developed model, it is of great importance that the method chosen to handle the missing data is adequate for its purpose. The overall aim of this thesis was to develop methods for handling missing data in the context of nonlinear mixed effects models and to compare strategies for handling missing data in order to provide guidance for efficient handling and consequences of inappropriate handling of missing data. In accordance with missing data theory, all missing data can be divided into three categories; missing completely at random (MCAR), missing at random (MAR) and missing not at random (MNAR). When data are MCAR, the underlying missing data mechanism does not depend on any observed or unobserved data; when data are MAR, the underlying missing data mechanism depends on observed data but not on unobserved data; when data are MNAR, the underlying missing data mechanism depends on the unobserved data itself. Strategies and methods for handling missing observation data and missing covariate data were evaluated. These evaluations showed that the most frequently used estimation algorithm in nonlinear mixed effects modelling (first-order conditional estimation), resulted in biased parameter estimates independent on missing data mechanism. However, expectation maximization (EM) algorithms (e. g. importance sampling) resulted in unbiased and precise parameter estimates as long as data were MCAR or MAR. When the observation data are MNAR, a proper method for handling the missing data has to be applied to obtain unbiased and precise parameter estimates

关键词： Pharmacometrics population models censored observations missing covariates missing dependent variable missing data mechanism missing completely at random (MCAR) missing at random (MAR) missing not at random (MNAR) estimation algorithms

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Cramer-Rao Lower Bound Attainment in Range-Only Positioning Using Geometry: The G-WLS

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2021年 70卷

作者： Fontanelli, Daniele Shamsfakhr, Farhad Palopoli, Luigi Dept Ind Engn I-38123 Trento Italy Univ Trento Dept Informat Engn & Comp Sci I-38123 Trento Italy

The positioning problem addressed in this article amounts to finding the planar coordinates of a device from a collection of ranging measurements taken from other devices located at known positions. The solution based on weighted least square (WLS) is popular, but its accuracy depends from a number of factors only partially known. In this article, we explore the dependency of the uncertainty from the geometric configuration of the anchors. We show a refinement technique for the estimate produced by the WLS that compensates for the effects of geometry on the WLS and reduces the target uncertainty to a value very close to the Cramer-Rao Lower Bound. The resulting algorithm is called geometric WLS (G-WLS) and its application is particularly important in the most critical conditions for WLS (i.e., when the target is far apart from the anchors). The effectiveness of the G-WLS is proven theoretically and is demonstrated on a large number of experiments and simulations.

关键词： Cramer-Rao lower bound (CRLB) estimation algorithms indoor positioning mobile robot estimation ranging-based positioning ultrawide band (UWB) uncertainty analysis

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A scalable multi-step least squares method for network identification with unknown disturbance topology

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AUTOMATICA 2022年 141卷

作者： Fonken, Stefanie J. M. Ramaswamy, Karthik Raghavan Van den Hof, Paul M. J. Eindhoven Univ Technol Dept Elect Engn Eindhoven Netherlands

Identification methods for dynamic networks typically require prior knowledge of the network and disturbance topology, and often rely on solving poorly scalable non-convex optimization problems. While methods for estimating network topology are available in the literature, less attention has been paid to estimating the disturbance topology, i.e., the (spatial) noise correlation structure and the noise rank in a filtered white noise representation of the disturbance signal. In this work we present an identification method for dynamic networks, in which an estimation of the disturbance topology precedes the identification of the full dynamic network with known network topology. To this end we extend the multi-step Sequential Linear Regression and Weighted Null Space Fitting methods to deal with reduced rank noise, and use these methods to estimate the disturbance topology and the network dynamics in the full measurement situation. As a result, we provide a multi-step least squares algorithm with parallel computation capabilities and that rely only on explicit analytical solutions, thereby avoiding the usual non-convex optimizations involved. Consequently we consistently estimate dynamic networks of Box Jenkins model structure, while keeping the computational burden low. We provide a consistency proof that includes path-based data informativity conditions for allocation of excitation signals in the experimental design. Numerical simulations performed on a dynamic network with reduced rank noise clearly illustrate the potential of this method. (c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： System identification Dynamic networks estimation algorithms Least squares Topology estimation

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