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20th World Congress of the International-Federation-of-Automatic-Control (IFAC)

作者： Filippova, Tatiana F. Russian Acad Sci Krasovskii Inst Math & Mech Ural Branch Sofia Kovalevskaya Str 16 Ekaterinburg 620990 Russia

The problem of estimating reachable sets of nonlinear dynamical control systems with quadratic nonlinearity and with uncertainty in initial states is studied. We assume that the uncertainty is of a set-membership kind when we know only the bounding set for unknown items and any additional statistical information on their behavior is not available. We present here approaches that allow finding ellipsoidal estimates of reachable sets which use the special structure of nonlinearity of studied control system. The algorithms of constructing such ellipsoidal set-valued estimates and numerical simulation results are given. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： estimation algorithms Nonlinear control systems Set-membership uncertainty Ellipsoidal calculus

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On the Configuration-LP of the Restricted Assignment Problem 28

On the Configuration-LP of the Restricted Assignment Problem

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28th Annual ACM-SIAM Symposium on Discrete algorithms (SODA)

作者： Jansen, Klaus Rohwedder, Larts Univ Kiel Dept Comp Sci D-24118 Kiel Germany

ISBN: (纸本)9781611974782

We consider the classical problem of SCHEDULING ON UN-RELATED MACHINES. In this problem a set of jobs is to be distributed among a set of machines and the maximum load (makespan) is to be minimized. The processing time p(ij) of a job j depends on the machine i it is assigned to. Lenstra, Shmoys and Tardos gave a polynomial time 2-approximation for this problem [8]. In this paper we focus on a prominent special case, the RESTRICTED ASSIGNMENT problem, in which p(ij) is an element of {p(j), infinity}. The configuration-LP is a linear programming relaxation for the RESTRICTED ASSIGNMENT problem. It was shown by Svensson that the multiplicative gap between integral and fractional solution, the integrality gap, is at most 2 - 1/17 approximate to 1.9412 [11]. In this paper we significantly simplify his proof and achieve a bound of 2 - 1/6 approximate to 1.8333. As a direct consequence this provides a polynomial (2 - 1/6 + is an element of)-estimation algorithm for the RESTRICTED ASSIGNMENT problem by approximating the configuration-LP. The best lower bound known for the integrality gap is 1.5 and no estimation algorithm with a guarantee better than 1.5 exists unless P = NP.

关键词： estimation algorithms scheduling local search linear programming integrality gap

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Methods and algorithms of determination of complexity of test questions for formation a database system of the adaptive test-control of knowledge

Methods and algorithms of determination of complexity of tes...

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International Conference on Information Science and Communications Technologies (ICISCT) - Applications, Trends and Opportunities

作者： Khidirova, Ch. M. Tashkent Univ Informat Technol Tashkent Uzbekistan

In given paper offered methods and algorithms of determination of complexity of test questions for formation a database system of the adaptive test control for objective estimation of knowledge of students (pupils) in... 详细信息

ISBN: (纸本)9781538621684

关键词： information weight feature estimation algorithms test-control of knowledge complexity of the test questions

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

Effects of Differential Pressure Measurement Characteristics...

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8th IFAC Symposium on Advances in Automotive Control (AAC)

作者： Kiwan, Rani Stefanopoulou, Anna G. Martz, Jason Surnilla, Gopichandra Ali, Imtiaz Styles, Daniel Joseph Univ Michigan Ann Arbor MI 48109 USA Ford Motor Co Dearborn MI 48121 USA

With proper control, cooled LP-EGR can be used for knock mitigation in SI engines, enabling fuel economy improvements through snore 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 (Delta P) tneasurerrient and the steady compressible flow orifice equation is investigated for various Delta P 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 Delta P sensor. Errors in the estimated EGR percentage using the steady compressible orifice equation with averaged Delta P measurement can he as high as 30%, and errors within +/- 1% require a Delta P of at least 10 kPa. These two measures can be improved up to a maximum EGR estimation error of 10% and a minimum Delta P of 4 kPa respectively through the use of crank-angle resolved Delta P 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 Delta P exceeding 1 kPa. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Low pressure exhaust gas recirculation Differential pressure measurement Error analysis estimation algorithms Pulsating flow

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q-Calculus Based Extended Kalman Filter for the Dynamic State estimation of a Synchronous Generator

<i>q</i>-Calculus Based Extended Kalman Filter for the Dynam...

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IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia)

作者： Ahmed, Arif McFadden, Fiona Stevens Rayudu, Ramesh Victoria Univ Wellington Robinson Res Inst Wellington 6140 New Zealand Victoria Univ Wellington Sch Engn & Comp Sci Smart Power & Renewable Energy Syst Grp Wellington 6140 New Zealand

ISBN: (纸本)9781509043033

The evolution of power systems into smart systems requires complex, efficient, and effective algorithms for control and optimization of the system. With this motivation, we propose and study a novel extended Kalman filter (EKF) algorithm utilizing q-calculus for the real-time dynamic state estimation (DSE) problem for synchronous generators. A 4th order nonlinear synchronous generator model is studied for DSE. Two distinct cases were looked into, one involving normal simulation and the other involving short circuit fault simulation. The observed advantages of the proposed algorithm are faster convergence and better mean-square-error (MSE) performance. As a further advantage, utilization of q-calculus also introduces a tunable q-parameter into the EKF algorithm. The DSE problem is studied under in an environment of Gaussian noise and compared with the traditional EKF. Further research work is suggested involving comparison with other DSE algorithms and in-depth analysis of the algorithm.

关键词： Dynamic state estimation q-calculus extended Kalman filter synchronous generator estimation algorithms

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Uncertainty of the Signal Parameter estimation from Sampled Data

Uncertainty of the Signal Parameter Estimation from Sampled ...

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Conference on Precision Electromagnetic Measurements (CPEM)

作者： Lapuh, Rado Sira, Martin Lindic, Matjaz Voljc, Bostjan Metrol Inst Republ Slovenia Ljubljana Slovenia Czech Metrol Inst Prague Czech Republic Slovenian Inst Qual & Metrol Ljubljana Slovenia

ISBN: (纸本)9781467391344

This paper presents the evaluation of uncertainty components attributed to the algorithm used to estimate sampled signal parameters. The white noise in the signal will influence the standard deviation of the estimates while signal imperfections like harmonic distortions, interharmonics and even non-white noise would produce bias, leading to non-statistical uncertainties. An a-priori knowledge of sampled signal is required to account for proper evaluation of these uncertainties.

关键词： Measurement sampling estimation algorithms harmonic distortion estimation error uncertainty

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On the Configuration-LP of the Restricted Assignment Problem 17

On the Configuration-LP of the Restricted Assignment Problem

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Annual ACM-Society for Industrial and Applied Mathmatics Symposium on Discrete algorithms

作者： Klaus Jansen Lars Rohwedder Department of Computer Science University of Kiel

ISBN: (纸本)9781510836358

We consider the classical problem of SCHEDULING ON UNRELATED MACHINES. In this problem a set of jobs is to be distributed among a set of machines and the maximum load (makespan) is to be minimized. The processing time p_(ij) of a job j depends on the machine i it is assigned to. Lenstra, Shmoys and Tardos gave a polynomial time 2-approximation for this problem [8]. In this paper we focus on a prominent special case, the RESTRICTED ASSIGNMENT problem, in which p_(ij) ∈ {p_j, ∞}. The configuration-LP is a linear programming relaxation for the RESTRICTED ASSIGNMENT problem. It was shown by Svensson that the multiplicative gap between integral and fractional solution, the integrality gap, is at most 2 - 1/17 ≈ 1.9412 [11]. In this paper we significantly simplify his proof and achieve a bound of 2 - 1/6 ≈ 1.8333. As a direct consequence this provides a polynomial (2 - 1/6 + ε)-estimation algorithm for the RESTRICTED ASSIGNMENT problem by approximating the configuration-LP. The best lower bound known for the integrality gap is 1.5 and no estimation algorithm with a guarantee better than 1.5 exists unless P = NP.

关键词： estimation algorithms Scheduling Local search Linear programming Integrality gap

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Piezo-actuated vibration disturbance mirror for investigating accelerometer-based tip-tilt reconstruction in large telescopes

Piezo-actuated vibration disturbance mirror for investigatin...

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7th IFAC Symposium on Mechatronic Systems (MECHATRONICS)

作者： Glueck, Martin Pott, Joerg-Uwe Sawodny, Oliver Univ Stuttgart Inst Syst Dynam ISYS Waldburystr 17-19 D-70563 Stuttgart Germany MPIA Konigstuhl 17 D-69117 Heidelberg Germany

The optical performance of large telescopes depends not only on the correction of atmospheric turbulences but also on the suppression of structural vibrations. Nowadays, these disturbances are compensated by Adaptive Optics (AO) systems. Especially for the vibration suppression new control concepts are developed. A well-known method is a state feedback controller. However, for observations with natural faint guide stars the integration time of the wavefront sensor is increased and therefore the bandwidth of the control loop is not sufficient for a fully vibration compensation. Hence, we want to avoid this problem by using an Accelerometer-based Disturbance Feedforward control (DFF), which is independent of the integration time. The vibrations are measured at the relevant telescope mirrors and the tip-tilt modes are reconstructed for the actuator control signals. For investigating the DFF a laboratory setup is built. The setup consists of a classical AO system and additional designed tip-tilt mirrors for simulating and compensating the vibrations. Several accelerometer are mounted at the disturbance mirror. Based on the measured accelerations two position estimators are investigated in order to use them in real telescope applications. (C) 2016, IFAC (International Federation of Automatic Control) Hosting Elsevier Ltd. All rights reseirved.

关键词： vibration measurement accelerometers signal reconstruction estimation algorithms actuators

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

Identifiability and Parameter Estimation of Linear Continuou...

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17th IFAC Symposium on System Identification (SYSID 2015)

作者： Mu, Biqiang Guo, Jin Wang, Le Yi Yin, George Xu, Lijian Zheng, Wei Xing Chinese Acad Sci Key Lab Syst & Control Beijing 100190 Peoples R China Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China Wayne State Univ Dept Elect & Comp Engn Detroit MI 48202 USA Wayne State Univ Dept Math Detroit MI 48202 USA State Univ New York Farmingdale State Coll Dept Elect & Comp Engn Technol Farmingdale NY 11735 USA Univ Western Sydney Sch Comp Engn & Math Penrith NSW 2751 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. (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Linear Continuous-time Systems irregular sampling identifiability nonlinear least square estimation algorithms convergence and asymptotical normality

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