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...
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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.
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 tim...
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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.
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...
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ISBN:
(纸本)9781538621684
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 the course of training learning systems.
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....
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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 c...
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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.
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 fi...
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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.
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...
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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.
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...
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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.
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 ...
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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.
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. Conditio...
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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.
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