Some classes of nonlinear controlled systems are considered. This systems have a linear or bilinear approximation. For different classes of the allowed controls the sufficient conditions of boundedness of the integral...
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Some classes of nonlinear controlled systems are considered. This systems have a linear or bilinear approximation. For different classes of the allowed controls the sufficient conditions of boundedness of the integral vortex are obtained. The dependence of this characteristic on degree of perturbations is discussed. External estimation of the integral vortex by means of the Lyapunov functions is constracted.
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 selecti...
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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.
Generalized adaptive notch filters (GANFs) are estimators of coefficients of quasi-periodically time-varying systems. Current state of the art GANFs can deliver highly accurate estimates of system variations' freq...
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ISBN:
(纸本)9781479988518
Generalized adaptive notch filters (GANFs) are estimators of coefficients of quasi-periodically time-varying systems. Current state of the art GANFs can deliver highly accurate estimates of system variations' frequency, but underperform in terms of accuracy of the coefficient estimates. The paper proposes a novel multistage GANF with accuracy improved in this aspect. The processing pipeline consists of three stages. The preliminary (pilot) frequency estimates are obtained first, then treated with a specially designed linear filter and used to guide the coefficient tracking GANF, which works out the estimates of system coefficients. The proposed solution has considerably better performance than a single stage GANF or a simple two-stage approach consisting of the pilot frequency estimator and the amplitude tracking GANF only.
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 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)9781509052288
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.
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