A method for the application of the MIMO iterative waterfilling algorithm for broadband channels is presented. The modified game-theoretic problem formulation and its Nash equilibrium are presented, along with conditi...
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A method for the application of the MIMO iterative waterfilling algorithm for broadband channels is presented. The modified game-theoretic problem formulation and its Nash equilibrium are presented, along with conditions for its existence and uniqueness and for the convergence of the distributed algorithm. The method is verified using a simple design example. The performance of the MIMO iterative waterfilling algorithm in the presence of errors in the channel state information (CSI) is also presented.
In this work, an energy based acoustic source localization task in a wireless sensor network (WSN) is considered. Based on data gathered from field experiments, it is revealed that the acoustic energy gathered at sens...
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In this work, an energy based acoustic source localization task in a wireless sensor network (WSN) is considered. Based on data gathered from field experiments, it is revealed that the acoustic energy gathered at sensor nodes exhibits a heavy-tail, non-Gaussian characteristic and should be fitted into a contaminated Gaussian model. This property renders conventional least square and maximum likelihood based location estimation methods ineffective. Leveraging the distributed, in-network processing nature of a WSN, a novel de-centralized robust acoustic source localization (DRASL) algorithm is proposed. With the DRASL, local sensor nodes receive sensor readings broadcast from neighboring sensors and independently compute local location estimates using a light-weight iterative Nonlinear Reweighted Least Square (INRLS) algorithm. The local location estimate then will be relayed to a fusion center where the final location estimate is obtained as a weighted average of the local estimates. The potential advantage of this algorithm is validated using extensive simulation in a real-world operation scenario. It is show that its performance is superior than existing methods while promising to be more energy efficient.
In this paper,a novel approach to dynamic output-feedback control is established for positive systems with interval *** and sufficient conditions for the existence of robust controllers are established.
ISBN:
(纸本)9781510823808
In this paper,a novel approach to dynamic output-feedback control is established for positive systems with interval *** and sufficient conditions for the existence of robust controllers are established.
A method for UAV landing precisely on ground wire of high voltage transmission line is proposed based-on virtual control *** solves the problem of high complexity and low computational efficiency of traditional attitu...
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A method for UAV landing precisely on ground wire of high voltage transmission line is proposed based-on virtual control *** solves the problem of high complexity and low computational efficiency of traditional attitude estimation ***,the iterative algorithm based on spatial collinearity error is used to improve the pose estimation ***,according to the idea of virtual control point in EPn P algorithm,the pose estimation accuracy of the iterative solution is improved without increasing the computational ***,the performance of the algorithm is tested by simulation and unmanned aerial vehicle *** results show that the algorithm not only maintains the pose estimation accuracy,but also can obtain the pose estimation speed better than the orthogonal iterative algorithm which has a broader application prospects.
iterative learning identification algorithms for time-varying neural networks training are presented, by which neural networks based identification for discrete-time varying nonlinear systems can be carried out, as th...
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iterative learning identification algorithms for time-varying neural networks training are presented, by which neural networks based identification for discrete-time varying nonlinear systems can be carried out, as the system undertaken performs tasks repeatedly over a finite time interval. This paper develops the iterative learning least squares algorithm with dead-zone for the weights updating along the iteration axis. In order to improve the convergence rate, the learning algorithm is modified by re-adjusting the covariance matrix. The proposed algorithms guarantee that the estimation error converges to a bound point wisely over the entire time interval. Numerical results are presented to demonstrate effectiveness of the proposed learning algorithms.
This paper applies the hierarchical identification principle and the gradient search method to study iterative solutions for a class of general coupled matrix equations with real coefficients. As long as the convergen...
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ISBN:
(纸本)9781457700811
This paper applies the hierarchical identification principle and the gradient search method to study iterative solutions for a class of general coupled matrix equations with real coefficients. As long as the convergence factors are appropriately chosen, the proposed algorithms for any initial values can provide iterative solutions that are arbitrarily close to the unique solutions of the equations. Two numerical examples are given to demonstrate the effectiveness of the proposed algorithms.
This paper proposes to extend the given reference signal in the iterative learning control context so that the resultant signal has the non-minimum phase zero structure as the given plant. This extension enables preve...
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This paper proposes to extend the given reference signal in the iterative learning control context so that the resultant signal has the non-minimum phase zero structure as the given plant. This extension enables preventing control inputs exponentially increasing. The extending signals can be synthesized by solving a linear equation. The effectiveness of the proposed method is examined by using a numerical example.
Designing a. nonlinear H∞ control law requires solving the Hamilton-Jacobi-Isaacs (HJI) equations, which are a set of nonlinear partial differential equations. An algorithm for obtaining the Taylor series solution of...
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Designing a. nonlinear H∞ control law requires solving the Hamilton-Jacobi-Isaacs (HJI) equations, which are a set of nonlinear partial differential equations. An algorithm for obtaining the Taylor series solution of HJI equations was given in [5], which showed that the coefficients of the Taylor series were governed by an algebraic Ricatti equation, and a sequence of linear algebraic equations. An iterative algorithm was further developed in [6] that can significantly improve the computational efficiency over the algorithm given in [5]. In this paper, we will further consider the computer implementation of the algorithm developed in [5] and [6]. Our algorithm has been tested on a nonlinear benchmark control problem. A fifth-order controller is obtained with its performance compared with the linear and third order ones. Computational efficiency is also compared with the Gaussian elimination method.
In a pursuit-evasion game, a pursuer tries to capture evader while the evader is trying to avoid capture. During the pursuit and evasion, pursuer longs for minimizing the distance from evader at any time while evader ...
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In a pursuit-evasion game, a pursuer tries to capture evader while the evader is trying to avoid capture. During the pursuit and evasion, pursuer longs for minimizing the distance from evader at any time while evader wants to the maximal distance. Although the relevant information of each side is unknown for each other, the initial information about pursuer and evader's locations and transition directions can be presented according to the prior probability. Then a Bayesian iterative process can be used to modify the probability of opponent's actions and to maximize the probability. It can make the pursuer and evader satisfy their min and max needs respectively. Simulations show that with the increase of pursuit-evasion area, capture frequency has robust convergence, and average capture time and iterative frequency increase faster.
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