This work is intended as an attempt to develop a simple real-time guidance scheme for mobile sensors used to enhance estimation of a spatially distributed process described by a partial differential equation. Using Ly...
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Real-life call detail data (CDR) are used to build a graph of a social network of telecommunication operator customers. Affiliation network is used in graph construction since CDR data are partially kept anonymous. A ...
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Functional programming languages are ideally suited for developing dependable software, but not much work have been done on modeling functional programs. Although UML is mainly based on concepts which are native to im...
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The problem of enclosing all solutions of an underdetermined system of equations is considered. A few variants of the algorithm to solve this problem are compared - some of the features come from the literature and so...
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The problem of enclosing all solutions of an underdetermined system of equations is considered. A few variants of the algorithm to solve this problem are compared - some of the features come from the literature and some are original. The paper discusses both implementational and theoretical issues of the problem, including a useful theorem that is proved. Shared-memory parallelization, using OpenMP is also considered and numerical results for proper test problems are presented.
The paper deals with the problem of designing an unknown input filter for non-linear discrete-time stochastic systems. In particular, it is shown how to design an unknown input filter for a single (constant) unknown i...
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The paper deals with the problem of designing an unknown input filter for non-linear discrete-time stochastic systems. In particular, it is shown how to design an unknown input filter for a single (constant) unknown input distribution matrix. Subsequently, the interacting multiple model algorithm is employed to tackle the problem of selecting an appropriate unknown input distribution matrix from a predefined set. The final part of the paper shows an illustrative example, which confirms the effectiveness of the proposed approach.
The paper presents FraDIA, a framework facilitating the creation of vision systems, which can operate as a stand-alone application as well as play the role of a vision subsystem for robotic controllers. The article de...
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The paper presents FraDIA, a framework facilitating the creation of vision systems, which can operate as a stand-alone application as well as play the role of a vision subsystem for robotic controllers. The article describes motivations leading to the tool creation, its structure and a method of integration with the MRROC++ system, enabling the development of a robot controller with visual feedback. The usefulness of the framework is demonstrated on the example of a robot playing checkers. In the application, FraDIA was used to implement two different vision subsystems, and the control system exhibited two behaviors utilizing visual information in two totally different ways: passive, responsible for monitoring the state of the game, and active, in which vision was utilized during the manipulator motion for localizing a pawn to be grasped. Regarding the complexity of the system, a specification method based on agents and the transition function was used. The method, consisting of mathematical formulas supplemented by data flow diagrams, enables the reader to understand both the system structure and its behavior.
This paper presents an identification method of dynamic systems based on the Group Method of Data Handing. In particular, a new structure of the dynamic neuron in pole representation is proposed. Moreover, a new train...
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This paper presents an identification method of dynamic systems based on the Group Method of Data Handing. In particular, a new structure of the dynamic neuron in pole representation is proposed. Moreover, a new training algorithm based on the Unscented Kalman Filter is presented. The final part of this work contains an illustrative example regarding the application of the proposed approach to an identification of the tunnel furnace.
Abstract The paper is concerned with disturbance modeling and observer design for Model Predictive control (MPC) with different formulations of state-space process models. Systematic discussion is given, presenting th...
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Abstract The paper is concerned with disturbance modeling and observer design for Model Predictive control (MPC) with different formulations of state-space process models. Systematic discussion is given, presenting the ways the deterministic disturbances most important in process control applications should be treated in the MPC algorithm, to obtain disturbance attenuation and offset-free control. The closely related problem of observer design and understanding is explained. It is shown that a simple approach with a process state observer only, in the presence of deterministic disturbances, can work better than the conventional approach of extended process-disturbance state estimation. The observer design is also considered for the case of extended velocity form state-space modeling including integrators. A simplified approach with reduced order observer is given. The results are illustrated on a 2×2 example process problem.
In this article a new approach to iterative learning control for the practically relevant case of deterministic discrete linear plants with uniform rank greater than unity is developed. The analysis is undertaken in a...
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In this paper we propose a novel distributed algorithm to solve degenerate linear programs on asynchronous networks. Namely, we propose a distributed version of the well known simplex algorithm. We prove its convergen...
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