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2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control
This paper presents a dynamic routing method for supervisory control of multiple laser guided vehicles (LGVs) that are traveling within a layout of a given warehouse. In dynamic routing a calculated path particularly depends on the number of currently active LGVs' missions and their priorities. In order to solve the shortest path problem dynamically, the proposed routing method uses the string matrix...
This paper deals with a synthesis of dynamic controllers for a class of nonlinear systems. First, mathematical model of nonlinear plant with sector-bounded nonlinearity is given. Secondly, the analysis condition for systems with sector-bounded nonlinearity is introduced, and based on this condition, the synthesis problem is formulated as a bilinear matrix inequality one. Since it is difficult to solve...
Biological process modeling requires the use of a non-LTI description. On the other hand, experimental data suggest that the behavior of many biological systems can be described with good approximation by means of piecewise linear time-invariant (LIT) models. On the basis of these considerations, the present work focuses on the problem of analyzing a set of experimental data and identifying the points...
A simple method of selecting the LQG dynamic weighting functions is proposed. This involves minimizing the traditional variance-based cost function but with a controller structure that is determined by a dynamic weighting LQG problem. This effectively forces a controller structure that has traditional integral action and controller roll-off terms. The methodology is similar to the so-called restricted-structure...
This paper shows an approach to integrating common approximate dynamic programming (ADP) algorithms into a theoretical framework to address both analytical characteristics and algorithmic features. Several important insights are gained from this analysis, including new approaches to the creation of algorithms. Built on this paradigm, ADP learning algorithms are further developed to address a broader...
In this paper, an analytical comparison is done between dynamic programming and reinforcement learning methods in dynamic two-player games. The emphasis is on the large number of states and actions available for each player and different conflictive optimization objectives of these games that make them complicated in modeling and analysis. Optimization and decision making is done through quantifying...
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