In this paper we give new results on the analysis and control of differential linear repetitive processes, which are a distinct class of 2D linear systems of both systems theoretic and applications interest. The new r...
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In this paper we give new results on the analysis and control of differential linear repetitive processes, which are a distinct class of 2D linear systems of both systems theoretic and applications interest. The new results relate to stability and control in the presence of uncertainty in the process state space model. The family of control laws used has a well defined physical basis in terms of the underlying process dynamics.
Repetitive processes are a distinct class of 2D systems of both systems theoretic and applications interest. They cannot be controlled by direct extension of existing techniques from either standard or 2D systems theo...
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Repetitive processes are a distinct class of 2D systems of both systems theoretic and applications interest. They cannot be controlled by direct extension of existing techniques from either standard or 2D systems theory. Here we give new results on the design of physically based feedback control laws. These results relate to design for performance and are illustrated on data for a model which arises in the modelling of a physical process.
In this paper, we explore the possibility of applying Monte Carlo methods (i.e., randomization) to semi-infinite programming problems. Equivalent stochastic optimization problems are derived for a general class of sem...
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In this paper, we explore the possibility of applying Monte Carlo methods (i.e., randomization) to semi-infinite programming problems. Equivalent stochastic optimization problems are derived for a general class of semi-infinite programming problems. For the equivalent stochastic optimization problems, algorithms based on stochastic approximation and Monte Carlo sampling methods are proposed. The asymptotic behavior of the proposed algorithms is analyzed and sufficient conditions for their almost sure convergence are obtained.
Software cybernetics explores the interplay between software and control and is motivated by the fundamental question whether or not and how software behavior can be controlled. In this paper, we formulate the underly...
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Software cybernetics explores the interplay between software and control and is motivated by the fundamental question whether or not and how software behavior can be controlled. In this paper, we formulate the underlying motivations and ideas of software cybernetics and review various existing research topics in this emerging area, including feedback mechanisms in software processes, bisimulation and controllability, adaptive software, software synthesis, software test process control, and adaptive testing. We identify software rejuvenation and performance control, software fault-tolerance, logical foundation for control systems, and communication complexity for control systems as potential research topics. Several on-going research projects are also summarized.
In this paper, a new adaptive multichannel filter for the detection and removal of impulsive noise, bit errors and outliers in digital color images is provided. The proposed nonlinear filter takes the advantages of th...
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This paper is concerned with an application study of model-based fault detection method to a ship propulsion system. When modeling the object system, Quasi-ARMAX model with multi-model form is used. In this model, the...
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This paper is concerned with an application study of model-based fault detection method to a ship propulsion system. When modeling the object system, Quasi-ARMAX model with multi-model form is used. In this model, the system non-linearity is incorporated into model parameters by using non-linear non-parametric models (NNMs). Kullback discrimination Information (KDI) is introduced as fault detection index to evaluate the distortion in identified model, which is caused by a fault. The effectiveness of the method is verified through simulation studies on the ship propulsion system.
Bit errors and impulses introduced into cardiographic image sequences prohibit to process and evaluate the heart dynamics correctly. Thus, biomedical imaging such as vascular imaging and quantification of heart dynami...
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In the area of process automation it is increasingly frequent to find control loops that close through communication networks, giving as a result what we know as distributed control systems. The CAN fieldbus (controll...
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In the area of process automation it is increasingly frequent to find control loops that close through communication networks, giving as a result what we know as distributed control systems. The CAN fieldbus (controller area network) is a solid industrial network, with a high baud rate and a capacity for error detection that makes it ideal for aggressive electromagnetic environments. The special idiosyncrasy of CAN, with protocols based on message priority, makes it especially interesting for the implementation of real-time control systems. Here, a CAN node realization is presented. This is useful for industrial and/or educational applications because it allows the study and analysis of the delays suffered by the messages. It is based on a model for the planning of deadline monotonic (DM) type tasks in a global system controlled by CANalyzer. The calculation of the worstcase delay has been carried out by means of the jCAN1 software tool, previously validated on a specific theoretical example. Finally, the results are evaluated and verified, and discussed with reference to the practical results obtained in a multi-node system constituted by a group of identical nodes to the one designed here.
In this paper, a vector generalization of weighted median optimization approaches is provided. The proposed optimized weighted vector median filters utilize the relationship between standard median filter and vector m...
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In this paper, a vector generalization of weighted median optimization approaches is provided. The proposed optimized weighted vector median filters utilize the relationship between standard median filter and vector median filter and also take the advantage of the generalized adaptive optimization algorithms initially developed for weighted median filters.
We provide new adaptive multichannel filtering schemes for the detection and removal of impulsive noise, bit errors and outliers in digital color images. The proposed nonlinear filter is based on the generalized multi...
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We provide new adaptive multichannel filtering schemes for the detection and removal of impulsive noise, bit errors and outliers in digital color images. The proposed nonlinear filter is based on the generalized multichannel concept of the local entropy contrast and the robust order-statistics theory. The proposed entropy based directional distance filter is computationally attractive, robust for a wide range of the impulsive noise corruption and significantly improves the signal-detail preservation capability of the standard multichannel filters outputting the lowest ranked vector as the output sample.
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