In this paper, design of Takagi-Sugeno controllers for a twin-rotor system from empirical data is addressed. First, identification of linear models using Prediction Error Method in the presence of nonlinear distortion...
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ISBN:
(纸本)9781457710957
In this paper, design of Takagi-Sugeno controllers for a twin-rotor system from empirical data is addressed. First, identification of linear models using Prediction Error Method in the presence of nonlinear distortions and in feedback systems is revisited, and it is demonstrated that feedback nonlinear systems with an integral action can be locally represented by linear models rather than affine models. Moreover, it is demonstrated that how the consistency and unbiasedness of the identified models can be improved by proper design of the experiments. In order to ensure that the unmodeled contributions in the resulting piecewise linear model are sufficiently small, a criterion is proposed based on the small-gain theorem that can be used for unfalsification of the piecewise linear model. Finally, by taking advantage of the separation principle, design of fuzzy Takag-Sugeno state feedback and observer is formulated in terms of Linear Matrix Inequalities (LMIs). The implementation results on the actual system demonstrate significant improvements with respect to the initial controller and previous work on similar systems.
Electrocardiogram (ECG) signal has biomedical signs showing the working activity of the heart muscle by human body. Being able to take these biomedical signs from human body is important for diagnosis. Although there ...
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Electrocardiogram (ECG) signal has biomedical signs showing the working activity of the heart muscle by human body. Being able to take these biomedical signs from human body is important for diagnosis. Although there are a lot of Independent Component Analysis (ICA) algorithms that separate ECG signals from noises in the literature, separation qualities of them depend on initial conditions. The aim of this study is to find an ICA algorithm giving the stable separation quality for different initial conditions. Experimental results show that Kernel Independent Component Analysis algorithm (KICA) provides more accurate and stable results than the other algorithms.
The paper considers a class of one-dimensional circular standard cellular neural network (CNN) arrays with a typical three-segment piecewise linear activation and two-sided cooperative (positive) interactions (a coope...
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The paper considers a class of one-dimensional circular standard cellular neural network (CNN) arrays with a typical three-segment piecewise linear activation and two-sided cooperative (positive) interactions (a cooperative CNN ring). Numerical simulations show that in a wide range of interconnection parameters, and for a wide set of initial conditions, the solutions of a cooperative CNN ring display unexpectedly long oscillations, lasting even hundreds of cycles, before they eventually converge toward an equilibrium point. The goal of this paper is to confirm the presence of such long-transient oscillations through laboratory experiments on a simple discrete-component prototype of a cooperative CNN ring with 16 cells and to analyze some of their salient features. Analytical results are also provided to support the numerical and experimental findings.
Due to the large number of the resources, the frequent reengineering of manufacturing processes and the often changing product types, the maintenance of the simulation model and the provision of up-to-date input data ...
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Due to the large number of the resources, the frequent reengineering of manufacturing processes and the often changing product types, the maintenance of the simulation model and the provision of up-to-date input data are almost always difficult. The paper introduces new quantitative analysis method including processing time and batch calculation algorithms applied in the automatic building of discrete-event simulation systems. The simulation model and the mentioned algorithms are both directly interfaced with real execution databases and the overall solution supports the shop-floor managers in making control decisions. The applicability of the elaborated approach is illustrated by the results of experiments relying on real historical data.
Simultaneous Localization and Mapping (SLAM) algorithms with multiple autonomous robots have received considerable attention in recent years. In general, SLAM algorithms use odometry information and measurements from ...
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ISBN:
(纸本)9781467324199
Simultaneous Localization and Mapping (SLAM) algorithms with multiple autonomous robots have received considerable attention in recent years. In general, SLAM algorithms use odometry information and measurements from exteroceptive sensors of robots. The accuracy of these measurements and the performance of the corresponding SLAM algorithm directly affect the overall success of the system. This paper presents comparative performance evaluations of three Simultaneous Localization and Mapping (SLAM) algorithms using Extended Kalman Filter (EKF), Compressed Extended Kalman Filter (CEKF) and Unscented Kalman Filter (UKF). Specifically, it focuses on their SLAM performances and processing time requirements. To show the effect of CPU power on the processing time of SLAM algorithms, two notebooks and a netbook with different specifications have been used. Comparative simulation results show that processing time requirements are consistent with the computational complexities of SLAM algorithms. The results we obtained are consistent with the CPU power tests of independent organizations and show that higher processing power decreases processing time accordingly. The results also show that CEKF is more suitable for outdoor SLAM applications where there are a lot of natural and artificial features.
Traditional smart home system based on TCP/IP network applies TC35i cell phone module in smart home controller, and realizes function of short message service by GSM network. This realization model is complex, high-co...
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作者:
Gábor SzederkényiZ. A. TuzaKatalin M. HangosProcess Control Research Group
Computer and Automation Research Institute Hungarian Academy of Sciences. Kende u. 13-17 H-1111 Budapest Hungary and Faculty of Information Technology Pázm Hungary Faculty of Information Technology
Pázmány Péter Catholic University Práter u. 50/a H-1083 Budapest Hungary Process Control Research Group
Computer and Automation Research Institute Hungarian Academy of Sciences. Kende u. 13-17 H-1111 Budapest Hungary and Dept. of Electrical Engineering and Informatio Hungary
A numerical method is proposed in this paper for the computation of dense and sparse reaction network structures for kinetic polynomial models with uncertain parameters represented as intervals. The problem is traced ...
A numerical method is proposed in this paper for the computation of dense and sparse reaction network structures for kinetic polynomial models with uncertain parameters represented as intervals. The problem is traced back to mixed integer linear programming.
Tuning of controller is one of the most basic functions in control engineering in obtaining optimal control parameters and hence achieving optimal dynamic responses of the system. The work presents the self-tuning PI ...
Tuning of controller is one of the most basic functions in control engineering in obtaining optimal control parameters and hence achieving optimal dynamic responses of the system. The work presents the self-tuning PI controller that potential to auto-tune the controller parameters and adapting the changes in controlled process parameter for a MIMO system. The decentralized PI controller with an adaptive interaction algorithm is developed and tested to nonlinear multivariable wastewater treatment plant. It is aims to self-tune the PI control parameters in regulating the substrate and DO concentrations from a steady state operating point. It was observed that the proposed control structure and the tuning algorithm were successfully tracks the desired set-point with considerable effects in noisy environment.
One of the most widespread techniques to evaluate various aspects of an existing manufacturing system is discrete-event simulation (DES). However, building a simulation model of a manufacturing system needs great reso...
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One of the most widespread techniques to evaluate various aspects of an existing manufacturing system is discrete-event simulation (DES). However, building a simulation model of a manufacturing system needs great resource expenditures. Automated data col-lection and model buildup can drastically reduce the time of the design phase as well as support model reusability. Since most of the manufacturing systems are controlled by low level controllers they store structure and control logic of the system to be modeled by a DES system. The paper introduces an ongoing research of PLC code processing method for automatic simulation model gen-eration of a conveyor system of a leading automotive factory.
Preserving connectivity of a network topology is a crucial aspect for multi-robot systems in order to perform almost any collaborative task. This problem turns out to be significantly challenging in the case of a hete...
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ISBN:
(纸本)9781457710957
Preserving connectivity of a network topology is a crucial aspect for multi-robot systems in order to perform almost any collaborative task. This problem turns out to be significantly challenging in the case of a heterogeneous multirobot system equipped with different sensors with limited field of view. Such an interaction scheme, in fact, is described by directed graphs (digraphs), for which, a few approaches have still been presented in literature. This paper addresses the problem of estimating an approximated minimum strongly connected digraph contained in a given digraph. A novel decentralized approach is proposed and its suitability is confirmed by simulations.
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