898 resultados para linear and nonlinear systems identification


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Recurrent neural networks can be used for both the identification and control of nonlinear systems. This paper takes a previously derived set of theoretical results about recurrent neural networks and applies them to the task of providing internal model control for a nonlinear plant. Using the theoretical results, we show how an inverse controller can be produced from a neural network model of the plant, without the need to train an additional network to perform the inverse control.

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This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.

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With the ever increasing demands for high complexity consumer electronic products, market pressures demand faster product development and lower cost. SoCbased design can provide the required design flexibility and speed by allowing the use of IP cores. However, testing costs in the SoC environment can reach a substantial percent of the total production cost. Analog testing costs may dominate the total test cost, as testing of analog circuits usually require functional verification of the circuit and special testing procedures. For RF analog circuits commonly used in wireless applications, testing is further complicated because of the high frequencies involved. In summary, reducing analog test cost is of major importance in the electronic industry today. BIST techniques for analog circuits, though potentially able to solve the analog test cost problem, have some limitations. Some techniques are circuit dependent, requiring reconfiguration of the circuit being tested, and are generally not usable in RF circuits. In the SoC environment, as processing and memory resources are available, they could be used in the test. However, the overhead for adding additional AD and DA converters may be too costly for most systems, and analog routing of signals may not be feasible and may introduce signal distortion. In this work a simple and low cost digitizer is used instead of an ADC in order to enable analog testing strategies to be implemented in a SoC environment. Thanks to the low analog area overhead of the converter, multiple analog test points can be observed and specific analog test strategies can be enabled. As the digitizer is always connected to the analog test point, it is not necessary to include muxes and switches that would degrade the signal path. For RF analog circuits, this is specially useful, as the circuit impedance is fixed and the influence of the digitizer can be accounted for in the design phase. Thanks to the simplicity of the converter, it is able to reach higher frequencies, and enables the implementation of low cost RF test strategies. The digitizer has been applied successfully in the testing of both low frequency and RF analog circuits. Also, as testing is based on frequency-domain characteristics, nonlinear characteristics like intermodulation products can also be evaluated. Specifically, practical results were obtained for prototyped base band filters and a 100MHz mixer. The application of the converter for noise figure evaluation was also addressed, and experimental results for low frequency amplifiers using conventional opamps were obtained. The proposed method is able to enhance the testability of current mixed-signal designs, being suitable for the SoC environment used in many industrial products nowadays.

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A neural model for solving nonlinear optimization problems is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The network is shown to be completely stable and globally convergent to the solutions of nonlinear optimization problems. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are presented to validate the developed methodology.

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This paper presents an efficient neural network for solving constrained nonlinear optimization problems. More specifically, a two-stage neural network architecture is developed and its internal parameters are computed using the valid-subspace technique. The main advantage of the developed network is that it treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty or weighting parameters for its initialization.

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In practical situations, the dynamics of the forcing function on a vibrating system cannot be considered as given a priori, and it must be taken as a consequence of the dynamics of the whole system. In other words, the forcing source has limited power, as that provided by a DC motor for an example, and thus its own dynamics is influenced by that of the vibrating system being forced. This increases the number of degrees of freedom of the problem, and it is called a non-ideal problem. In this work, we considerer two non-ideal problems analyzed by using numerical simulations. The existence of the Sommerfeld effect was verified, that is, the effect of getting stuck at resonance (energy imparted to the DC motor being used to excite large amplitude motions of the supporting structure). We considered two kinds of non-ideal problem: one related to the transverse vibrations of a shaft carrying two disks and another to a piezoceramic bar transducer powered by a vacuum tube generated by a non-ideal source Copyright © 2007 by ASME.

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Structural damage identification is basically a nonlinear phenomenon; however, nonlinear procedures are not used currently in practical applications due to the complexity and difficulty for implementation of such techniques. Therefore, the development of techniques that consider the nonlinear behavior of structures for damage detection is a research of major importance since nonlinear dynamical effects can be erroneously treated as damage in the structure by classical metrics. This paper proposes the discrete-time Volterra series for modeling the nonlinear convolution between the input and output signals in a benchmark nonlinear system. The prediction error of the model in an unknown structural condition is compared with the values of the reference structure in healthy condition for evaluating the method of damage detection. Since the Volterra series separate the response of the system in linear and nonlinear contributions, these indexes are used to show the importance of considering the nonlinear behavior of the structure. The paper concludes pointing out the main advantages and drawbacks of this damage detection methodology. © (2013) Trans Tech Publications.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This paper presents an investigation into some practical issues that may be present in a real experiment, when trying to validate the theoretical frequency response curve of a two degree-of-freedom nonlinear system consisting of coupled linear and nonlinear oscillators. Some specific features, such as detached resonance curves, have been theoretically predicted in multi degree-of-freedom nonlinear oscillators, when subject to harmonic excitation, and the system parameters have been shown to be fundamental in achieving such features. When based on a simplified model, approximate analytical expression for the frequency response curves may be derived, which may be validated by the numerical solutions. In a real experiment, however, the practical achievability of such features was previously shown to be greatly affected by small disturbances induced by gravity and inertia, which led to some solutions becoming unstable which had been predicted to be stable. In this work a practical system configuration is proposed where such effects are reduced so that the previous limitations are overcome. A virtual experiment is carried out where a detailed multi-body model of the oscillator is assembled and the effects on the system response are investigated.

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Pós-graduação em Engenharia Mecânica - FEIS

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This thesis starts showing the main characteristics and application fields of the AlGaN/GaN HEMT technology, focusing on reliability aspects essentially due to the presence of low frequency dispersive phenomena which limit in several ways the microwave performance of this kind of devices. Based on an equivalent voltage approach, a new low frequency device model is presented where the dynamic nonlinearity of the trapping effect is taken into account for the first time allowing considerable improvements in the prediction of very important quantities for the design of power amplifier such as power added efficiency, dissipated power and internal device temperature. An innovative and low-cost measurement setup for the characterization of the device under low-frequency large-amplitude sinusoidal excitation is also presented. This setup allows the identification of the new low frequency model through suitable procedures explained in detail. In this thesis a new non-invasive empirical method for compact electrothermal modeling and thermal resistance extraction is also described. The new contribution of the proposed approach concerns the non linear dependence of the channel temperature on the dissipated power. This is very important for GaN devices since they are capable of operating at relatively high temperatures with high power densities and the dependence of the thermal resistance on the temperature is quite relevant. Finally a novel method for the device thermal simulation is investigated: based on the analytical solution of the tree-dimensional heat equation, a Visual Basic program has been developed to estimate, in real time, the temperature distribution on the hottest surface of planar multilayer structures. The developed solver is particularly useful for peak temperature estimation at the design stage when critical decisions about circuit design and packaging have to be made. It facilitates the layout optimization and reliability improvement, allowing the correct choice of the device geometry and configuration to achieve the best possible thermal performance.

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This thesis proposes design methods and test tools, for optical systems, which may be used in an industrial environment, where not only precision and reliability but also ease of use is important. The approach to the problem has been conceived to be as general as possible, although in the present work, the design of a portable device for automatic identification applications has been studied, because this doctorate has been funded by Datalogic Scanning Group s.r.l., a world-class producer of barcode readers. The main functional components of the complete device are: electro-optical imaging, illumination and pattern generator systems. For what concerns the electro-optical imaging system, a characterization tool and an analysis one has been developed to check if the desired performance of the system has been achieved. Moreover, two design tools for optimizing the imaging system have been implemented. The first optimizes just the core of the system, the optical part, improving its performance ignoring all other contributions and generating a good starting point for the optimization of the whole complex system. The second tool optimizes the system taking into account its behavior with a model as near as possible to reality including optics, electronics and detection. For what concerns the illumination and the pattern generator systems, two tools have been implemented. The first allows the design of free-form lenses described by an arbitrary analytical function exited by an incoherent source and is able to provide custom illumination conditions for all kind of applications. The second tool consists of a new method to design Diffractive Optical Elements excited by a coherent source for large pattern angles using the Iterative Fourier Transform Algorithm. Validation of the design tools has been obtained, whenever possible, comparing the performance of the designed systems with those of fabricated prototypes. In other cases simulations have been used.