For linear time-invariant systems Bode's sensitivity integral is a well-known formula that quantifies some of the limitations in feedback control. In this paper we show that a very similar formula holds for linear...
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For linear time-invariant systems Bode's sensitivity integral is a well-known formula that quantifies some of the limitations in feedback control. In this paper we show that a very similar formula holds for linear time-periodic systems. We use the infinite-dimensional frequency-response operator called the harmonic transfer function to prove the result. It is shown that the harmonic transfer function is an analytic operator and a trace class operator under the assumption that the periodic system has roll-off 2. A periodic system has roll-off 2 if the first time-varying Markov parameter is equal to zero.
Device and machinery noise can be reduced by controlling vibration of casing walls - such approach, referred to as the active casing approach, has been successfully applied by the authors in previous publications. It ...
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Device and machinery noise can be reduced by controlling vibration of casing walls - such approach, referred to as the active casing approach, has been successfully applied by the authors in previous publications. It was observed that for an effective active control it is crucial to mount sensors and actuators at appropriate locations on the vibrating structure. However, an optimization process of sensors and actuators arrangement requires a precise mathematical model of such structure. In this research a cuboid light-weight casing is considered. A mathematical model describing walls of such casing requires parameters to be defined that cannot be delivered by the producer nor measured directly. The aim of this paper is to develop and evaluate an identification procedure of model parameters basing on experimental data - distinguished natural frequencies and modeshapes. A memetic algorithm is used to find optimal set of model parameters. automatic classification of simulated modeshapes is employed. Obtained results are validated experimentally for multiple casing walls.
Omola (object-oriented modelling language), a language for structured dynamic models, is presented. The language is based on ideas from object-oriented programming. Models are represented as classes with attributes. I...
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Omola (object-oriented modelling language), a language for structured dynamic models, is presented. The language is based on ideas from object-oriented programming. Models are represented as classes with attributes. Inheritance and hierarchical submodel decomposition improve model structure and facilitate reuse of models. The language is designed to be general and extensible in order to employ future, as yet unpredicted, model representation concepts. A few examples of extensions are given.< >
An overview is given of two graphical control languages for supervisory control applications implemented in G2. The languages are used for model-based diagnosis and sequential control applications.
An overview is given of two graphical control languages for supervisory control applications implemented in G2. The languages are used for model-based diagnosis and sequential control applications.
The impact of the selected Lyapunov function on the performance of a nonlinear system designed by adaptive backstepping is considered. Special attention is paid to the comparison of various Barrier Lyapunov Functions,...
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The impact of the selected Lyapunov function on the performance of a nonlinear system designed by adaptive backstepping is considered. Special attention is paid to the comparison of various Barrier Lyapunov Functions, which assure preservation of hard state constraints during any transient. The differences in the system operation are discussed and some recommendations the Lyapunov function selection are given.
Globalization and growing new markets force the car manufacturers to work faster and more efficient in developing new safety and comfort features for their vehicles. Hence, time-consuming expensive testing is more and...
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Globalization and growing new markets force the car manufacturers to work faster and more efficient in developing new safety and comfort features for their vehicles. Hence, time-consuming expensive testing is more and more replaced by computer simulations. Normally, these simulations are based on complex physical models describing the dynamic behavior of the vehicle and its components. Sometimes, physical modeling of the nonlinear behavior of certain vehicle components can be very difficult. In these cases, neural networks may be used to model the systems' nonlinearities. The paper discusses the advantages of combining physical modeling with neural networks for a semi-physical process model. The vertical vehicle dynamics are used as example.
We formulate and solve a control problem where data are sent over a communication network that introduces random time delays. Past time delays are assumed known by the use of time stamps and the probability distributi...
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We formulate and solve a control problem where data are sent over a communication network that introduces random time delays. Past time delays are assumed known by the use of time stamps and the probability distribution of future delays are modeled with a Markov chain with continuous observation densities. We generalize previous results on LQG control of jump linear systems to cover this situation.
Recent years have witnessed the emergence of new types of semantic search engines which attempt to overcome the defects of the traditional search engines by providing different search patterns. A big question here is ...
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This paper designs an improved fast nonsingular terminal sliding mode control (FNTSMC) method for permanent magnet linear motors to track the periodic control tasks, which uses an iterative learning controller to lear...
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In the paper nonlinear transformations of multivariate orthogonal multisine random time-series are discussed. A focus on transformations that preserves orthogonality of transformed multivariate orthogonal multisine ra...
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In the paper nonlinear transformations of multivariate orthogonal multisine random time-series are discussed. A focus on transformations that preserves orthogonality of transformed multivariate orthogonal multisine random time-series elements is given and the following from this property decomposition of multichannel nonlinear dynamic system identification problem into separate single-channel nonlinear dynamic system identification problems is described. This decomposition is illustrated by simulation examples devoted to identification of two-input single-output nonlinear dynamic systems based on observed mixtures of single-channel nonlinear block-oriented dynamic system outputs and the corresponding samples of the used bivariate orthogonal white multisine random excitations.
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