Direct Robust Sampled-Data Marine Control Systems Design on Basis of Parametric Transfer Function Method 1
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Robustness
Digital Control
Basis (linear algebra)
The synthesis of digital feedback control systems in the frequency domain involves: finding the discrete transfer function G(z) of the sampled model of the dynamic process; using an appropriate method to find the discrete transfer function D(z) of the feedback controller; and establishing and validating, based on simulation, the control diagram thus synthesized. Direct design of digital controllers from the model approach is not always trivial, given the multiple conditions and constraints that need to be reflected in the form of a closed-loop transfer function F(z). The transfer functions D(z) and G(z) of a digital control loop are closely dependent on the sampling frequency fs = 1 / T used. It is therefore important to know the practical conditions for choosing the range of fs for which quantities D(z) and G(z) are sufficiently reliable.
Digital Control
Discrete frequency domain
Feedback Control
Feedback loop
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Isogonal Basis is a generalization for the orthogonal basis.The properties of isogonal basis and orthogonal basis are similar.So discussing the property of isogonal basis can give us a tool of analyzing Euclidean space and deepen apprehend of Euclidean space for us.This paper mainly extends the property of orthogonal basis to isogonal basis and gets five principles.
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Controllers are usually implemented in a digital computer. Figure 11.1 shows a single-loop sampled-data control system with c z (z) representing the z-transfer function of the digital controller, and (1 - e - s T s as the transfer function of the hold element, T is the sampling interval.
Sampled data systems
Robustness
Sampling interval
Digital Control
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The problem of converting existing continuous-data control systems into digital control systems is considered. The objective of this paper is to develop a computer-aided method for synthesizing the pulse-transfer function of the digital controller. This is done by matching the frequency response of the digital control system to that of the continuous system with a minimum weighted mean-square error. Formulas for computing the parameters of the digital controller are obtained as a result. The design technique is illustrated aith a numerical example, and a comparison with previous methods is also presented.
Digital Control
Sampled data systems
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This paper is concerned with the robust stabilizability for single-input single-output plants. Robust stabilizability means that a fixed controller can stabilize simultaneously all the plants in a given class which is characterized by a frequency-dependent uncertainty band function around the transfer function of a nominal model. A necessary and sufficient condition for robust stabilizability is derived based on the well-known Nevanlinna-Pick theory in classical analysis. It is shown that the values of the uncertainty band function should be restricted within a certain range at the unstable poles of the nominal model, in order for the class to be robustly stabilizable. A procedure of synthesizing a robust stabilizer is given and the parametrization of all the robust stabilizers is also shown.
Parametrization (atmospheric modeling)
Robustness
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Sampled data systems
Sampling interval
Robustness
Digital Control
Interval data
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Robustness
Digital Control
Basis (linear algebra)
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The problem of converting existing continuous data control systems into digital control systems is considered. The objective of this paper is to develop a computer-aided method for synthesizing the pulse-transfer function of the digital controller. This is done by matching the frequency response of the digital control system to that of the continuous system with a minimum weighted mean square error. Formulas for computing the parameters of the digital controller are obtained as a result. The design technique is illustrated with a numerical example and a comparison with previous methods is also presented.
Digital Control
Sampled data systems
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The purpose of this note is to introduce interesting and useful properties differential-basis and p-basis in theorem 3.3. The result gives a existence differential basis of $S^P$ [$[{\Lambda}_1]$ ](S) which has a p-basis over $S^p$ ($S^p[{\Lambda}_1]$ ).
Basis (linear algebra)
Basis function
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The properties and concrete structures of subquantale are studied.The concepts of a dense subset and a basis on Quantale are introduced.The relationship between dense subsets and basis and the properties of dense subset and basis are discussed.
Basis (linear algebra)
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