The Experts below are selected from a list of 207 Experts worldwide ranked by ideXlab platform
Jason Sheng-hong Tsai - One of the best experts on this subject based on the ideXlab platform.
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Realization, design and implementation of row-pseudoproper left Matrix Fraction descriptions with impulsive modes☆
Computers & Mathematics with Applications, 1994Co-Authors: Jason Sheng-hong Tsai, Wein Shung Chen, Leang-san ShiehAbstract:A novel and minimal realization algorithm is proposed for determining generalized state-space representation from a so-called row-pseudoproper left Matrix Fraction description (LMFD). The realized system with the state-space representation form is proved to be controllable and observable in the sense of [1,2] if the given row-pseudoproper MFD is left coprime. Besides, the proposed state feedback control law not only satisfies the optimal regional-pole-placement design for the realized generalized dynamical system, but also eliminates the impulsive terms in the state response of the closed-loop system. For practical consideration, an equivalent input-output feedback structure of the designed state-feedback controller is adopted. Based on the cascaded and/or parallel active RC networks with better sensitivity and stability properties, the resulting structure of the equivalent input-output feedback controller can be readily implemented based on proper subsystems.
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Generalized Matrix Euclidean algorithms for solving diophantine equations and associated problems
Computers & Mathematics with Applications, 1993Co-Authors: Jason Sheng-hong Tsai, S.s. Chen, Leang-san ShiehAbstract:Abstract Based on the Matrix Fraction descriptions of multi-variable control systems, this paper presents the generalized Matrix Euclidean algorithms for solving Diophantine equations and associated problems. A chain rule is developed for finding the greatest common right(left) divisor of two square(non-square) polynomial matrices and the irreducible right(left) Matrix Fraction description from the reducible or irreducible left(right) Matrix Fraction description. Also, the development of multi-variable pole-assignment controllers are discussed for engineering applications.
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Implementation of column-pseudoproper right Matrix Fraction descriptions with cascaded or parallel active RC networks
Journal of the Franklin Institute, 1993Co-Authors: Jason Sheng-hong Tsai, Chu T. WangAbstract:Abstract An effective and constructive approach for implementing the so-called column-pseudoproper right Matrix Fraction descriptions defined by Tan and Vandewalle with cascaded or parallel active RC networks is presented. The resulting structure contains m sets of decoupled RC-voltage amplifier networks in a cascaded form or in a parallel form, for structuring accessible intermediate states. A state-feedback control law is applied around the auxiliary network for the realization of the desired overall voltage Matrix Fraction descriptions. The proposed cascaded and parallel RC networks have shown good sensitivity and stability properties.
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Minimal order realization with a special coordinate for Matrix Fraction descriptions
Journal of the Franklin Institute, 1993Co-Authors: Wen-liang Chen, Jason Sheng-hong TsaiAbstract:Abstract This paper presents a generalized and minimal realization algorithm for constructively determining generalized state-space representation from a so-called column (row)- pseudoproper or a column(row)-proper or a nonstrictly-proper right(left) Matrix Fraction description (MFD). The realized state-space representation form with a special coordinate is proved to be controllable and observable in the sense of Rosenbrock and Cobb; besides, the dimension of the system after realization is equal to the determinantal degree of the given right(left) MFD in the normal sense.
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Generalized realizations with a special coordinate for Matrix Fraction descriptions
International Journal of Systems Science, 1992Co-Authors: Jason Sheng-hong Tsai, Wein Shung ChenAbstract:A generalized and feasible realization algorithm for constructively determining generalized state-space representation from a so-called column (row)-pseudo-proper or a column (row)-proper right (left) Matrix Fraction description (MFD) is proposed. The realized state-space representation form with a special coordinate is proved to be controllable and observable in the sense of Rosenbrock and Cobb; moreover, the dimension of the system after realization is equal to the deter-minantal degree of the given right (left) MFD in the normal sense.
Nicos Karcanias - One of the best experts on this subject based on the ideXlab platform.
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Decoupling and pole assignment of singular systems: a frequency domain approach
Automatica, 1997Co-Authors: D. Vafiadis, Nicos KarcaniasAbstract:Abstract A new approach to the row by row decoupling of singular systems via state feedback and regular input transformation is presented. The proposed method is based on the Matrix Fraction description of the system and is an extension of the frequency domain method for strictly proper systems. The solvability condition of the problem is readily obtained from the ‘numerator’ Matrix of a coprime and column reduced Matrix Fraction description of the given system. Pole placement and decoupling is also considered, and the characterization of the fixed poles is given.
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Generalized state-space realizations from Matrix Fraction descriptions
IEEE Transactions on Automatic Control, 1995Co-Authors: D. Vafiadis, Nicos KarcaniasAbstract:The problem of the realization of a Matrix Fraction description (MFD) of a nonproper transfer function is considered. An algorithm for the realization is developed, and it is shown that it is a natural generalization of Wolovich's method (1973) for the case of proper systems. The resulting generalized state-space system is shown to be reachable, and the conditions for its minimality, in terms of the coprimeness and column reducedness of the MFD, are derived. The relation between the controllability indexes of the realization and the Forney order (1975) of the MFD is established. >
Wein Shung Chen - One of the best experts on this subject based on the ideXlab platform.
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Realization, design and implementation of row-pseudoproper left Matrix Fraction descriptions with impulsive modes☆
Computers & Mathematics with Applications, 1994Co-Authors: Jason Sheng-hong Tsai, Wein Shung Chen, Leang-san ShiehAbstract:A novel and minimal realization algorithm is proposed for determining generalized state-space representation from a so-called row-pseudoproper left Matrix Fraction description (LMFD). The realized system with the state-space representation form is proved to be controllable and observable in the sense of [1,2] if the given row-pseudoproper MFD is left coprime. Besides, the proposed state feedback control law not only satisfies the optimal regional-pole-placement design for the realized generalized dynamical system, but also eliminates the impulsive terms in the state response of the closed-loop system. For practical consideration, an equivalent input-output feedback structure of the designed state-feedback controller is adopted. Based on the cascaded and/or parallel active RC networks with better sensitivity and stability properties, the resulting structure of the equivalent input-output feedback controller can be readily implemented based on proper subsystems.
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Generalized realizations with a special coordinate for Matrix Fraction descriptions
International Journal of Systems Science, 1992Co-Authors: Jason Sheng-hong Tsai, Wein Shung ChenAbstract:A generalized and feasible realization algorithm for constructively determining generalized state-space representation from a so-called column (row)-pseudo-proper or a column (row)-proper right (left) Matrix Fraction description (MFD) is proposed. The realized state-space representation form with a special coordinate is proved to be controllable and observable in the sense of Rosenbrock and Cobb; moreover, the dimension of the system after realization is equal to the deter-minantal degree of the given right (left) MFD in the normal sense.
Kenji Sugimoto - One of the best experts on this subject based on the ideXlab platform.
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ROCOND - Blind identification of polynomial Matrix Fraction for disturbance rejection
IFAC Proceedings Volumes, 2012Co-Authors: Daisuke Tanaka, Takuya Hirotani, Kenji SugimotoAbstract:Abstract This paper proposes an approach to blind system identification for disturbance rejection control. We first identify plant dynamics with unknown disturbance, based on a well-known FIR (Finite Impulse Response) approximation technique for BSD (Blind Signal Deconvolution) in terms of independence of signals. Since we are more interested in the system itself than signal deconvolution, we adopt polynomial Matrix Fraction with a given degree structure, and then adjust the coefficients by projecting the FIR learning law to this parameter space of modest dimension. Finally we design feedback control for disturbance rejection via the identified system representation. Numerical simulation for a simple example is carried out to illustrate the proposed approach.
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Blind Identification of Polynomial Matrix Fraction with Applications
Perspectives in Mathematical System Theory Control and Signal Processing, 2010Co-Authors: Kenji SugimotoAbstract:Fractional representation by polynomial matrices is a tool for describing linear dynamical systems, often providing a unique insight into the systems. It has turned out that the coefficient matrices in this representation can be identified without knowing the input data, under some statistic assumptions. This is an outcome by combining system theory with a recent progress in signal processing; i.e., a methodology generically called independent component analysis.
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Blind identification of polynomial Matrix Fraction via independent component analysis
International Journal of Robust and Nonlinear Control, 2007Co-Authors: Masuhiro Nitta, Kenji SugimotoAbstract:This paper proposes a method for blind system identification based on independence of input signals. Under the assumption that the system is multi-input multi-output, square, and represented by a polynomial Matrix Fraction with constant numerator Matrix, the method makes it possible to identify the system parameter without observation of input signals. This rather challenging problem is solved by applying independent component analysis to an augmented state-space representation in order to estimate coefficients of the denominator polynomial Matrix and the numerator Matrix. After giving this blind system identification algorithm, the paper shows how the proposed method is used in application. The first issue is suppression of disturbance with unknown dynamics. Assuming that a disturbance enters into a system independently of the control input signals, the method identifies a denominator polynomial Matrix of the disturbance dynamics. Then an H∞ controller is designed in order to suppress the effect of the disturbance. The second is fault detection of mechanical systems subject to vibration from the environment. The vibration source is assumed to be unmeasurable, and yet the method achieves detection of a parameter change of the system due to fault. Copyright © 2006 John Wiley & Sons, Ltd.
Chu T. Wang - One of the best experts on this subject based on the ideXlab platform.
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Implementation of column-pseudoproper right Matrix Fraction descriptions with cascaded or parallel active RC networks
Journal of the Franklin Institute, 1993Co-Authors: Jason Sheng-hong Tsai, Chu T. WangAbstract:Abstract An effective and constructive approach for implementing the so-called column-pseudoproper right Matrix Fraction descriptions defined by Tan and Vandewalle with cascaded or parallel active RC networks is presented. The resulting structure contains m sets of decoupled RC-voltage amplifier networks in a cascaded form or in a parallel form, for structuring accessible intermediate states. A state-feedback control law is applied around the auxiliary network for the realization of the desired overall voltage Matrix Fraction descriptions. The proposed cascaded and parallel RC networks have shown good sensitivity and stability properties.