Proceedings ArticleDOI
Robustness properties of output predictive dead-beat control: SISO case
J. Reid,Raman K. Mehra,Earl Krikwood +2 more
- Vol. 18, Iss: 18, pp 307-314
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TLDR
In this article, the "dead beat" or discrete minimum time control law for sampled data systems is formulated as an output predictive linear equation problem rather than an eigenvalue/eigenvector assignment problem, which allows one to derive very general bounds for closed loop stability under conditions of both model and prediction.Abstract:
The "dead beat" or "discrete minimum time" control law for sampled data systems is formulated as an output predictive linear equation problem rather than an eigenvalue/eigenvector assignment problem. Using the contraction mapping principle and a singular value analysis of this linear equation problem, then allows one to derive very general bounds for closed loop stability under conditions of both model and prediction, large scale errors. Furthermore, a direct design procedure is provided for selection of the "optimal" sample time to maximize closed loop robustness.read more
Citations
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Journal ArticleDOI
Model predictive control: theory and practice—a survey
TL;DR: The flexible constraint handling capabilities of MPC are shown to be a significant advantage in the context of the overall operating objectives of the process industries and the 1-, 2-, and ∞-norm formulations of the performance objective are discussed.
Journal ArticleDOI
Properties of generalized predictive control
David Clarke,C. Mohtadi +1 more
TL;DR: Simulated examples show that GPC is suitable for controlling a complex plant such as unstable/inverse unstable systems and how the observer polynomial independently tailors the response to the disturbances.
Journal ArticleDOI
Model predictive control: Theory and practice
TL;DR: Model predictive control (MPC) as mentioned in this paper is a family of controllers in which there is a direct use of an explicit and separately identifiable model and has been widely used in industrial applications.
Journal ArticleDOI
Properties of Generalized Predictive Control
David Clarke,C. Mohtadi +1 more
TL;DR: In this article, a Generalized Predictive Control (GPC) approach is presented for controlling complex plant such as unstable/inverse unstable systems, where the selection of particular "horizons" (the "costing horizons" and the "control horizon") leads to well-understood basic techniques such as dead-beat, pole-placement, Generalized Minimum Variance and LQ.
Journal ArticleDOI
Multivariable process control - A survey
TL;DR: The survey encompasses both linear and nonlinear multivariable systems, on-line estimation, adaptive control, distributed systems, and recent developments in computer-aided control system design that provide the basis for predictions of the future evolution of the field.
References
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LINPACK Users' Guide
TL;DR: General matrices Band matrices positive definite matrices Positive definite band matrices Symmetric Indefinite Matrices Triangular matrices Tridiagonal matrices The Cholesky decomposition The QR decomposition up to and including the singular value decomposition is studied.
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On the general theory of control systems
TL;DR: In this paper, a general theory of control systems is outlined which answers many basic questions (what is controllable? why? how?) and gives a highly efficient method of computation.
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TL;DR: In this article, the authors propose a linear vector space representation of the state space and linear vector spaces of the linear operator representations of state vectors. But the state vector spaces do not have the same properties as the vector spaces used in this paper.
Proceedings ArticleDOI
Singular value analysis of linear systems
TL;DR: In this paper, Singular value analysis is applied in a very direct way to systems of linear differential equations as well, where norm characteristics (l2 norm) of relevant maps are reflected, with no distortion, by norm characteristics of associated grammian matrices.
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