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Multivariable Control of Industrial Fractionators
IFAC Proceedings Volumes, 1986Abstract The multivariable Nyquist Array method offers a concept which enables the classical singie-iiiput/s iugle-uutput Nyquist control dcoign methode to ba extended to multivariable systems. This concept is based on partial decoupling using a compensator net-work to achieve what is known as a “diagonal-dominant” structure, whereby single-loop ...
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A multivariate control median test
Journal of Statistical Planning and Inference, 1999zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Park, Hyo-Il, Desu, M. M.
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Multivariate Control Chart Based on Multivariate Smirnov Test
Communications in Statistics - Simulation and Computation, 2014Robust control charts are useful in statistical process control (SPC) when there is limited knowledge about the underlying process distribution, especially for multivariate observations. This article develops a new robust and self-starting multivariate procedure based on multivariate Smirnov test (MST), which integrates a multivariate two-sample ...
Maoyuan Zhou +3 more
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An Approach to Multivariable Control of Manipulators
Journal of Dynamic Systems, Measurement, and Control, 1987The paper presents simple schemes for multivariable control of multiple-joint robot manipulators in joint and Cartesian coordinates. The joint control scheme consists of two independent multivariable feedforward and feedback controllers. The feedforward controller is the minimal inverse of the linearized model of robot dynamics and contains only ...
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QUALITY CONTROL WITH MULTIVARIATE DATA
Australian Journal of Statistics, 1992SummaryThe paper examines statistical process control of bivariate and multivariate data, using in particular the multivariate equivalents of the univariate Shewhart chart, CUSUM chart and the Exponentially Weighted Moving Average chart. This illustrates the usefulness of Principal Component methods in statistical process control with multivariate data.
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Ensuring integral controllability for robust multivariable control
Computers & Chemical Engineering, 2016Abstract Integral controllability (IC) is a desired property of multivariable models used in robust controller design. IC requires satisfaction of eigenvalue-based inequalities involving the real process and identified model. Design of experiments for identification of models that satisfy these inequalities is cumbersome.
Shyam Panjwani, Michael Nikolaou
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Anti-Windup Designs for Multivariable Controllers
Automatica, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Youbin Peng +3 more
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Adaptive Control of Multivariable Systems
1985Abstract : During this period the Principal Investigator wrote six technical papers. Titles are: New directions in parameter adaptive control, Adaptive stabilization of linear systems with unknown high frequency, A smooth algorithm for adaptive stabilization of a discrete linear system with an unknown high frequency gain, A 4(n+1)-dimensional model ...
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Decentralized control of linear multivariable systems
Automatica, 1975Abstract This paper studies the effects of decentralized feedback on the closed-loop properties of jointly controllable, jointly observable k-channel linear systems. Channel interactions within such systems are described by means of suitably defined directed graphs.
J. P. Corfmat, A. Stephen Morse
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Multivariable Structure of Fuzzy Control Systems
IEEE Transactions on Systems, Man, and Cybernetics, 1986Application of fuzzy set theory to the design of control systems has led to interest in the description of multivariable fuzzy systems. The authors present an idea for the solution of multivariable fuzzy equations by decomposition of a multivariable fuzzy system into a set of one- dimensional systems. The authors use the block diagram representation of
Madan M. Gupta +2 more
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