1. What are the contributions in this paper?
In this paper, minimum variance control is applied to non-minimum phase plants augmented with adaptive compensators.
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Minimum Variance Control Harnessed for Non-Minimum-Phase Plants
R. Kumar,John B. Moore +1 more
15
TL;DR: In this paper, minimum variance control is applied to non-minimum phase plants augmented with adaptive compensators, where the objective of the compensators is to achieve, asymptotically, a minimum phase property for the augmented plant.
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About: This article is published in IFAC Proceedings Volumes. The article was published on 01 Aug 1981. and is currently open access. The article focuses on the topics: Adaptive control & Stochastic control.
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Citations
Generalized minimum variance control law revisited
TL;DR: In this paper, it was shown that the controller has poor stability characteristics on non-minimum phase systems and that the magnitude of the error weighting term must be severely restricted in some problems if stability is to be maintained.
44
Global convergence of output error recursions in colored noise
John B. Moore
- 01 Dec 1981
TL;DR: Under reasonable conditions, the algorithms achieve global convergence of the one-step-ahead prediction error to the additive independent (possible colored) measurement noise.
25
Technical communique: On adaptive minimum variance regulation for non-minimum phase plants
R. Kumar,John B. Moore +1 more
TL;DR: This paper presents only the discrete-time adaptive regulator version of the adaptive pole assignment scheme, which has interpretations as an adaptive quadratic index minimizing procedure and also as an Adaptive pole assignment algorithm.
18
Patent
Decentralized cautious adaptive control system
Abhijit J. M. Chakravarty,Dagfinn Gangsaas,John B. Moore +2 more
- 19 Nov 1987
TL;DR: In this article, an output vector produced by a plant in response to an input vector is filtered by a plurality of bandpass filters, each filter having a different pass band, and a filtered output vector from each filter is provided as input to a separate adaptive feedback controller, and feedback vectors produced by the separate controllers are summed to provide the input vector to the plant.
17
Stochastic Adaptive Control via Consistent Parameter Estimation
TL;DR: In this article, the convergence analysis for stochastic adaptive control of linear discrete-time systems is developed for a wide class of control schemes with the property that when there is consistant deterministic plant parameter estimation, closed loop stability is achieved.
12
References
Linear Optimal Control
Abstract: GMRES: A Generalized Minimal Residual Algorithm for Dr. Gregory L. Plett's HomepageGitHub python-control/python-control: The Python Control Textbook: Dynamic Programming and Optimal ControlIET Digital Library: IET Control Theory & ApplicationsRobust Control Theory Carnegie Mellon UniversityDynamic Programming and Optimal Control – Institute for Optimal control WikipediaLecture Notes | Principles of Optimal Control What is disturbance rejection in motion control systems?Linear–quadratic–Gaussian control Wikipedia(PDF) MODERN CONTROL SYSTEMS SOLUTION MANUAL DORF ...Data-driven optimal control with a relaxed linear program Python Control Systems Library — Python Control Systems Electrical and Computer EngineeringElectric linear actuators for smooth, intelligent Ch. 8 Linear Quadratic RegulatorsMathematical Modeling of Systems EngineeringOptimal Control TheoryLinear Motion Linear Stages Translation Stages Dover (PDF) Control Systems in Robotics: A ReviewMatthew Monnig Peet's Home Page Arizona State UniversityRobust output feedback model predictive control for Ex linear luminaires with LEDs Explosion Hazard SystemsElectrical & Systems Engineering (ESE) < University of Constrained Optimal Control: Piecewise Affine And Linear [PDF] Control Systems Engineering By A.Nagoor Kani Book EE263 Introduction to Linear Dynamical SystemsLinear-Quadratic-Integral control MATLAB lqiOptimal Control Methods For Linear Discrete Time Economic Overshoot and undershoot in servo control systemsLinear Matrix Inequalities in System and Control Theory
2.1K
Discrete Time Stochastic Adaptive Control
TL;DR: It is shown that, with probability one, the algorithm will ensure the system inputs and outputs are sample mean square bounded and the conditional mean square output tracking error achieves its global minimum possible value for linear feedback control.
429
Discrete time stochastic adaptive control
Graham C. Goodwin,Peter J. Ramadge,Peter E. Caines +2 more
- 01 Jan 1979
TL;DR: It is shown that, with probability one, the algorithm will ensure the system inputs and outputs are sample mean square bounded and the mean square output tracking error achieves its global minimum possible value for linear feedback control.
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