Analysis of multi-loop multi-rate digital control systems

Konar, A. F.; Lee, John

doi:10.1109/cdc.1976.267774

Cited by 5 publications

(5 citation statements)

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“…The control u is to be sampled and held at time instants t k , with all elements of u possibly sampled at different rates. The discrete-time dynamics of the continuous plant are described by (2) where and the control vector, u, has been partitioned into subsets u f and u s to signify those controls computed at the base rate and those scheduled at lower rates, respectively.…”

Section: Summary Of the Design Proceduresmentioning

confidence: 99%

A New Technique for Multirate Digital Control Design and Sample Rate Selection

Glasson¹

1982

Journal of Guidance, Control, and Dynamics

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A new approach for designing multirate digital flight control systems based on optimal control theory is described. The error rejection properties of control systems designed by the, new technique are investigated through a case study. The example considered is the F-14 aircraft controlled by a multirate proportional-plusintegral controller. The aircraft/controller system is "flown" through a turbulent atmosphere; a covariance analysis of state variable errors determines the ability of the controller to reject turbulence-induced errors. The controller sample rate and control sequence are varied to determine their influence on the disturbance rejection properties of the controller. Finally, a sample rate optimization scheme based on performance/computation tradeoff is presented.

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Section: Summary Of the Design Proceduresmentioning

confidence: 99%

A New Technique for Multirate Digital Control Design and Sample Rate Selection

Glasson¹

1982

Journal of Guidance, Control, and Dynamics

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“…In , gain‐scheduled controllers are designed for multi‐rate sampled‐data systems and applied to a rotorcraft model. A common drawback of is that the sampling‐rate ratios of the sensors are assumed to be rational numbers (commensurate samplings). The commensurate sampling assumption does not hold in practice because the sampling interval of each sensor is usually not uniform.…”

Section: Introductionmentioning

confidence: 99%

“…In contrast to , this paper addresses sensor allocation (also known as sensor placement) with guaranteed exponential stability for linear multi‐rate sampled‐data systems. Let there exist a continuous‐time linear controller that stabilizes a linear system.…”

Section: Introductionmentioning

confidence: 99%

“…Stability analysis and controller synthesis of multi-rate sampled-data systems are practically relevant problems and have attracted researchers for several decades [1][2][3][4][5][6][7][8][9][10][11][12][13]. A frequency domain technique for dual-rate sampled-data systems (with 2:1 and 4:1 sampling ratios) is developed in [2] and applied to the Space Shuttle flight control system. In [4], the controller synthesis problem for linear multi-rate sampled-data systems is studied in discrete time using pole placement.…”

Section: Introductionmentioning

confidence: 99%

“…In [8], gain-scheduled controllers are designed for multi-rate sampled-data systems and applied to a rotorcraft model. A common drawback of [1][2][3][4][5][6][7][8][9] is that the sampling-rate ratios of the sensors are assumed to be rational numbers (commensurate samplings). The commensurate where y represents the distance from the line y D 0, and r are the heading angle and its time derivative, respectively, v D 0:25 (m/s) is the unicycle's velocity, u denotes the torque input about the´axis, I D 1 (kg m 2 ) is the unicycle's moment of inertia with respect to its center of mass, and k D 0:15 (Nm s) is the damping coefficient.…”

Section: Introductionmentioning

confidence: 99%

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Sensor allocation with guaranteed exponential stability for linear multi-rate sampled-data systems

Moarref

Rodrigues

2015

Int. J. Robust. Nonlinear Control

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Summary This paper addresses sensor allocation with guaranteed exponential stability for linear multi‐rate sampled‐data systems. It is assumed that a continuous‐time linear plant is exponentially stabilized by a continuous‐time linear controller. Given sensors with incommensurate sampling rates, the objective is to allocate each state to a sensor such that the resulting multi‐rate sampled‐data system remains exponentially stable. The main contributions of this paper are twofold. First, we propose sufficient Krasovskii‐based conditions to partition the state vector among sensors such that exponential stability of the closed‐loop system is guaranteed. Second, the problem of finding a partition that guarantees exponential stability is cast as a mixed integer program subject to linear matrix inequalities. The theoretical results are successfully applied to two robotic problems: path‐following in unicycles and hovering in quadrotors. Copyright © 2015 John Wiley & Sons, Ltd.

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Introduction

Bavafa-Toosi¹

2019

Introduction to Linear Control Systems

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Analysis of multi-loop multi-rate digital control systems

Cited by 5 publications

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A New Technique for Multirate Digital Control Design and Sample Rate Selection

A New Technique for Multirate Digital Control Design and Sample Rate Selection

Sensor allocation with guaranteed exponential stability for linear multi-rate sampled-data systems

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