A DESIGN METHOD OF GENERALIZED MINIMUM VARIANCE CONTROL CONSIDERING SAFETY OF SAMPLED-DATA SYSTEMS

2007 ◽  
Author(s):  
TAKAO SATO ◽  
SHIRO MASUDA ◽  
AKIRA INOUE
Keyword(s):  
Design Method ◽  
Minimum Variance ◽  
Data Systems ◽  
Sampled Data ◽  
Minimum Variance Control

scholarly journals Periodic Switched Control of Dual-Rate Sampled-Data Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-16
Author(s):  
Dawei Zhang ◽  
Wei Bai ◽  
Xinchun Jia
Keyword(s):  
Design Method ◽  
Switched System ◽  
Data Systems ◽  
State Variables ◽  
Sampled Data ◽  
Data Control ◽  
Switched Control ◽  
Rate Design ◽  
Input Delays ◽  
Delay Dependent

This paper is concerned with the periodic switched control of a linear dual-rate sampled-data system. The state variables of the continuous-time plant are sampled by two types of sensors. The ratio of two sampling rates is assumed to be a rational number. Depending on whether the sampled-data of state variables at two sampling rates is available simultaneously or separately, a periodic switched controller is constructed. Applying an input delay approach, the closed-loop system is modeled as a switched system with subsystems having different input delays. Some delay-dependent criteria for theH∞performance of the switched system and the existence of the switched controller are derived by employing a Lyapunov-Krasovskii functional that includes information about two sampling periods. The dual-rate sampled-data control of a vehicle dynamic system is given to show that the proposed method is effective and it can achieve a betterH∞control performance than the single-rate design method.

Self-Tuning Generalized Minimum Variance Control Based on On-Demand Type Feedback Controller

2016 ◽  
Vol 28 (5) ◽  
pp. 674-680 ◽  
Author(s):  
Akira Yanou ◽  
◽  
Mamoru Minami ◽  
Takayuki Matsuno
Keyword(s):  
Design Method ◽  
Strong Stability ◽  
Minimum Variance ◽  
Feedback Controller ◽  
Feedback Signal ◽  
Minimum Variance Control ◽  
On Demand ◽  
Control Objective ◽  
Self Tuning ◽  
Type Feedback

[abstFig src='/00280005/08.jpg' width='300' text='Feedback signal is generated on demand' ] This paper proposes a design method of self-tuning generalized minimum variance control based on on-demand type feedback controller. A controller, such as generalized minimum variance control (GMVC), generalized predictive control (GPC) and so on, can be extended by using coprime factorization. Then new design parameter is introduced into the extended controller, and the parameter can re-design the characteristic of the extended controller, keeping the closed-loop characteristic that way. Although strong stability systems can be obtained by the extended controller in order to design safe systems, focusing on feedback signal, the extended controller can adjust the magnitude of the feedback signal. That is, the proposed controller can drive the magnitude of the feedback signal to zero if the control objective was achieved. In other words the feedback signal by the proposed method can appear on demand of achieving the control objective. Therefore this paper proposes on-demand type feedback controller using self-tuning GMVC for plant with uncertainty. A numerical example is shown in order to check the characteristic of the proposed method.

scholarly journals Disturbance Modelling for Minimum Variance Control in Adaptive Optics Systems Using Wavefront Sensor Sampled-Data

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3054
Author(s):  
María Coronel ◽  
Rodrigo Carvajal ◽  
Pedro Escárate ◽  
Juan C. Agüero
Keyword(s):  
Adaptive Optics ◽  
Minimum Variance ◽  
Likelihood Method ◽  
Wavefront Sensor ◽  
Sampled Data ◽  
Minimum Variance Control ◽  
Astronomical Images ◽  
Large Telescopes ◽  
Identification Techniques ◽  
Damped Oscillators

Modern large telescopes are built based on the effectiveness of adaptive optics systems in mitigating the detrimental effects of wavefront distortions on astronomical images. In astronomical adaptive optics systems, the main sources of wavefront distortions are atmospheric turbulence and mechanical vibrations that are induced by the wind or the instrumentation systems, such as fans and cooling pumps. The mitigation of wavefront distortions is typically attained via a control law that is based on an adequate and accurate model. In this paper, we develop a modelling technique based on continuous-time damped-oscillators and on the Whittle’s likelihood method to estimate the parameters of disturbance models from wavefront sensor time-domain sampled-data. On the other hand, when the model is not accurate, the performance of the minimum variance controller is affected. We show that our modelling and identification techniques not only allow for more accurate estimates, but also for better minimum variance control performance. We illustrate the benefits of our proposal via numerical simulations.

Digital Control Design Via Convex Optimization

1993 ◽  
Vol 115 (4) ◽  
pp. 579-586 ◽  
Author(s):  
R. E. Avedon ◽  
B. A. Francis
Keyword(s):  
Convex Optimization ◽  
Operator Theory ◽  
Design Method ◽  
Numerical Algorithms ◽  
Optimization Techniques ◽  
Data Systems ◽  
Sampled Data ◽  
Design Heuristics ◽  
Stability Robustness ◽  
Data Design

A design method for sampled-data systems is presented incorporating robust control theory and convex optimization techniques. The technique is developed using operator theory applied to the relevant input-output operators for both performance and stability robustness. Numerical algorithms and an example for the SISO case are presented to explore some traditional sampled-data design heuristics.

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