scholarly journals Minimal Feedback Optimal Control of Linear-Quadratic-Gaussian Systems: No Communication is also a Communication

2020 ◽  
Vol 53 (2) ◽  
pp. 2201-2207
Author(s):  
Dipankar Maity ◽  
John S. Baras
Keyword(s):  
Optimal Control ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Feedback Optimal Control

Linear Quadratic Gaussian Optimal Control for Human Eye Aberration Correction

2014 ◽  
Vol 51 (4) ◽  
pp. 041102
Author(s):  
王波 Wang Bo ◽  
钮赛赛 Niu Saisai ◽  
吴卫明 Wu Weiming
Keyword(s):  
Optimal Control ◽  
Aberration Correction ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Human Eye

Risk-sensitive linear/quadratic/gaussian control

1981 ◽  
Vol 13 (4) ◽  
pp. 764-777 ◽  
Author(s):  
P. Whittle
Keyword(s):  
Optimal Control ◽  
Kalman Filter ◽  
Risk Aversion ◽  
Separation Theorem ◽  
Linear Quadratic ◽  
Criterion Function ◽  
Linear Quadratic Gaussian ◽  
State Estimate ◽  
Certainty Equivalence ◽  
Risk Sensitive

The conventional linear/quadratic/Gaussian assumptions are modified in that minimisation of the expectation of cost G defined by (2) is replaced by minimisation of the criterion function (5). The scalar –θ is a measure of risk-aversion. It is shown that modified versions of certainty equivalence and the separation theorem still hold, that optimal control is still linear Markov, and state estimate generated by a version of the Kalman filter. There are also various new features, remarked upon in Sections 5 and 7. The paper generalises earlier work of Jacobson.

Microclimate control of a greenhouse by adaptive Generalized Linear Quadratic strategy

2018 ◽  
Vol 11 (1) ◽  
pp. 377 ◽  
Author(s):  
Mohamed Essahafi ◽  
Mustapha Ait Lafkih
Keyword(s):  
Optimal Control ◽  
Least Squares ◽  
Recursive Least Squares ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Advanced Technique ◽  
Online Identification ◽  
State Models ◽  
The Cost ◽  
And Control

<p>To highlight the conceptual aspects related to the implementation of techniques optimal control in the form state, we present in this paper, the identification and control of the temperature and humidity of the air inside a greenhouse. Using respectively an online identification based on the recursive least squares with forgotten Factor method and the multivariable adaptive linear quadratic Gaussian approach which the advanced technique (LQG) is presented.  The design of this controller parameters is based on state models identified directly from measured greenhouse data. hence the performances of the controller developed are illustrated by different tests and simulations on identified models of a greenhouse. Discussions on the results obtained are then processed in the paper to show the effectiveness of the controller in terms of stability and optimization of the cost of control.</p>

Multi-Dimension Uncertain Linear Quadratic Optimal Control with Cross Term

2015 ◽  
Vol 19 (5) ◽  
pp. 670-675 ◽  
Author(s):  
Yuefen Chen ◽  
◽  
Bo Li
Keyword(s):  
Differential Equation ◽  
Optimal Control ◽  
Linear Feedback ◽  
Linear Quadratic ◽  
Linear Quadratic Optimal Control ◽  
Riccati Differential Equation ◽  
Cross Term ◽  
Lq Optimal Control ◽  
Quadratic Optimal Control ◽  
Feedback Optimal Control

In this paper, we consider a multi-dimension uncertain linear quadratic (LQ) optimal control with cross term. With the aid of the equation of optimality of a general multi-dimension uncertain optimal control, we present a necessary and sufficient condition for the existence of optimal linear feedback optimal control which is associated with a Riccati differential equation. Moreover, some properties of the solution for the Riccati differential equation are discussed. Furthermore, the uniqueness of the feedback optimal control for the uncertain linear quadratic optimal control with cross term is proved. Finally, as an application, an example is presented to illustrate the theory obtained.

LQG Control for Nonstandard Singularly Perturbed Discrete-Time Systems

2004 ◽  
Vol 126 (4) ◽  
pp. 860-864 ◽  
Author(s):  
Beom-Soo Kim ◽  
Young-Joong Kim ◽  
Myo-Taeg Lim
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Discrete Time ◽  
Singularly Perturbed ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Reduced Order ◽  
Discrete Time Systems ◽  
Time Systems

In this paper we present a control method and a high accuracy solution technique in solving the linear quadratic Gaussian problems for nonstandard singularly perturbed discrete time systems. The methodology that exists in the literature for the solution of the standard singularly perturbed discrete time linear quadratic Gaussian optimal control problem cannot be extended to the corresponding nonstandard counterpart. The solution of the linear quadratic Gaussian optimal control problem is obtained by solving the pure-slow and pure-fast reduced-order continuous-time algebraic Riccati equations and by implementing the pure-slow and pure-fast reduced-order Kalman filters. In order to show the effectiveness of the proposed method, we present the numerical result for a one-link flexible robot arm.

scholarly journals Temperature Control of Stirred Tank Heater using Optimal Control Technique

2020 ◽  
Author(s):  
Mustefa Jibril ◽  
Messay Tadese ◽  
Eliyas Alemayehu
Keyword(s):  
Optimal Control ◽  
Temperature Control ◽  
Open Loop ◽  
Loop System ◽  
Stirred Tank ◽  
Control Technique ◽  
Closed Loop System ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Quadratic Integral

This paper presents the application of optimal control problem in modeling of stirred tank heater temperature control. The analysis of the open loop system shows that the system is not efficient without a controller. Linear Quadratic Gaussian (LQG) and Linear Quadratic Integral (LQI) controllers are used to increase the performance of the system. Comparison of the closed loop system with the proposed controllers have been done with Matlab/Simulink Toolbox and a promising results have been analyzed.

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