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>

scholarly journals Online Identification of Lithium-ion Battery Model Parameters with Initial Value Uncertainty and Measurement Noise

2021 ◽  
Author(s):  
Xinghao Du ◽  
Jinhao Meng ◽  
Kailong Liu ◽  
Yingmin Zhang ◽  
Shunli Wang ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Least Squares ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Recursive Least Squares ◽  
Model Parameters ◽  
Initial Value ◽  
Online Identification ◽  
Noise Disturbances ◽  
The Cost

Abstract Online parameter identification is essential for the accuracy of the battery Equivalent Circuit Model (ECM). The traditional Recursive Least Squares (RLS) method is easily biased with the noise disturbances from sensors, which degrades the modeling accuracy in practice. Meanwhile, the Recursive Total Least Squares (RTLS) method can deal with the noise interferences, but the parameter slowly converges to the reference with initial value uncertainty. To alleviate the above issues, this paper proposes a co-estimation framework utilizing the advantages of RLS and RTLS for a higher parameter identification performance of the battery ECM. RLS converges quickly by updating the parameters along the gradient of the cost function. RTLS is applied to attenuate the noise effect once the parameters have converged. Both simulation and experimental results prove that the proposed method has good accuracy, fast convergence rate, and also robustness against noise corruption.

An LQ Approach to Active Control of Vibrations in Helicopters

1996 ◽  
Vol 118 (3) ◽  
pp. 482-488 ◽  
Author(s):  
Sergio Bittanti ◽  
Fabrizio Lorito ◽  
Silvia Strada
Keyword(s):  
Optimal Control ◽  
Active Control ◽  
Linear Quadratic ◽  
Control Effort ◽  
Vibration Effect ◽  
Suitable Definition ◽  
Lq Optimal Control ◽  
The One ◽  
Definition Of ◽  
And Control

In this paper, Linear Quadratic (LQ) optimal control concepts are applied for the active control of vibrations in helicopters. The study is based on an identified dynamic model of the rotor. The vibration effect is captured by suitably augmenting the state vector of the rotor model. Then, Kalman filtering concepts can be used to obtain a real-time estimate of the vibration, which is then fed back to form a suitable compensation signal. This design rationale is derived here starting from a rigorous problem position in an optimal control context. Among other things, this calls for a suitable definition of the performance index, of nonstandard type. The application of these ideas to a test helicopter, by means of computer simulations, shows good performances both in terms of disturbance rejection effectiveness and control effort limitation. The performance of the obtained controller is compared with the one achievable by the so called Higher Harmonic Control (HHC) approach, well known within the helicopter community.

Online parameter estimation and adaptive control with limited information in structures

2021 ◽  
pp. 107754632110191
Author(s):  
Fereidoun Amini ◽  
Elham Aghabarari
Keyword(s):  
Parameter Estimation ◽  
Adaptive Control ◽  
Least Squares ◽  
Control Algorithm ◽  
Least Squares Method ◽  
Recursive Least Squares ◽  
Limited Information ◽  
Online Identification ◽  
Recursive Least Squares Method ◽  
Adaptive Control Algorithm

An online parameter estimation is important along with the adaptive control, that is, a time-dependent plant. This study uses both online identification and the simple adaptive control algorithm with velocity feedback. The recursive least squares method was used to identify the stiffness and damping parameters of the structure’s stories. Identification was carried out online without initial estimation and only by measuring the structural responses. The limited information regarding sensor measurements, parameter convergence, and the effects of the covariance matrix is examined. The integration of the applied online identification, the appropriate reference model selection in simple adaptive control, and adopting the proportional integral filter was used to limit the structural control response error. Some numerical examples are simulated to verify the ability of the proposed approach. Despite the limited information, the results show that the simultaneous use of online identification with the recursive least squares method and simple adaptive control algorithm improved the overall structural performance.

Exakte posenabhängige Strukurmodelle*/Accurate virtual machine tool structures - Online-identification of the general model of a lightweight machine tool structure with pose-dependent dynamic behavior

2017 ◽  
Vol 107 (05) ◽  
pp. 323-328
Author(s):  
S. Apprich ◽  
F. Wulle ◽  
A. Prof. Pott ◽  
A. Prof. Verl
Keyword(s):  
Machine Tool ◽  
Least Squares ◽  
Dynamic Behavior ◽  
Natural Frequencies ◽  
Recursive Least Squares ◽  
Machine Model ◽  
Online Identification ◽  
Working Space ◽  
Machine Tool Structure ◽  
Machine Tool Structures

Serielle Werkzeugmaschinenstrukturen weisen ein posenabhängiges, dynamisches Verhalten auf, wobei die Eigenfrequenzen um mehrere Hertz im Arbeitsraum variieren können. Die genaue Kenntnis dieses Verhaltens gestattet eine verbesserte Regelung der Strukturen. Ein generelles parametrisches Maschinenmodell, dessen Parameter online durch einen Recursive-Least-Squares-Algorithmus an das reale Maschinenverhalten angepasst werden, stellt Informationen über dieses Maschinenverhalten bereit. &nbsp; Serial machine tool structures feature a pose-dependent dynamic behavior with natural frequencies varying by serveral hertz within the working space. The accurate knowledge of this behavior allows an improved control of the structures. A general parametric machine model, whose parameters are adapted online to the actual machine tool behavior by a Recursive Least Squares algorithm, provides information about the pose-dependent dynamic behavior.

scholarly journals Route Planning: B

2021 ◽  
pp. 259-269
Author(s):  
Jean Walrand
Keyword(s):  
Route Planning ◽  
The State ◽  
Control Problems ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Certainty Equivalence ◽  
Markov Decision Problems ◽  
Markov Decision ◽  
The Cost ◽  
Elegant Solution

AbstractThere is a class of control problems that admit a particularly elegant solution: the linear quadratic Gaussian (LQG) problems. In these problems, the state dynamics and observations are linear, the cost is quadratic, and the noise is Gaussian. Section 14.1 explains the theory of LQG problems when one observes the state. Section 14.2 discusses the situation when the observations are noisy and shows the remarkable certainty equivalence property of the solution. Section 14.3 explains how noisy observations affect Markov decision problems.

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

scholarly journals Delayed Stochastic Linear-Quadratic Control Problem and Related Applications

2012 ◽  
Vol 2012 ◽  
pp. 1-22 ◽  
Author(s):  
Li Chen ◽  
Zhen Wu ◽  
Zhiyong Yu
Keyword(s):  
Optimal Control ◽  
Differential Equations ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Stochastic Differential Equations ◽  
Backward Stochastic Differential Equations ◽  
Delay System ◽  
Linear Quadratic ◽  
Stochastic Linear System ◽  
And Control

We discuss a quadratic criterion optimal control problem for stochastic linear system with delay in both state and control variables. This problem will lead to a kind of generalized forward-backward stochastic differential equations (FBSDEs) with Itô’s stochastic delay equations as forward equations and anticipated backward stochastic differential equations as backward equations. Especially, we present the optimal feedback regulator for the time delay system via a new type of Riccati equations and also apply to a population optimal control problem.

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