scholarly journals Generalization of the FOPDT Model for Identification and Control Purposes

Processes ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 682 ◽  
Author(s):  
Cristina I. Muresan ◽  
Clara M. Ionescu
Keyword(s):  
Real Life ◽  
Parameter Design ◽  
Dynamic Feedback ◽  
Discussion Section ◽  
Stability Margins ◽  
Closed Loops ◽  
First Order ◽  
Design Systems ◽  
The Stability ◽  
And Control

This paper proposes a theoretical framework for generalization of the well established first order plus dead time (FOPDT) model for linear systems. The FOPDT model has been broadly used in practice to capture essential dynamic response of real life processes for the purpose of control design systems. Recently, the model has been revisited towards a generalization of its orders, i.e., non-integer Laplace order and fractional order delay. This paper investigates the stability margins as they vary with each generalization step. The relevance of this generalization has great implications in both the identification of dynamic processes as well as in the controller parameter design of dynamic feedback closed loops. The discussion section addresses in detail each of this aspect and points the reader towards the potential unlocked by this contribution.

scholarly journals Full Characterization of Act-and-wait Control for First-order Unstable Lag Processes

2010 ◽  
Vol 16 (7-8) ◽  
pp. 1209-1233 ◽  
Author(s):  
T. Insperger ◽  
P. Wahi ◽  
A. Colombo ◽  
G. Stépán ◽  
M. Di Bernardo ◽  
...  
Keyword(s):  
Time Delay ◽  
Feedback Systems ◽  
Periodic Control ◽  
First Order ◽  
Full Characterization ◽  
The Stability ◽  
And Control ◽  
Time Periodic ◽  
Special Case

Act-and-wait control is a special case of time-periodic control for systems with feedback delay, where the control gains are periodically switched on and off in order to stabilize otherwise unstable systems. The stability of feedback systems in the presence of time delay is a challenging problem. In this paper, we show that the act-and-wait type time-periodic control can always provide deadbeat control for first-order unstable lag processes with any (large but) fixed value of the time delay in the feedback loop. A full characterization of this act-and-wait controller with respect to the system and control parameters is given based on performance and robustness against disturbances.

On the analysis and control of hyperbolic systems associated with vibrating networks

1994 ◽  
Vol 124 (1) ◽  
pp. 77-104 ◽  
Author(s):  
J. E. Lagnese ◽  
G. Leugering ◽  
E. J. P. G. Schmidt
Keyword(s):  
Hyperbolic Systems ◽  
Three Dimensional ◽  
Exact Controllability ◽  
General Linear Model ◽  
Regularity Of Solutions ◽  
Closed Loops ◽  
One Dimensional ◽  
First Order ◽  
And Control ◽  
First Time

In this paper a general linear model for vibrating networks of one-dimensional elements is derived. This is applied to various situations including nonplanar networks of beams modelled by a three-dimensional variant on the Timoshenko beam, described for the first time in this paper. The existence and regularity of solutions is established for all the networks under consideration. The methods of first-order hyperbolic systems are used to obtain estimates from which exact controllability follows for networks containing no closed loops.

scholarly journals Dynamics of the Rumor-Spreading Model with Control Mechanism in Complex Network

2022 ◽  
Vol 2022 ◽  
pp. 1-17
Author(s):  
Wei Zhang ◽  
Hongyong Deng ◽  
Xingmei Li ◽  
Huan Liu
Keyword(s):  
Social Order ◽  
Real Life ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Rumor Spreading ◽  
Unique Existence ◽  
Spreading Model ◽  
The Stability ◽  
And Control ◽  
Theoretical Results

The spread of rumors has a great impact on social order, people’s psychology, and life. In recent years, the application of rumor-spreading models in complex networks has received extensive attention. Taking the management and control of rumors by relevant departments in real life into account, the SIDRQ rumor-spreading model that combines forgetting mechanism, immune mechanism, and suspicion mechanism and guides on a uniform network is established in this paper. Then, the basic reproductive number of the system and the unique existence of the solution are discussed, and the stability of the system is analyzed using the basic reproductive number, Lyapunov function, and Lienard and Chipart theorem; furthermore, the basic reproductive number may not be able to deduce the stability of the system and a counterexample is given. Finally, the influence of different parameters on the spread of rumors is studied, and the validity of the theoretical results is verified.

Robust stabilization and control using fractional order integrator

2016 ◽  
Vol 39 (10) ◽  
pp. 1559-1576 ◽  
Author(s):  
Amina Ben Hmed ◽  
Messaoud Amairi ◽  
Mohamed Aoun
Keyword(s):  
Stability Boundary ◽  
Robust Stabilization ◽  
Smith Predictor ◽  
Order System ◽  
Stabilization Problem ◽  
Stabilizing Controller ◽  
First Order ◽  
Analytic Expressions ◽  
The Stability ◽  
And Control

This paper addresses the robust stabilization problem of first-order uncertain systems. To treat the robust stabilization problem, an interval-based stabilization method using stability conditions of the non-commensurate elementary fractional transfer function of the second kind is developed. Some analytic expressions are determined to compute the set of all stabilizing controller parameters and plot the stability boundary. A robust performance control is also developed to fulfil some desired time-domain performances as the iso-overshoot property. The fractional controller can be used combined with the Smith predictor to control a first-order system with time delay and achieve desired specifications. Numerical examples are presented to illustrate the obtained results.

scholarly journals Data-Driven Stability Assessment of Multilayer Long Short-Term Memory Networks

2021 ◽  
Vol 11 (4) ◽  
pp. 1829
Author(s):  
Davide Grande ◽  
Catherine A. Harris ◽  
Giles Thomas ◽  
Enrico Anderlini
Keyword(s):  
Neural Network ◽  
Network Architecture ◽  
Short Term Memory ◽  
Moving Average ◽  
Machine Learning Algorithms ◽  
Physical Models ◽  
Data Driven ◽  
The Stability ◽  
And Control ◽  
Nonlinear Autoregressive

Recurrent Neural Networks (RNNs) are increasingly being used for model identification, forecasting and control. When identifying physical models with unknown mathematical knowledge of the system, Nonlinear AutoRegressive models with eXogenous inputs (NARX) or Nonlinear AutoRegressive Moving-Average models with eXogenous inputs (NARMAX) methods are typically used. In the context of data-driven control, machine learning algorithms are proven to have comparable performances to advanced control techniques, but lack the properties of the traditional stability theory. This paper illustrates a method to prove a posteriori the stability of a generic neural network, showing its application to the state-of-the-art RNN architecture. The presented method relies on identifying the poles associated with the network designed starting from the input/output data. Providing a framework to guarantee the stability of any neural network architecture combined with the generalisability properties and applicability to different fields can significantly broaden their use in dynamic systems modelling and control.

scholarly journals Derivative-Free King’s Scheme for Multiple Zeros of Nonlinear Functions

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1242
Author(s):  
Ramandeep Behl ◽  
Sonia Bhalla ◽  
Eulalia Martínez ◽  
Majed Aali Alsulami
Keyword(s):  
Iterative Methods ◽  
Fourth Order ◽  
Order Of Convergence ◽  
Real Life ◽  
Multiple Roots ◽  
Computational Results ◽  
Nonlinear Functions ◽  
First Order ◽  
Life Problems ◽  
Derivative Free

There is no doubt that the fourth-order King’s family is one of the important ones among its counterparts. However, it has two major problems: the first one is the calculation of the first-order derivative; secondly, it has a linear order of convergence in the case of multiple roots. In order to improve these complications, we suggested a new King’s family of iterative methods. The main features of our scheme are the optimal convergence order, being free from derivatives, and working for multiple roots (m≥2). In addition, we proposed a main theorem that illustrated the fourth order of convergence. It also satisfied the optimal Kung–Traub conjecture of iterative methods without memory. We compared our scheme with the latest iterative methods of the same order of convergence on several real-life problems. In accordance with the computational results, we concluded that our method showed superior behavior compared to the existing methods.

Personal Information as Symmetry Breaker in Disagreements

Philosophy ◽  
2021 ◽  
pp. 1-20
Author(s):  
Diego E. Machuca
Keyword(s):  
Personal Information ◽  
Conscious Experience ◽  
Real Life ◽  
Cognitive Capacities ◽  
First Order ◽  
Natural Reaction ◽  
Epistemic Standing

Abstract When involved in a disagreement, a common reaction is to tell oneself that, given that the information about one's own epistemic standing is clearly superior in both amount and quality to the information about one's opponent's epistemic standing, one is justified in one's confidence that one's view is correct. In line with this natural reaction to disagreement, some contributors to the debate on its epistemic significance have claimed that one can stick to one's guns by relying in part on information about one's first-order evidence and the functioning of one's cognitive capacities. In this article, I argue that such a manoeuvre to settle controversies encounters the problem that both disputants can make use of it, the problem that one may be wrong about one's current conscious experience, and the problem that it is a live possibility that many of one's beliefs are the product of epistemically distorting factors. I also argue that, even if we grant that personal information is reliable, when it comes to real-life rather than idealized disagreements, the extent of the unpossessed information about one's opponent's epistemic standing provides a reason for doubting that personal information can function as a symmetry breaker.

scholarly journals Drone Deep Reinforcement Learning: A Review

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 999
Author(s):  
Ahmad Taher Azar ◽  
Anis Koubaa ◽  
Nada Ali Mohamed ◽  
Habiba A. Ibrahim ◽  
Zahra Fathy Ibrahim ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
State Of The Art ◽  
Real Life ◽  
Environment Monitoring ◽  
Simulated Environments ◽  
Infrastructure Inspection ◽  
Remote Sensing Mapping ◽  
And Control ◽  
The Military ◽  
Uav Navigation

Unmanned Aerial Vehicles (UAVs) are increasingly being used in many challenging and diversified applications. These applications belong to the civilian and the military fields. To name a few; infrastructure inspection, traffic patrolling, remote sensing, mapping, surveillance, rescuing humans and animals, environment monitoring, and Intelligence, Surveillance, Target Acquisition, and Reconnaissance (ISTAR) operations. However, the use of UAVs in these applications needs a substantial level of autonomy. In other words, UAVs should have the ability to accomplish planned missions in unexpected situations without requiring human intervention. To ensure this level of autonomy, many artificial intelligence algorithms were designed. These algorithms targeted the guidance, navigation, and control (GNC) of UAVs. In this paper, we described the state of the art of one subset of these algorithms: the deep reinforcement learning (DRL) techniques. We made a detailed description of them, and we deduced the current limitations in this area. We noted that most of these DRL methods were designed to ensure stable and smooth UAV navigation by training computer-simulated environments. We realized that further research efforts are needed to address the challenges that restrain their deployment in real-life scenarios.

scholarly journals Bleaching of chlorophylls by UV irradiation in vitro: The effects on chlorophyll organization in acetone and n-hexane

2008 ◽  
Vol 73 (3) ◽  
pp. 271-282 ◽  
Author(s):  
Jelena Zvezdanovic ◽  
Dejan Markovic
Keyword(s):  
Uv Irradiation ◽  
Photosynthetic Pigments ◽  
Energy Input ◽  
First Order ◽  
First Order Kinetics ◽  
Uv Photons ◽  
The Stability ◽  
Major Factors

The stability of chlorophylls toward UV irradiation was studied by Vis spectrophotometry in extracts containing mixtures of photosynthetic pigments in acetone and n-hexane. The chlorophylls underwent destruction (bleaching) obeying first-order kinetics. The bleaching was governed by three major factors: the energy input of the UV photons, the concentration of the chlorophylls and the polarity of the solvent, implying different molecular organizations of the chlorophylls in the two solvents.

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