scholarly journals Weather and Climate Manipulation as an Optimal Control for Adaptive Dynamical Systems

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Sergei A. Soldatenko
Keyword(s):  
Dynamical System ◽  
Optimal Control ◽  
Control Problem ◽  
Large Scale ◽  
Atmospheric Dynamics ◽  
Climate System ◽  
Chaotic Dynamical System ◽  
Weather And Climate ◽  
Earth’S Climate ◽  
Climate Manipulation

The weather and climate manipulation is examined as an optimal control problem for the earth climate system, which is considered as a complex adaptive dynamical system. Weather and climate manipulations are actually amorphous operations. Since their objectives are usually formulated vaguely, the expected results are fairly unpredictable and uncertain. However, weather and climate modification is a purposeful process and, therefore, we can formulate operations to manipulate weather and climate as the optimization problem within the framework of the optimal control theory. The complexity of the earth’s climate system is discussed and illustrated using the simplified low-order coupled chaotic dynamical system. The necessary conditions of optimality are derived for the large-scale atmospheric dynamics. This confirms that even a relatively simplified control problem for the atmospheric dynamics requires significant efforts to obtain the solution.

TREATMENT OF THE ERROR DUE TO UNRESOLVED SCALES IN SEQUENTIAL DATA ASSIMILATION

2011 ◽  
Vol 21 (12) ◽  
pp. 3619-3626 ◽  
Author(s):  
ALBERTO CARRASSI ◽  
STÉPHANE VANNITSEM
Keyword(s):  
Dynamical System ◽  
Kalman Filter ◽  
Data Assimilation ◽  
Large Scale ◽  
Model Error ◽  
Environmental Modeling ◽  
Sequential Data ◽  
Chaotic Dynamical System ◽  
Error Covariance ◽  
Sequential Data Assimilation

In this paper, a method to account for model error due to unresolved scales in sequential data assimilation, is proposed. An equation for the model error covariance required in the extended Kalman filter update is derived along with an approximation suitable for application with large scale dynamics typical in environmental modeling. This approach is tested in the context of a low order chaotic dynamical system. The results show that the filter skill is significantly improved by implementing the proposed scheme for the treatment of the unresolved scales.

Battery Charge Control With an Electro-Thermal-Aging Coupling

2015 ◽  
Author(s):  
Xiaosong Hu ◽  
Hector E. Perez ◽  
Scott J. Moura
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Thermal Aging ◽  
Large Scale ◽  
Clean Energy ◽  
Battery Charge ◽  
Charge Control ◽  
Highly Nonlinear ◽  
Pseudo Spectral Method

Efficient and safe battery charge control is an important prerequisite for large-scale deployment of clean energy systems. This paper proposes an innovative approach to devising optimally health-conscious fast-safe charge protocols. A multi-objective optimal control problem is mathematically formulated via a coupled electro-thermal-aging battery model, where electrical and aging sub-models depend upon the core temperature captured by a two-state thermal sub-model. The Legendre-Gauss-Radau (LGR) pseudo-spectral method with adaptive multi-mesh-interval collocation is employed to solve the resulting highly nonlinear six-state optimal control problem. Charge time and health degradation are therefore optimally traded off, subject to both electrical and thermal constraints. Minimum-time, minimum-aging, and balanced charge scenarios are examined in detail. The implications of the upper voltage bound, ambient temperature, and cooling convection resistance to the optimization outcome are investigated as well.

scholarly journals The Determination of Feasible Control Variables for Geoengineering and Weather Modification Based on the Theory of Sensitivity in Dynamical Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Sergei A. Soldatenko ◽  
Rafael M. Yusupov
Keyword(s):  
Optimal Control ◽  
Mathematical Models ◽  
General Circulation ◽  
Large Scale ◽  
Baroclinic Instability ◽  
Model Parameters ◽  
Weather Modification ◽  
Control Variables ◽  
Weather And Climate ◽  
Human Operators

Geophysical cybernetics allows for exploring weather and climate modification (geoengineering) as an optimal control problem in which the Earth’s climate system is considered as a control system and the role of controller is given to human operators. In mathematical models used in climate studies control actions that manipulate the weather and climate can be expressed via variations in model parameters that act as controls. In this paper, we propose the “instability-sensitivity” approach that allows for determining feasible control variables in geoengineering. The method is based on the sensitivity analysis of mathematical models that describe various types of natural instability phenomena. The applicability of this technique is illustrated by a model of atmospheric baroclinic instability since this physical mechanism plays a significant role in the general circulation of the atmosphere and, consequently, in climate formation. The growth rate of baroclinic unstable waves is taken as an indicator of control manipulations. The information obtained via calculated sensitivity coefficients is very beneficial for assessing the physical feasibility of methods of control of the large-scale atmospheric dynamics and for designing optimal control systems for climatic processes. It also provides insight into potential future changes in baroclinic waves, as a result of a changing climate.

scholarly journals Closed-loop and congestion control of the global carbon-climate system

2021 ◽  
Vol 165 (1-2) ◽  
Author(s):  
Carlos A. Sierra ◽  
Holger Metzler ◽  
Markus Müller ◽  
Eurika Kaiser
Keyword(s):  
Climate Change ◽  
Dynamical System ◽  
Congestion Control ◽  
Control Problem ◽  
Closed Loop ◽  
Climate System ◽  
Closed Loop Control ◽  
Loop Control ◽  
Dangerous Climate Change ◽  
Global Carbon

AbstractThe global carbon-climate system is a complex dynamical system with multiple feedbacks among components, and to steer this system away from dangerous climate change, it may not be enough to prescribe action according to long-term scenarios of fossil fuel emissions. We introduce here concepts from control theory, a branch of applied mathematics that is effective at steering complex dynamical systems to desired states, and distinguish between open- and closed-loop control. We attempt (1) to show that current scientific work on carbon-climate feedbacks and climate policy more closely resembles the conceptual model of open- than closed-loop control, (2) to introduce a mathematical generalization of the carbon-climate system as a compartmental dynamical system that can facilitate the formal treatment of the closed-loop control problem, and (3) to formulate carbon-climate control as a congestion control problem, discussing important concepts such as observability and controllability. We also show that most previous discussions on climate change mitigation and policy development have relied on an implicit assumption of open-loop control that does not consider frequent corrections due to deviations of goals from observations. Using a reduced complexity model, we illustrate that the problem of managing the global carbon cycle can be abstracted as a network congestion problem, accounting for nonlinear behavior and feedback from a global carbon monitoring system. As opposed to scenarios, the goal of closed-loop control is to develop rules for continuously steering the global carbon-climate system away from dangerous climate change.

Optimal Control of a Multifactor Uncertain System

2019 ◽  
Vol 27 (03) ◽  
pp. 397-414
Author(s):  
Yun Sun ◽  
Yuanguo Zhu
Keyword(s):  
Dynamical System ◽  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Modern Science ◽  
Uncertain System ◽  
Game Model ◽  
Important Research ◽  
Important Research Topic ◽  
Zero Sum

Along with the development of the modern science and technology, people face a lot of data in different areas of production and life. In dealing with these data which include many indeterminant factors, we can use the multifactor uncertain system to describe a dynamical system with uncertain noises. Optimal control problem is an important research topic which aims at finding the optimal strategy in a dynamical system. In this paper, we consider the optimal control problem for the multifactor uncertain system with two evaluation criterions. Then a two person zero sum differential game model in a multifactor uncertain system is discussed. Finally, as an application, our result is used to solve an uncertain portfolio game model.

Northern Tales: A Synthesis of MAGS Atmospheric and Hydrometeorological Research

2007 ◽  
Vol 88 (9) ◽  
pp. 1411-1426 ◽  
Author(s):  
K. K. Szeto ◽  
R. E. Stewart ◽  
M. K. Yau ◽  
J. Gyakum
Keyword(s):  
Large Scale ◽  
Water Cycle ◽  
Climate System ◽  
Atmospheric Flows ◽  
Continental Scale ◽  
Weather And Climate ◽  
Scientific Results ◽  
Two Phases ◽  
Key Aspects ◽  
Physical Features

The Mackenzie Global Energy and Water Cycle Experiment (GEWEX) Study (MAGS) is one of the continental-scale experiments approved specifically by GEWEX to better understand and model water and energy cycling at high latitudes. The project has gone through two phases since its inception in 1994 and conclusion in December 2005. Many scientific results have been achieved through MAGS research to advance our understanding of the Mackenzie River basin climate system. This article is a synthesis of its atmospheric research achievements through an integrative description of the basin's climate system, along with highlights of MAGS research that has advanced our knowledge and understanding of various key aspects of the system. In particular, the significance of MAGS research is discussed in the hancing knowledge of the basin's hydroclimate with focuses on i) the large-scale atmospheric processes that control the transport of water and energy into the basin, and ii) the interactions of the large-scale atmospheric flows with physical features of the basin's environment in affecting the weather and climate of the basin.

scholarly journals An Optimal Control Perspective on Weather and Climate Modification

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 305
Author(s):  
Sergei Soldatenko ◽  
Rafael Yusupov
Keyword(s):  
Optimal Control ◽  
Sensitivity Analysis ◽  
Dynamical Systems ◽  
Weather Conditions ◽  
Model Parameters ◽  
Weather Modification ◽  
Atmospheric Sciences ◽  
Atmospheric Processes ◽  
Weather And Climate ◽  
Earth’S Climate

Intentionally altering natural atmospheric processes using various techniques and technologies for changing weather patterns is one of the appropriate human responses to climate change and can be considered a rather drastic adaptation measure. A fundamental understanding of the human ability to modify weather conditions requires collaborative research in various scientific fields, including, but not limited to, atmospheric sciences and different branches of mathematics. This article being theoretical and methodological in nature, generalizes and, to some extent, summarizes our previous and current research in the field of climate and weather modification and control. By analyzing the deliberate change in weather and climate from an optimal control and dynamical systems perspective, we get the ability to consider the modification of natural atmospheric processes as a dynamic optimization problem with an emphasis on the optimal control problem. Within this conceptual and unified theoretical framework for developing and synthesizing an optimal control for natural weather phenomena, the atmospheric process in question represents a closed-loop dynamical system described by an appropriate mathematical model or, in other words, by a set of differential equations. In this context, the human control actions can be described by variations of the model parameters selected on the basis of sensitivity analysis as control variables. Application of the proposed approach to the problem of weather and climate modification is illustrated using a low-order conceptual model of the Earth’s climate system. For the sake of convenient interpretation, we provide some weather and climate basics, as well as we give a brief glance at control theory and sensitivity analysis of dynamical systems.

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