Optimal Control Theory Applied to a Dynamic Aquatic Ecosystem

1973 ◽  
Vol 30 (4) ◽  
pp. 576-579 ◽  
Author(s):  
N. U. Ahmed ◽  
N. D. Georganas
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Dynamic Model ◽  
Aquatic Ecosystem ◽  
Optimal Control Theory ◽  
Minimum Cost ◽  
Single Species ◽  
Pollution Reduction ◽  
Polluted Environment ◽  
Species Removal

In this report we present a dynamic model for an aquatic ecosystem consisting of a single species living in a polluted environment. Considering the dynamics of growth of the species and increase in pollution, we apply optimal control theory to obtain species removal and pollution reduction rates at minimum cost.

Dynamic model for population distribution and optimum immigration and job creation policies

2004 ◽  
Vol 31 (2) ◽  
pp. 261
Author(s):  
N. U. Ahmed ◽  
Yongjuan He
Keyword(s):  
Numerical Simulation ◽  
Optimal Control ◽  
Control Theory ◽  
Dynamic Model ◽  
Optimal Control Theory ◽  
Close Agreement ◽  
Population Distribution ◽  
Job Creation ◽  
Population Level ◽  
Decision Control

In this paper we demonstrate that by use of modern Systems and Optimal Control theory, it is possible to formulate optimum immigration and job creation strategies while maintaining population level close to certain pre-specified targets. With this objective in mind, we consider a simplified dynamic model based on a previous model developed in (Ahmed and Rahim, 2001:325-358) to describe the population distribution in Canada. Numerical results demonstrate that the model population is in close agreement with the actual population. This model was then used to formulate a control problem with immigration and job creation rates being the decision (control) variables. Using optimal control theory, optimum immigration and job creation policies were determined. Results are illustrated by numerical simulation and they are found to be very encouraging.

Optimal Control Theory

2018 ◽  
Author(s):  
John E. Prussing
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Optimal Control Theory ◽  
Necessary Conditions ◽  
Minimum Principle ◽  
Minimum Cost ◽  
Initial Time ◽  
Pontryagin Minimum Principle ◽  
Final Time ◽  
Terminal Constraints

Optimal Control Theory is reviewed in detail. We consider a dynamic system that operates between a specified initial time and a final time which may be specified or unspecified. Necessary conditions for a minimum cost functional are derived. Terminal constraints are considered. Pontryagin Minimum Principle is discussed.

Dispersion of nanoparticles with optimal control theory based on destabilization

2014 ◽  
Vol 2 ◽  
pp. 86-86
Author(s):  
Miki U. Kobayashi ◽  
Nobuaki Aoki ◽  
Noriyoshi Manabe ◽  
Tadafumi Adschiri
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Optimal Control Theory ◽  
Dispersion Of Nanoparticles

scholarly journals Recoil control of deepwater drilling riser system based on optimal control theory

2020 ◽  
pp. 108473
Author(s):  
Xiuquan Liu ◽  
Zhaowei Liu ◽  
Xianglei Wang ◽  
Nan Zhang ◽  
Na Qiu ◽  
...  
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Optimal Control Theory ◽  
Deepwater Drilling

scholarly journals Optimal Control for a COVID-19 Model Accounting for Symptomatic and Asymptomatic

2020 ◽  
Vol 8 (1) ◽  
pp. 168-179
Author(s):  
Jead M. Macalisang ◽  
Mark L. Caay ◽  
Jayrold P. Arcede ◽  
Randy L. Caga-anan
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Medical Care ◽  
Optimal Control Theory ◽  
Comparable Result ◽  
Type Model ◽  
Hospital Beds ◽  
Transmission Reduction ◽  
Bed Capacity ◽  
The Government

AbstractBuilding on an SEIR-type model of COVID-19 where the infecteds are further divided into symptomatic and asymptomatic, a system incorporating the various possible interventions is formulated. Interventions, also referred to as controls, include transmission reduction (e.g., lockdown, social distancing, barrier gestures); testing/isolation on the exposed, symptomatic and asymptomatic compartments; and medical controls such as enhancing patients’ medical care and increasing bed capacity. By considering the government’s capacity, the best strategies for implementing the controls were obtained using optimal control theory. Results show that, if all the controls are to be used, the more able the government is, the more it should implement transmission reduction, testing, and enhancing patients’ medical care without increasing hospital beds. However, if the government finds it very difficult to implement the controls for economic reasons, the best approach is to increase the hospital beds. Moreover, among the testing/isolation controls, testing/isolation in the exposed compartment is the least needed when there is significant transmission reduction control. Surprisingly, when there is no transmission reduction control, testing/isolation in the exposed should be optimal. Testing/isolation in the exposed could seemingly replace the transmission reduction control to yield a comparable result to that when the transmission reduction control is being implemented.

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