# On the stock estimation for some fishery systems

On the stock estimation for some fishery systems In this work we address the stock estimation problem for two fishery models. We show that a tool from nonlinear control theory called “observer” can be helpful to deal with the resource stock estimation in the field of renewable resource management. It is often difficult or expensive to measure all the state variables characterising the evolution of a given population system, therefore the question arises whether from the observation of certain indicators of the considered system, the whole state of the population system can be recovered or at least estimated. The goal of this paper is to show how some techniques of control theory can be applied for the approximate estimation of the unmeasurable state variables using only the observed data together with the dynamical model describing the evolution of the system. More precisely we shall consider two fishery models and we shall show how to built for each model an auxiliary dynamical system (the observer) that uses the available data (the total of caught fish) and which produces a dynamical estimation $$\hat x(t)$$ of the unmeasurable stock state x(t). Moreover the convergence speed of $$\hat x(t)$$ towards x(t) can be chosen. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Reviews in Fish Biology and Fisheries Springer Journals

# On the stock estimation for some fishery systems

, Volume 19 (3) – Feb 1, 2009
15 pages

/lp/springer_journal/on-the-stock-estimation-for-some-fishery-systems-0Jy6HaBewr
Publisher
Springer Netherlands
Subject
Life Sciences; Zoology ; Freshwater & Marine Ecology
ISSN
0960-3166
eISSN
1573-5184
D.O.I.
10.1007/s11160-009-9104-7
Publisher site
See Article on Publisher Site

### Abstract

In this work we address the stock estimation problem for two fishery models. We show that a tool from nonlinear control theory called “observer” can be helpful to deal with the resource stock estimation in the field of renewable resource management. It is often difficult or expensive to measure all the state variables characterising the evolution of a given population system, therefore the question arises whether from the observation of certain indicators of the considered system, the whole state of the population system can be recovered or at least estimated. The goal of this paper is to show how some techniques of control theory can be applied for the approximate estimation of the unmeasurable state variables using only the observed data together with the dynamical model describing the evolution of the system. More precisely we shall consider two fishery models and we shall show how to built for each model an auxiliary dynamical system (the observer) that uses the available data (the total of caught fish) and which produces a dynamical estimation $$\hat x(t)$$ of the unmeasurable stock state x(t). Moreover the convergence speed of $$\hat x(t)$$ towards x(t) can be chosen.

### Journal

Reviews in Fish Biology and FisheriesSpringer Journals

Published: Feb 1, 2009

## You’re reading a free preview. Subscribe to read the entire article.

### DeepDyve is your personal research library

It’s your single place to instantly
that matters to you.

over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month ### Explore the DeepDyve Library ### Unlimited reading Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere. ### Stay up to date Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates. ### Organize your research It’s easy to organize your research with our built-in tools. ### Your journals are on DeepDyve Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more. All the latest content is available, no embargo periods. ### DeepDyve Freelancer ### DeepDyve Pro Price FREE$49/month

\$360/year
Save searches from Google Scholar, PubMed
Create lists to organize your research
Export lists, citations