Establishing Model of Adaptive Control in the Optimal Fishing Strategy Based on Quantum Control Techniques

Article Preview

Abstract:

In this paper, the problem about establishing model of adaptive control in the optimal fishing strategy based on quantum control technique is proposed. An equation satisfied by fish stocks in a fishing conditions is obtained. Based on the stability analysis the question how to control fishing to the maximum sustainable yield and economic benefits is presented. The model of fish stocks growth in a fishing condition is established on calculus of variations. In the changes of fish prices, fishing cost, the inflation rate and bank loans, the fishing quantity is adjusted to obtain the maximum economic benefits through adaptive control methods and quantum control techniques. Analysis results have shown the validity of the proposed method.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

4274-4278

Citation:

Online since:

October 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] M. Jerry, N. Raissi. The Optimal Strategy for a Bioeconomical Model of a Harvesting Renewable Resource Problem[J]. Mathematical and Computer Modelling, vol. 36, No. 11, pp.1293-3106, (2002).

DOI: 10.1016/s0895-7177(02)00277-7

Google Scholar

[2] H.K. Chiou, G.H. Tzeng. Fuzzy Classification for Solving the Optimal Strategy Combination of Green Engineering Industry with Interdependent Situations [C]. 2006 IEEE International Conference on Fuzzy Systems, pp.1625-32.

DOI: 10.1109/fuzzy.2006.1681925

Google Scholar

[3] S. Lin, H.J. Xiao, D.Q. Yang. Forecasting Fish Stock Recruitment and Planning Optimal Harvesting Strategies by Using Neural Network[J]. Journal of Computers, vol. 4, No. 11, pp.1075-1082, (2009).

DOI: 10.4304/jcp.4.11.1075-1082

Google Scholar

[4] J.R. Chen, Y. Wang. Optimization Approach on Using Fishing Strategy[J]. Computer Engineering and Applications, vol. 45, No. 9, pp.53-56, (2009).

Google Scholar

[5] J.C. Zambrini. Stochastic Dynamics: a Review of Stochastic Calculus of Variations [J]. International Journal of Theoretical Physics, vol. 24, No. 3, pp.277-327, (1985).

DOI: 10.1007/bf00669792

Google Scholar

[6] S. Konjik, M. Kunzinger. Foundations of the Calculus of Variations in Generalized Function Algebras [J]. Acta Applicandae Mathematicae, vol. 103, No. 2, pp.169-199, (2008).

DOI: 10.1007/s10440-008-9228-0

Google Scholar

[7] G. Crasta. Existence Result for Noncoercive Nonconvex Problems in the Calculus of Variations [J]. Nonlinear Analysis, Theory, Methods and Applications, vol. 26, No. 9, pp.1527-1533, (1996).

DOI: 10.1016/0362-546x(95)00010-s

Google Scholar

[8] V.P. Bhatkar. Fundamental Necessary Conditions of Non-local Calculus of Variations [J]. International Journal of Control, vol. 15, No. 5, pp.1005-1007, (1972).

DOI: 10.1080/00207177208932215

Google Scholar

[9] Z.H. Chen, D.Y. Dong, C.B. Zhang. Quantum Control Theory [M]. Hefei: University of Science and Technology of China Press, (2005).

Google Scholar