### Identification of target system operations. 4. the practice of determining the optimal control

#### Abstract

Classic methods for determining the functional extrema can be successfully applied to solve a relatively narrow range of practical tasks. This is due to the fact that, in general, the quality of the studied output product in the process of movement varies. The traditional methods lose their main advantage associated with the assessment of the process quality at each step of the trajectory change.

In this paper, we have used the example of identifying the process of batch liquid heating to illustrate the use of the devised efficiency criterion for practical determining the optimal control on the basis of experimental data and analytical determining of the value of the heating mechanism depreciation.

Studies show that a necessary condition for finding a reliable optimality criterion is the account of technological equipment wear in situations where its impact on the assessment of efficiency is significant. The question of whether to consider or ignore the equipment depreciation (when searching the optimum) must be justified in each case.

It was found that the maximum efficiency shifts relative to the minimum cost and maximum added value (profit in open systems) towards higher productivity. This is due to the fact that the growth rate of cost, in the vicinity of the minimum cost, is much lower than the decline in the rate of operation (productivity). Ultimately, this leads to an increase in the integral added value if the cyclic operations are handled more efficiently.

The devised optimization criterion has a peculiar feature of its natural sensitivity to both the variation in the values of the system products’ cost and the operation time.

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PDF#### References

Lutsenko, I. (2014). Deployed model of extremal system operation for solving optimal management problems. Eastern-European Journal of Enterprise Technologies, 5, 2 (71), 61–66. doi: 10.15587/1729-4061.2014.28592

Lutsenko, I. (2015). Identification of target system operations.. Development of global efficiency criterion of target operations. Eastern-European Journal of Enterprise Technologies, 2, 2 (74), 35–40. doi: 10.15587/1729-4061.2015.38963

Lutsenko, I. (2015). Optimal control of systems engineering. Development of a general structure of the technological conversion subsystem (Part 2). Eastern-European Journal of Enterprise Technologies, 1, 2 (73), 43–50. doi: 10.15587/1729-4061.2015.36246

Kirk, E. (2004). Optimal Control Theory: An Introduction (Dover Books on Electrical Engineering). New York: Dover Publications, 464.

Tripathi, J. N., Apte, P. R., Mukherjee, J. (2011). Optimizing Gain of 5 GHz RF amplifier keeping minimum deviation in center frequency and noise figure. 2011 International Symposium on Integrated Circuits, 200–203. doi: 10.1109/isicir.2011.6131912

Someren, E. P., Wessels, L. F. A., Backer, E., Reinders, M. J. T. (2003). Multi-criterion optimization for genetic network modeling. Signal Processing, 83 (4), 763–775. doi: 10.1016/s0165-1684(02)00473-5

Zhang, S., Zhang, C., Han, G., Wang Q. (2014). Optimal Control Strategy Design Based on Dynamic Programming for a Dual-Motor Coupling-Propulsion System. The Scientific World Journal, 2014, 1–9. doi: 10.1155/2014/958239

Crassidis, L., Junkins, L. (2004). Optimal Estimation of Dynamic Systems. Washington, D.C., 608. doi: 10.1201/9780203509128

Lapygin, Y., Prokhorov, N. (2007). Cost Management in the enterprise. Eksmo, 102.

Mihaylov, V. V. (1973). Nadezhnost elektrosnabzheniya promyishlennyih predpriyatiy. Moscow: Energiya, 167.

#### GOST Style Citations

Lutsenko, I. Deployed model of extremal system operation for solving optimal management problems [Text] / I. Lutsenko // Eastern-European Journal of Enterprise Technologies. – 2014. – Vol. 5, Issue 2 (71). – P. 61–66. doi: 10.15587/1729-4061.2014.28592

Lutsenko, I. Identification of target system operations.. Development of global efficiency criterion of target operations [Text] / I. Lutsenko // Eastern-European Journal of Enterprise Technologies. – 2015. – Vol. 2, Issue 2 (74). – P. 35–40. doi: 10.15587/1729-4061.2015.38963

Lutsenko, I. Optimal control of systems engineering. Development of a general structure of the technological conversion subsystem (Part 2) [Text] / I. Lutsenko // Eastern-European Journal of Enterprise Technologies. – 2015. – Vol. 1, Issue 2 (73). – P. 43–50. doi: 10.15587/1729-4061.2015.36246

Kirk, E. Optimal Control Theory: An Introduction (Dover Books on Electrical Engineering) [Text] / E. Kirk. – New York : Dover Publications, 2004. – 464 p.

Tripathi, J. N. Optimizing Gain of 5 GHz RF amplifier keeping minimum deviation in center frequency and noise figure [Text] / J. N. Tripathi, P. R Apte, J. Mukherjee // 2011 International Symposium on Integrated Circuits, 2011. – P. 200–203. doi: 10.1109/isicir.2011.6131912

Someren, E. P. Multi-criterion optimization for genetic network modeling. [Text] / E. P. Someren, L. F. A. Wessels, E. Backer, M. J. T. Reinders // Signal Processing. – 2003. – Vol. 83, Issue 4. – P. 763–775. doi: 10.1016/s0165-1684(02)00473-5

Zhang, S. Optimal Control Strategy Design Based on Dynamic Programming for a Dual-Motor Coupling-Propulsion System [Text] / S. Zhang, C. Zhang, G. Han, Q. Wang // The Scientific World Journal. – 2014. – Vol. 2014. – P. 1–9. doi: 10.1155/2014/958239

Crassidis, L. Optimal Estimation of Dynamic Systems [Text] / L. J. Crassidis, L. J. Junkins. – Washington, D.C., 2004. – 608 p. doi: 10.1201/9780203509128

Lapygin, Y. Cost Management in the enterprise. [Text] / Y. Lapygin, N. Prokhorov. – Eksmo, 2007. – 102 p.

Mihaylov, V. V. Nadezhnost elektrosnabzheniya promyishlennyih predpriyatiy [Text] / V. V.Mihaylov. – Moscow : Energiya, 1973. – 167 p.

DOI: https://doi.org/10.15587/1729-4061.2015.54432

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Copyright (c) 2015 Елена Владиславовна Фомовская, Игорь Анатольевич Луценко

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ISSN (print) 1729-3774, ISSN (on-line) 1729-4061