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An Algorithm for Finding Feedback in a Problem with Constraints for One Class of Nonlinear Control Systems

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Abstract

We consider the construction of a feedback according to the Kalman algorithm for a continuous nonlinear control system on a finite time interval with control constraints where the right-hand side of the dynamics equations is linear in control and linearizable in the vicinity of the zero equilibrium position. The solution of an auxiliary optimal control problem with a quadratic functional is used for this task by analogy with the SDRE approach. Because this approach is used in the literature to find suboptimal synthesis in optimal control problems with a quadratic functional with formally linear systems where all coefficient matrices in differential equations and criteria can contain state variables, on a finite time interval it becomes necessary to solve a complicated matrix differential Riccati equations with state-dependent coefficient matrices. Due to the nonlinearity of the system this issue significantly increases the number of calculations for obtaining the coefficients of the gain matrix in the feedback and for obtaining synthesis with a given accuracy in comparison with the Kalman algorithm for linear-quadratic problems. The proposed synthesis construction algorithm is constructed using the extension principle proposed by V.F. Krotov and developed by V.I. Gurman and allows one not only to expand the scope of the SDRE approach to nonlinear control problems with control constraints in the form of closed inequalities, but also to propose a more efficient computational algorithm for finding the matrix of feedback gains in control problems on a finite interval. This article establishes the correctness of the application of the extension principle by introducing analogs of the Lagrange multipliers, which depend on the state and time, and also derives a formula for the suboptimal value of the quality criterion. The presented theoretical results are illustrated by calculating suboptimal feedbacks in the problems of managing three-sector economic systems.

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REFERENCES

  1. Mracek, C.P. and Cloutier, J.R., Control designs for the nonlinear benchmark problem via the state-dependent Riccati equation method, Int. J. Robust Nonlinear Control, 1998, vol. 8, nos. 4–5, pp. 401–433.  https://doi.org/10.1002/(SICI)1099-1239(19980415/30)8:4/5<401::AID-RNC361>3.0.CO;2-U

    Article  MathSciNet  MATH  Google Scholar 

  2. Cloutier, J.R. and Stansbery, D.T., The capabilities and art of state-dependent Riccati equation-based design, Proc. 2002 American Control Conf., Anchorage, Alaska, 2002, IEEE, 2002, vol. 1, pp. 86–91.  https://doi.org/10.1109/ACC.2002.1024785

  3. Afanas’ev, V. and Orlov, P., Suboptimal control of feedback-linearizable nonlinear plant, J. Comput. Syst. Sci. Int., 2011, vol. 50, no. 3, pp. 365–374.  https://doi.org/10.1134/S1064230711030026

    Article  MathSciNet  MATH  Google Scholar 

  4. Çimen, T., State-dependent Riccati equation (SDRE) control: A survey, IFAC Proc. Vols., 2008, vol. 41, no. 2, pp. 3761–3775.  https://doi.org/10.3182/20080706-5-KR-1001.00635

  5. Heydari, A. and Balakrishnan, S.N., Path planning using a novel finite horizon suboptimal controller, J. Guidance, Control Dynamics, 2013, vol. 36, no. 4, pp. 1210–1214.  https://doi.org/10.2514/1.59127

    Article  Google Scholar 

  6. Heydari, A. and Balakrishnan, S.N., Approximate closed-form solutions to finite-horizon optimal control of nonlinear systems, American Control Conference (ACC), Montreal, 2012, IEEE, 2012, pp. 2657–2662.  https://doi.org/10.1109/ACC.2012.6315505

  7. Krotov, V.F. and Gurman, V., Metody i zadachi optimal’nogo upravleniya (Methods and Problems of Optimal Control), Moscow: Nauka, 1973.

  8. Gurman, V., Printsip rasshireniya v zadachakh upravleniya (The Principle of Expansion in Control Problems), Moscow: Fizmatlit, 1985.

  9. Dmitriev, M., Murzabekov, Z., Makarov, D., and Mirzakhmedova, G., SDRE based stabilization of the affine control system with the stationary linear part, 23rd Int. Conf. on System Theory, Control and Computing (ICSTCC), Sinaia, Romania, 2019, IEEE, 2019, pp. 739–743.  https://doi.org/10.1109/ICSTCC.2019.8885437

  10. Aipanov, S.A. and Murzabekov, Z.N., Analytical solution of a linear quadratic optimal control problem with control value constraints, J. Comput. Syst. Sci. Int., 2014, vol. 1, no. 53, pp. 84–91.  https://doi.org/10.1134/S1064230713060026

    Article  MATH  Google Scholar 

  11. Murzabekov, Z., The synthesis of the proportional-differential regulators for the systems with fixed ends of trajectories under two-sided constraints on control values, Asian J. Control, 2016, vol. 18, no. 2, pp. 494–501.  https://doi.org/10.1002/asjc.1063

    Article  MathSciNet  MATH  Google Scholar 

  12. Murzabekov, Z., Milosz, M., and Tussupova, K., The optimal control problem with fixed-end trajectories for a three-sector economic model of a cluster, Intelligent Information and Database Systems. ACIIDS 2018, Nguyen, N., Hoang, D., Hong, TP., Pham, H., Trawiński, B., Eds., Lecture Notes in Computer Science, vol. 10751, Cham: Springer, 2018, pp. 382–391.  https://doi.org/10.1007/978-3-319-75417-8_36

    Book  Google Scholar 

  13. Murzabekov, Z., Milosz, M., and Tussupova, K., Modeling and optimization of the production cluster, Information Systems Architecture and Technology: Proceedings of 36th International Conference on Information Systems Architecture and Technology – ISAT 2015 – Part II, Grzech, A., Borzemski, L., Świątek, J., and Wilimowska, Z., Advances in Intelligent Systems and Computing, vol. 430, Cham: Springer, 2016, pp. 99–108.  https://doi.org/10.1007/978-3-319-28561-0_8

  14. Dmitriev, M. and Makarov, D.A., Smooth nonlinear controller in a weakly nonlinear control system with state dependent coefficients, Tr. Inst. Sist. Anal. Ross. Akad. Nauk, 2014, vol. 64, no. 4, pp. 53–58.

    Google Scholar 

  15. Kolemajev, V.A., Optimal balanced space of the open three-sector economy, Appl. Econometrics, 2008, vol. 3, no. 11, pp. 15–42.

    Google Scholar 

  16. Aseev, S.M., Besov, K., and Kryazhimsky, A., Infinite-horizon optimal control problems i economics, Russ. Math. Surv., 2012, vol. 67, no. 2, pp. 195–253.  https://doi.org/10.1070/RM2012v067n02ABEH004785

    Article  MathSciNet  MATH  Google Scholar 

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Funding

The research was partially supported by the Russian Science Foundation, grant no. 21-11-00202.

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Correspondence to M. G. Dmitriev, Z. N. Murzabekov or G. A. Mirzakhmedova.

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The authors declare that they have no conflicts of interest.

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Translated by F. Baron

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Dmitriev, M.G., Murzabekov, Z.N. & Mirzakhmedova, G.A. An Algorithm for Finding Feedback in a Problem with Constraints for One Class of Nonlinear Control Systems. Aut. Control Comp. Sci. 56, 623–633 (2022). https://doi.org/10.3103/S0146411622070033

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  • DOI: https://doi.org/10.3103/S0146411622070033

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