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Article

Keywords:
descriptor redundancy; differential algebraic equations; linear matrix inequality; nonlinear observer
Summary:
This work presents a novel methodology to design nonlinear observers for a class of systems modeled as differential algebraic equations. The proposal is based on writing both the system and the observer as nonlinear descriptor redundancy representations subject to algebraic restrictions; then the nonlinear observation error system is written in an explicit incremental form via suitable factorization techniques. A redundant Lyapunov function is then employed to guarantee asymptotic stability of the estimation error; linearity of the Lyapunov function and its time derivative with respect to the observer gains and Lyapunov function terms, allows gridding or convex treatment of expressions via linear matrix inequalities. Physical examples are presented to illustrate the proposal effectiveness against former methodologies.
References:
[1] Álvarez, J., Servín, J., Díaz, J. A., Bernal, M.: Differential algebraic observer-based trajectory tracking for parallel robots via linear matrix inequalities. Int. J. Systems Sci. 53 (2022), 10, 2149-2164. DOI  | MR 4452551
[2] Arceo, J. C., Alvarez, J., Armenta, C., Lauber, J., Cremoux, S., Simoneau-Buessinger, E., Bernal, M.: Novel solutions on model-based and model-free robotic-assisted ankle rehabilitation. Arch. Control Sci. 31 (2021), 1, 5-27. DOI  | MR 4247216
[3] Arceo, J. C., Sánchez, M., Estrada-Manzo, V., Bernal, M.: Convex stability analysis of nonlinear singular systems via linear matrix inequalities. IEEE Trans. Automat. Control 64 (2018), 4, 1740-1745. DOI  | MR 3936451
[4] Berger, T.: On observers for nonlinear differential-algebraic systems. IEEE Trans. Automat. Control 64 (2019), 5, 2150-2157. DOI  | MR 3951060
[5] Bernal, M., Sala, A., Lendek, Z., Guerra, T. M.: Analysis and Synthesis of Nonlinear Control Systems: A Convex Optimsation Approach. Springer, Cham 2022. MR 4397563
[6] Bock, H. G., Schulz, V.: Mathematical aspects of CFD-based optimization. In: Optimization and Computational Fluid Dynamics, Springer 2008, pp. 61-78. DOI 
[7] Boyd, S., Ghaoui, L. El, Feron, E., Balakrishnan, V.: Linear matrix inequalities in system and control theory. Studies in Applied Mathematics 15, Philadelphia 1994. DOI  | MR 1284712
[8] Cardin, P. T., Silva, P. R. da, Teixeira, M. A.: Implicit differential equations with impasse singularities and singular perturbation problems. Israel J. Math. 189 (2012), 307-322. DOI  | MR 2931399
[9] Duan, G. R.: Analysis and Design of Descriptor Linear Systems. Springer-Verlag, New York 2010. MR 2723074
[10] Gahinet, P., Nemirovskii, A., Laub, A. J., Chilali, M.: The LMI control toolbox. In: Proc. 1994 33rd IEEE Conference on Decision and Control 3 IEEE 1994, pp. 2038-2041. DOI  | MR 1382985
[11] Gonzalez, T., Bernal, M., Sala, A., Aguiar, B.: Cancellation-based nonquadratic controller design for nonlinear systems via Takagi-Sugeno models. IEEE Trans. Cybernet. 47 (2016), 9, 2628-2638. DOI 
[12] Guerra, T. M., Oliveira, V. C. de, Berdjag, D., Lv, Ch., Nguyen, A. T.: Fault tolerant observer design for a class of nonlinear systems with corrupted outputs. Int. J. Robust Nonlinear Control 34 (2024), 13, 8825-8843. DOI  | MR 4788982
[13] Guerra, T. M., Estrada-Manzo, V., Lendek, Z.: Observer design for Takagi-Sugeno descriptor models: An LMI approach. Automatica 52 (2015), 154-159. DOI  | MR 3310825
[14] Inc., MathWorks: Symbolic Math Toolbox. Natick, Massachusetts 2019.
[15] Khalil, H.: Nonlinear Control. Prentice Hall, New Jersey 2014. DOI 
[16] Lendek, Z., Guerra, T. M., R.Babuska, De-Schutter, B.: Stability analysis and nonlinear observer design using Takagi-Sugeno fuzzy models. Studies Fuzziness Soft Computing. Springer-Verlag, 2011.
[17] Merlet, J.-P.: Parallel robots. Springer Science Business Media 128, 2006.
[18] Nedialkov, N. S., Pryce, J. D., Tan, G.: Algorithm 948: Daesaa Matlab tool for structural analysis of differential-algebraic equations: Software. ACM Trans. Math. Software (TOMS) 41 (2015), 2, 1-14. DOI 10.1145/2700586 | MR 3318084
[19] Ohtake, H., Tanaka, K., Wang, H. O.: Fuzzy modeling via sector nonlinearity concept. Integrated Computer-Aided Engrg. 10 (2003), 4, 333-341. DOI 
[20] Pantelides, C. C.: The consistent initialization of differential-algebraic systems. SIAM J. Scientific Statist. Comput. 9 (1988), 2, 213-231. DOI  | MR 0930042
[21] Pantelides, C. C., Gritsis, D., Morison, K. R., Sargent, R. W. H.: The mathematical modelling of transient systems using differential-algebraic equations. Computers Chemical Engrg. 12 (1988), 5, 449-454. DOI 
[22] Quintana, D., Estrada-Manzo, V., Bernal, M.: An exact handling of the gradient for overcoming persistent problems in nonlinear observer design via convex optimization techniques. Fuzzy Sets Systems 416 (2021), 125-140. DOI  | MR 4258759
[23] Rabier, P. J., C, W., Rheinboldt: Nonholonomic motion of rigid mechanical systems from a DAE viewpoint. SIAM, 2000. MR 1740801
[24] Rabier, P. J., Rheinboldt, W. C.: Theoretical and numerical analysis of differential-algebraic equations. 2002. MR 1893418
[25] Riaza, R.: Differential-algebraic Systems: Analytical Aspects and Circuit Applications. World Scientific, 2008. MR 2426820
[26] Robles, R., Sala, A., Bernal, M., González, T.: Subspace-based Takagi-Sugeno modeling for improved LMI performance. IEEE Trans. Fuzzy Systems 25 (2016), 4, 754-767. DOI 
[27] Sadeghzadeh, A., Tóth, R.: Linear parameter-varying embedding of nonlinear models with reduced conservativeness. IFAC-PapersOnLine 53 (2020), 2, 4737-4743. DOI 
[28] Sala, A.: Computer control under time-varying sampling period: An LMI gridding approach. Automatica 41 (2005), 12, 2077-2082. DOI  | MR 2174802
[29] Sala, A., Arino, C.: Asymptotically necessary and sufficient conditions for stability and performance in fuzzy control: Applications of Polya's theorem. Fuzzy Sets Systems 158 (2007), 24, 2671-2686. DOI  | MR 2374213
[30] Scherer, C. W.: LMI relaxations in robust control. European J. Control 12 (2006), 1, 3-29. DOI  | MR 2221472
[31] Schoukens, M., Tóth, R.: Linear parameter varying representation of a class of MIMO nonlinear systems. IFAC-PapersOnLine 51 (2018), 26, 94-99. DOI 
[32] Takaba, K., Morihira, N., Katayama, T.: A generalized Lyapunov theorem for descriptor system. Systems Control Lett. 24 (1995), 1, 49-51. DOI  | MR 1307127
[33] Tanaka, K., Wang, H. O.: Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach. John Wiley and Sons, New York 2001.
[34] Taniguchi, T., Tanaka, K., Wang, H. O.: Fuzzy descriptor systems and nonlinear model following control. IEEE Trans. Fuzzy Systems 8 (2000), 4, 442-452. DOI 
[35] Zheng, G., Efimov, D., Bejarano, F. J., Perruquetti, W., Wang, H.: Interval observer for a class of uncertain nonlinear singular systems. Automatica 71 (2016), 159-168. DOI  | MR 3521965
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