Proper Lumping for Positive Bilinear Control Systems
Abstract: Positive systems naturally arise in situations where the model tracks physical quantities. Although the linear case is well understood, analysis and controller design for nonlinear positive systems remain challenging. Model reduction methods can help tame this problem. Here we propose a notion of model reduction for a class of positive bilinear systems with (bounded) matrix and exogenous controls. Our reduction, called proper positive lumping, aggregates the original system such that states of the corresponding reduced model represent non-negative linear combinations of original state variables. We prove a characterization result showing that the reductions by proper positive lumping are exactly those preserving the optimality of a suitable class of value functions. Moreover, we provide an efficient polynomial-time algorithm for the computation of the minimal lumping. We numerically evaluate our approach by applying it to a number of benchmark case studies.
- R. Shorten, F. Wirth, and D. Leith, “A positive systems model of TCP-like congestion control: asymptotic results,” IEEE/ACM transactions on networking, vol. 14, no. 3, pp. 616–629, 2006.
- T. Kaczorek, “Positive electrical circuits and their reachability,” Archives of Electrical Engineering, vol. 60, no. 3, pp. 283–301, 2011.
- G. Pappas and S. Simic, “Consistent abstractions of affine control systems,” IEEE TAC, vol. 47, no. 5, 2002.
- A. Rantzer and M. E. Valcher, “A tutorial on positive systems and large scale control,” in 2018 IEEE Conference on Decision and Control (CDC), 2018, pp. 3686–3697.
- F. Amato, M. Ariola, and P. Dorato, “Finite-time control of linear systems subject to parametric uncertainties and disturbances,” Automatica, vol. 37, no. 9, pp. 1459–1463, Sept. 2001.
- M. A. Rami and F. Tadeo, “Controller synthesis for positive linear systems with bounded controls,” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 54, no. 2, pp. 151–155, 2007.
- E. Weiss and M. Margaliot, “A generalization of linear positive systems with applications to nonlinear systems: Invariant sets and the Poincaré-Bendixson property,” Automatica, vol. 123, p. 109358, 2021.
- M. Aoki, “Control of large-scale dynamic systems by aggregation,” IEEE Trans. Automat. Contr., vol. 13, no. 3, pp. 246–253, 1968.
- T. J. Snowden, P. H. van der Graaf, and M. J. Tindall, “Methods of model reduction for large-scale biological systems: A survey of current methods and trends,” Bull. Math. Biol., vol. 79, no. 7, 2017.
- M. S. Okino and M. L. Mavrovouniotis, “Simplification of mathematical models of chemical reaction systems,” Chemical Reviews, vol. 2, no. 98, pp. 391–408, 1998.
- L. Cardelli, M. Tribastone, M. Tschaikowski, and A. Vandin, “Maximal aggregation of polynomial dynamical systems,” Proceedings of the National Academy of Sciences, vol. 114, no. 38, 2017.
- ——, “Guaranteed Error Bounds on Approximate Model Abstractions Through Reachability Analysis,” in QEST, 2018, pp. 104–121.
- ——, “Symbolic computation of differential equivalences,” Theor. Comput. Sci., vol. 777, pp. 132–154, 2019.
- S. Derisavi, H. Hermanns, and W. H. Sanders, “Optimal state-space lumping in Markov chains,” Information Processing Letters, vol. 87, no. 6, pp. 309–315, 2003.
- A. Dokoumetzidis and L. Aarons, “Proper lumping in systems biology models,” IET Systems Biology, vol. 3, no. 1, pp. 40–51, 2009.
- A. Ovchinnikov, I. Pérez Verona, G. Pogudin, and M. Tribastone, “CLUE: exact maximal reduction of kinetic models by constrained lumping of differential equations,” Bioinformatics, vol. 37, no. 19, pp. 3385–3385, 08 2021.
- L. Cardelli, R. Grosu, K. G. Larsen, M. Tribastone, M. Tschaikowski, and A. Vandin, “Algorithmic minimization of uncertain continuous-time Markov chains,” IEEE Trans. Automat. Contr., pp. 1–16, 2023.
- G. Li, H. Rabitz, and J. Tóth, “A general analysis of exact nonlinear lumping in chemical kinetics,” Chemical Engineering Science, vol. 49, no. 3, pp. 343–361, 1994.
- G. J. Pappas, G. Lafferriere, and S. Sastry, “Hierarchically consistent control systems,” IEEE Trans. Automat. Contr., vol. 45, no. 6, pp. 1144–1160, 2000.
- A. van der Schaft, “Equivalence of dynamical systems by bisimulation,” IEEE Trans. Automat. Contr., vol. 49, pp. 2160–2172, 2004.
- G. J. Pappas and S. Simic, “Consistent abstractions of affine control systems,” IEEE Trans. Automat. Contr., vol. 47, no. 5, 2002.
- P. Tabuada and G. J. Pappas, “Abstractions of Hamiltonian control systems,” Automatica, vol. 39, no. 12, pp. 2025–2033, 2003.
- V. Mehrmann and T. Stykel, “Balanced truncation model reduction for large-scale systems in descriptor form,” in Lecture Notes in Computational Science and Engineering. Springer-Verlag, 2005, pp. 83–115. [Online]. Available: https://doi.org/10.1007/3-540-27909-1˙3
- T. Reis and E. Virnik, “Positivity preserving model reduction,” in Positive Systems. Springer Berlin Heidelberg, 2009, pp. 131–139. [Online]. Available: https://doi.org/10.1007/978-3-642-02894-6˙13
- P. Li, J. Lam, Z. Wang, and P. Date, “Positivity-preserving H∞{}_{\infty}start_FLOATSUBSCRIPT ∞ end_FLOATSUBSCRIPT model reduction for positive systems,” Automatica, vol. 47, no. 7, pp. 1504–1511, 2011.
- T. Ishizaki, K. Kashima, A. Girard, J. Imura, L. Chen, and K. Aihara, “Clustered model reduction of positive directed networks,” Automatica, vol. 59, pp. 238–247, Sept. 2015.
- H. Sandberg and R. M. Murray, “Model reduction of interconnected linear systems using structured gramians,” IFAC Proceedings Volumes, vol. 41, no. 2, pp. 8725–8730, 2008.
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