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Robust resource allocation strategy for technology innovation ecosystems: state and control constraints

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Abstract

This paper considers a robust resource allocation strategy design problem in technology innovation ecosystem. The purpose is for both healthy competition and symbiosis between populations. We formulated this as a control design problem. There are three salient features of this problem. First, the control, since it means the resource and should always be positive, is constrained. Second, the state, since it means the population and should always be positive, is constrained. Third, the system, since it represents the interactions between the societal biomass and the resources, is highly uncertain. We endeavor to propose two separate transformations on the state and the control to convert the system to an equivalent and unconstrained system. In a sense, we embed the constraints into the (nonlinear) intrinsic system structure. Following this, the control design has to address two issues. First, the control is to render desirable performance of this (constraint-embedded) system regardless of the uncertainty. Second, the performance of the original system, which is the primary concern, should be equally within the threshold. This paper should be the first effort that addresses the resource allocation strategy of technology innovation ecosystem from the control perspective.

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References

  1. Solée, R.V., Valverde, S., Casals, M.R., Kauffman, S.A., Farmer, D., Eldredge, N.: The evolutionary ecology of technological innovations. Complexity 18(4), 15–27 (2013)

    Google Scholar 

  2. Sahal, D.: Patterns of Technological Innovation. Addison-Wesley, Reading (1981)

    Google Scholar 

  3. Schuster, P.: Untamable curiosity, innovation, discovery and bricolage. Complexity 11(5), 9–11 (2006)

    Google Scholar 

  4. Zhang, W., Liu, P., Zhang, J.: Multi-group symbiotic evolution mechanism in an innovative ecosystem: evidence from China. Rev Cercetare Interventie Soc 66, 249–277 (2019)

    Google Scholar 

  5. Wei, T., Zhu, Z., Li, Y., Yao, N.: The evolution of competition in innovation resource: a theoretical study based on Lotka–Volterra model. Technol. Anal. Strateg. Manag. 30(3), 295–310 (2018)

    Google Scholar 

  6. Chen, Y., Xie, F.J.: The bionics research of evolutionary path of photovoltaic industry’s innovation ecosystem based on Lotka–Volterra model. R&D Manag. 24, 74–84 (2012)

    Google Scholar 

  7. Bomze, I.M.: Lotka–Volterra equation and replicator dynamics: a two-dimensional classification. Biol. Cybern. 48(3), 201–211 (1983)

    MATH  Google Scholar 

  8. Bomze, I.M.: Lotka–Volterra equation and replicator dynamics: new issues in classification. Biol. Cybern. 72(5), 447–453 (1995)

    MATH  Google Scholar 

  9. Guidolin, M., Guseo, R.: Technological change in the US music industry: Within-product, cross-product and churn effects between competing blockbusters. Technol. Forecast. Soc. Change 99, 35–46 (2015)

    Google Scholar 

  10. Chakrabarti, A.S.: Stochastic Lotka–Volterra equations: a model of lagged diffusion of technology in an interconnected world. Phys. A Stat. Mech. Appl. 442, 214–223 (2016)

    MathSciNet  MATH  Google Scholar 

  11. Morris, S.A., Pratt, D.: Analysis of the Lotka–Volterra competition equations as a technological substitution model. Technol. Forecast. Soc. Change 70, 103–133 (2003)

    Google Scholar 

  12. Miranda, L.C.M., Lima, C.A.S.: Technology substitution and innovation adoption: the cases of imaging and mobile communication markets. Technol. Forecast. Soc. Change 80, 1179–1193 (2013)

    Google Scholar 

  13. Cerqueti, R., Tramontana, F., Ventura, M.: On the coexistence of innovators and imitators. Technol. Forecast. Soc. Change 90, 487–496 (2015)

    Google Scholar 

  14. De Guimarães, J.C.F., Severo, E.A., Dorion, E.C.H., Coallier, F., Olea, P.M.: The use of organisational resources for product innovation and organisational performance: a survey of the Brazilian furniture industry. Int. J. Prod. Econ. 180, 135–147 (2016)

    Google Scholar 

  15. Purchase, S., Kum, C., Olaru, D.: Paths, events and resource use: new developments in understanding innovation processes. Ind. Mark. Manag. 58, 123–136 (2016)

    Google Scholar 

  16. Sun, H., Chen, Y.H., Zhao, H.: Adaptive robust control methodology for active roll control system with uncertainty. Nonlinear Dyn. 92, 359–371 (2018)

    MATH  Google Scholar 

  17. Zhao, R., Chen, Y., Jiao, S., Ma, X.: A constraint-following control for uncertain mechanical systems: given force coupled with constraint force. Nonlinear Dyn. 93, 1201–1217 (2018)

    MATH  Google Scholar 

  18. Zhao, R., Li, M., Niu, Q., Chen, Y.H.: Udwadia–Kalaba constraint-based tracking control for artificial swarm mechanical systems: dynamic approach. Nonlinear Dyn. 100, 2381–2399 (2020)

    Google Scholar 

  19. Sun, Q., Yang, G., Wang, X., Chen, Y.H.: Cooperative game-oriented optimal design in constraint-following control of mechanical systems. Nonlinear Dyn. 101, 977–995 (2020)

    Google Scholar 

  20. Hwang, C.L., Liao, G.: Real-time pose imitation by mid-size humanoid robot with servo-cradle-head RGB-D vision system. IEEE Trans. Syst. Man Cybern. Syst. 49(1), 181–191 (2019)

    Google Scholar 

  21. Xu, J., Du, Y., Chen, Y.H., Guo, H., Ding, X.: Guaranteeing uniform ultimate boundedness for uncertain systems free of matching condition. IEEE Trans. Fuzzy Syst. 26(6), 3479–3493 (2018)

    Google Scholar 

  22. Yang, C., Duan, M., Lin, P., Ren, W., Gui, W.: Distributed containment control of continuous-time multiagent systems with nonconvex control input constraints. IEEE Trans. Ind. Electron. 66(10), 7927–7934 (2018)

    Google Scholar 

  23. Wang, Z., Li, G., Chen, X., Zhang, H., Chen, Q.: Simultaneous stabilization and tracking of nonholonomic wmrs with input constraints: controller Design and experimental validation. IEEE Trans. Ind. Electron. 66(7), 5343–5352 (2018)

    Google Scholar 

  24. Phat, V.N., Niamsup, P.: Stabilization of linear nonautonomous systems with norm-bounded controls. J. Optim. Theory Appl. 131(1), 135–149 (2006)

    MathSciNet  MATH  Google Scholar 

  25. Du, H., Zhang, N.: Fuzzy control for nonlinear uncertain electrohydraulic active suspensions with input constraint. IEEE Trans. Fuzzy Syst. 17(2), 343–356 (2008)

    Google Scholar 

  26. Saifia, D., Chadli, M., Labiod, S., Karimi, H.R.: \(H_{\infty }\) Fuzzy control of DC-DC converters with input constraint. Mathematical Problems in Engineering (2012)

  27. Chen, Y.H., Kuo, C.Y.: Positive uncertain systems with one-sided robust control. J. Dyn. Syst. Meas. Contr. 119(4), 675–684 (1997)

    MATH  Google Scholar 

  28. Zhao, R., Chen, Y.H., Jiao, S.: Optimal design of robust control for positive fuzzy dynamic systems with one-sided control constraint. J. Intell. Fuzzy Syst. 32(1), 723–735 (2017)

    MATH  Google Scholar 

  29. Li, C., Zhao, H., Sun, H., Chen, Y.H.: Robust bounded control for nonlinear uncertain systems with inequality constraints. Mech. Syst. Signal Process. 140, 106665 (2020)

    Google Scholar 

  30. Wang, X., Sun, Q., Yang, G., Chen, Y.H.: Optimal design of adaptive robust control for bounded constraint-following error in fuzzy mechanical systems. Int. J. Fuzzy Syst. 22(3), 970–984 (2020)

    MathSciNet  Google Scholar 

  31. Sun, Q., Yang, G., Wang, X., Chen, Y.H.: Regulating constraint-following bound for uncertain mechanical systems: an indirect control approach. IEEE Access 8, 70193–70203 (2020)

    Google Scholar 

  32. Sun, Q., Wang, X., Chen, Y.H.: Adaptive robust control for dual avoidance-arrival performance for uncertain mechanical systems. Nonlinear Dyn. 94(2), 759–774 (2018)

    Google Scholar 

  33. Yin, H., Chen, Y.H., Yu, D.: Vehicle motion control under equality and inequality constraints: a diffeomorphism approach. Nonlinear Dyn. 95(1), 175–194 (2019)

    MATH  Google Scholar 

  34. Hahn, W.: Stability of Motion. Springer, Berlin (1967)

    MATH  Google Scholar 

  35. Yoshizawa, T.: Stability Theory by Lyapunov’s Second Method. Mathematical Society of Japan, Tokyo (1966)

    MATH  Google Scholar 

  36. Sun, Q., Yang, G., Wang, X., Chen, Y.: Designing robust control for mechanical systems: constraint following and multivariable optimization. IEEE Trans. Ind. Inf. 16(8), 5267–5275 (2019)

    Google Scholar 

  37. Sun, Q., Yang, G., Wang, X., Chen, Y.: Regulating constraint-following bound for fuzzy mechanical systems: indirect robust control and fuzzy optimal design. IEEE Trans. Cybern. (2020). https://doi.org/10.1109/TCYB.2020.3040680

    Article  Google Scholar 

  38. Luenberger, D.G.: Optimization by Vector Space Methods. Wiley, New York (1969)

    MATH  Google Scholar 

  39. Zhang, G., McAdams, D.A., Shankar, V., Darani, M.M.: Technology evolution prediction using Lotka–Volterra equations. J. Mech. Des. 140(6), 061101 (2018)

    Google Scholar 

  40. Zhang, G., Mcadams, D.A., Shankar, V.: Modeling the evolution of system technology performance when component and system technology performances interact: commensalism and amensalism. Technol. Forecast. Soc. Change 125, 116–124 (2017)

    Google Scholar 

  41. Pei, L., Wang, Z., Ye, D.: Estimation of the competitive relationships between Amazon, Alibaba, and Suning based on a grey tripartite Lotka–Volterra model. Technol. Forecast. Soc. Change 29(4), 30–48 (2017)

    Google Scholar 

  42. Yan, J., Yu, X., Liu, P., Zhang, Q.: High-tech service platform ecosystem evolution: a simulation analysis using Lotka–Volterra model. Tech. Gazette 27(6), 1509–1518 (2020)

    Google Scholar 

  43. Hung, H., Chiu, Y., Huang, H., Wu, M.: An enhanced application of Lotka–Volterra model to forecast the sales of two competing retail formats. Comput. Ind. Eng. 109, 325–334 (2017)

    Google Scholar 

  44. Ivanova, I., Strand, O., Leydesdorff, L.: An eco-systems approach to constructing economic complexity measures: endogenization of the technological dimension using Lotka–Volterra equations. Adv. Complex Syst. 21(1), 1850023 (2019)

    MathSciNet  Google Scholar 

  45. Yung, K.L., Jiang, Z.Z., He, N., Ip, W.H., Huang, M.: System dynamics modeling of innovation ecosystem with two cases of space instruments. IEEE Trans. Eng. Manag. (2020). https://doi.org/10.1109/TEM.2020.3018782

    Article  Google Scholar 

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Acknowledgements

The research is supported jointly by the “Natural Science Foundation of China” (No. 51805263), the “Provincial Natural Science Foundation of Jiangsu” (No. BK20180474), the ”Nanjing University of Science and Technology Independent Research Program” (No. 30920021105), the “China Postdoctoral Science Foundation” (No. 2020M671494), the “Jiangsu Planned Projects for Postdoctoral Research Funds” (No. 2020Z179) and the “Fundamental Research Funds for the Central Universities” (No. 300102258306).

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Authors and Affiliations

  1. The School of Intellectual Property, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu, People’s Republic of China

    Xiuqian Chen & Fei Xia

  2. The School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu, People’s Republic of China

    Qinqin Sun

  3. Guangxi University of Finance and Economy, Nanning, 530003, Guangxi, People’s Republic of China

    Fei Xia

  4. The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Ye-Hwa Chen

  5. The Key Laboratory of Road Construction Technology and Equipment of MOE, Chang’an University, Xi’an, 710064, Shanxi, People’s Republic of China

    Ye-Hwa Chen

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  1. Xiuqian Chen
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Correspondence to Fei Xia.

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Chen, X., Sun, Q., Xia, F. et al. Robust resource allocation strategy for technology innovation ecosystems: state and control constraints. Nonlinear Dyn 103, 2931–2954 (2021). https://doi.org/10.1007/s11071-021-06215-7

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