Estrategia de control pasivo tolerante a fallas par un Sistema no lineal: Aplicación a un sistema de control de nivel sin interacción de dos tanques cónicos
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Publicado:
Dec 20, 2018
Palabras clave:
Fallo del actuador, perturbación del proceso, sistema no lineal, red neuronal, control pasivo tolerante a fallos
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Resumen
En los sistemas de ingeniería práctica, con frecuencia ocurren fallas desconocidas en el actuador, sensor o componente del sistema, que resultan de fallas de componentes e interconexión, degradan el rendimiento del control, la estabilidad del sistema y la rentabilidad, e incluso surgen situaciones peligrosas. Para evitar actividades anormales como fallas y mantener el rendimiento del control del sistema sujeto a fallas que ocurren en el sistema, el Control tolerante a fallas (FTC) es un enfoque realista para abordar la situación no deseada. El sistema de dos tanques cónicos se usa ampliamente en las industrias químicas y de procesos alimentarios debido a sus mayores ventajas. La configuración no interactiva del sistema de dos tanques cónicos es altamente no lineal debido a su forma y al área variable del tanque a través de la altura del tanque, por lo que el control de nivel de este sistema es extremadamente difícil. Este trabajo se lo realiza para diseñar una estrategia de control tolerante a fallas pasivas (PFTCS) para un sistema de control de nivel sin interacción de dos tanques cónicos (TTCNILCS) sujeto al sistema principal (fugas), fallas del actuador con perturbaciones externas del proceso. PFTC aumentará el rendimiento del control del sistema y la estabilidad del sistema en un nivel aceptable en presencia de fallas del sistema y del actuador. Los resultados de la simulación demuestran que la estrategia PFTC propuesta tiene una capacidad de tolerancia a fallas definida contra las fallas del sistema y del actuador, y también tiene una buena capacidad de rechazo de perturbaciones. Para verificar la eficacia de la estrategia de PFTC propuesta, se utilizan los índices de Error absoluto cuadrático medio (MSE) y Error cuadrático medio (RMSE).
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Estrategia de control pasivo tolerante a fallas par un Sistema no lineal: Aplicación a un sistema de control de nivel sin interacción de dos tanques cónicos. (2018). MASKAY, 9(1), 1-8. https://doi.org/10.24133/maskay.v9i1.1094
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Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
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Estrategia de control pasivo tolerante a fallas par un Sistema no lineal: Aplicación a un sistema de control de nivel sin interacción de dos tanques cónicos. (2018). MASKAY, 9(1), 1-8. https://doi.org/10.24133/maskay.v9i1.1094
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[2] H. R. Patel and V. A. Shah, “Fault Detection and Diagnosis Methods in Power Generation Plants - The Indian Power Generation Sector Perspective: An Introductory Review,” PDPU Journal of Energy and Management, vol. 2, no. 2, pp. 31-49, 2018.
[3] Y. Zhang, and J. Jiang, “Bibliographical review on reconfigurable fault tolerant control systems,” Annual Review in Control, vol. 32, no. 2, pp. 229– 252, 2008.
[4] R. Patton, “Fault-tolerant control systems: The 1997 situation,” in Proc. IFAC, Safeprocess’97, Kingston Upon Hull, UK, 1997, vol. 3, pp. 1033–1054.
[5] Y. Xu, S.Tong, and Y. Li, “Adaptive fuzzy decentralised fault-tolerant control for nonlinear large-scale systems with actuator failures and unmodelled dynamics,” International Journal of Systems science, vol. 46, no. 12, pp. 2195–2209, 2015.
[6] S. Tong, T. Wang, and Y. Li, “Fuzzy adaptive actuator failure compensation control of uncertain stochastic nonlinear systems with unmodelled dynamics,” IEEE Transactions on Fuzzy Systems, vol. 22, no. 3, pp. 563–574, 2014.
[7] S. Yin, H. Yang, H. Gao, J. Qiu, and O. Kaynak, “An Adaptive NN-Based Approach for Fault-Tolerant Control of Nonlinear Time-Varying Delay Systems with Unmodeled Dynamics,” IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 8, pp. 1902-1913,2017.
[8] Adriana, Vargas-Martinez, and L. E. Garaza-Castañón, “Combining Artificial Intelligence and Advanced Techniques in Fault-Tolerant Control,” Journal of Applied Research and Technology, vol. 09, no. 2, pp. 202-226, 2011.
[9] M. Basin L. Li, M. Krueger, and S. Ding, “A finite-time-convergent fault-tolerant control and its experimental verification for DTS200 three-tank system,” in Proc. IEEE, International Workshop on Recent Advances in Sliding Modes (RASM), Istanbul, Turkey, 2015, pp. 1-6.
[10] M. Fuente, V. Mateo, G. I. Sainz, S. Saludes, “Adaptive Neural-based Fault Tolerant Control for Nonlinear Systems,” in Proc. IFAC, 17th IFAC World Congress, Seoul, Korea, 2008, vol. 41, no. 2, pp. 2595-2600.
[11] B. Huo, S. Tong, and Y. Li, “Observer-based adaptive fuzzy fault-tolerant output feedback control of uncertain nonlinear systems with actuator faults,” International Journal of Control Automation, vol. 10, no. 6, pp. 1119-1128, 2012.
[12] S. Tong, B. Huo, and Y. Li, “Observer-based adaptive decentralized fuzzy fault-tolerant control of nonlinear large-scale systems with actuator failures,” IEEE Transactions on Fuzzy Systems, vol. 21, no. 1, pp. 1–15, 2014.
[13] H. R. Patel and V. A. Shah, “Fault Tolerant Control Systems: A Passive Approaches for Single Tank Level Control System,” i-manager’s Journal on Instrumentation and Control Engineering, vol. 6, no. 01, pp. 11-18, 2018.
[14] P. Li, and G. Yang, “An adaptive fuzzy design for fault-tolerant control of MIMO nonlinear uncertain systems,” Journal of Control Theory and Applications, vol. 9, no. 2, pp. 244-250, 2011.
[15] P. Li, and G. Yang, “Backstepping adaptive fuzzy control of uncertain nonlinear systems against actuator faults,” Journal of Control Theory and Applications, vol. 7, no. 3, pp. 248-256, 2009.
[16] P. Li, and G. Yang, “Adaptive fuzzy control of unknown nonlinear systems with actuator failures for robust output tracking,” in Proc. IEEE, American Control Conference (ACC 2008), Seattle, WA, USA, 2008, pp. 4898-4903.
[17] D. Ye, and G. Yang, “Adaptive Fault-Tolerant Tracking Control against Actuator Faults with Application to Flight Control,” IEEE Transactions on Control Systems Technology, vol. 14, no. 6, pp.1088-1096, 2006.
[18] G. Yang and D. Ye, “Adaptive fault-tolerant H∞ control via state feedback for linear systems against actuator faults,” in Proc. IEEE, 45th IEEE Conference on Decision and Control, San Diego, CA, USA, 2006, pp. 3530-3535.
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[20] J. D. Stefanovski, “Passive fault tolerant perfect tracking with additive faults,” Automatica, vol 87, pp. 432-436, 2018.
[21] X. Chun-Hua, and Y. Guang-Hong, “Decentralized adaptive fault-tolerant control for large-scale systems with external disturbances and actuator faults,” Automatica, vol. 85, pp. 83–90, 2017.
[22] H. R. Patel and V. A. Shah, “Fuzzy logic based passive fault tolerant control strategy for a single-tank system with system fault and process disturbances,” in Proc. IEEE, 5th International Conference on Electrical and Electronic Engineering (ICEEE), 3-5 May, Istanbul, Turkey,2018, pp. 257-262.
[23] N. Parikh, S. Rathore, R. Misra, and A. Markana, “A comparison between NMPC and LQG for the level control of three tank interacting system,” in Proc. IEEE, Indian Control Conference, ICC, Guwahati, India, pp. 200-205., 2017.
[24] L. Mendonca, J. M. Sousa, and J. M. Sa da Costa, “Fault accommodation of an experimental three tank system using fuzzy predictive control,” in Proc. IEEE, International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence), Hong Kong, China, 2008, pp. 1619–1625.
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[27] H. R. Patel and V. A. Shah, “A Framework for Fault-tolerant Control for an Interacting and Non-interacting Level Control System using AI,” in Proc. SCITEPRESS, 15th International Conference on Informatics in Control, Automation and Robotics-Volume-1,Porto, Portugal, SCITEPRESS, 2018, pp. 180-190.
[28] D. Jianqiu and H. Cui, “The Smith-PID Control of Three-Tank-System Based on Fuzzy Theory,” Journal of Computers, vol. 6, no. 3, pp. 514-523, 2011.
[29] L. Mastacan, and C. Dosoftei, “Level Fuzzy Control of Three-Tank System,” International Conference on Control Systems and Computer Science (CSCS), pp 30-35, 2013.
[30] M. Sarailooa, Rahmanib. Z, B Rezaieb. “A novel model predictive control scheme based on Bees algorithm in a class of nonlinear systems: Application to a three tank system,” Neurocomputing, vol. 152, pp. 294-304, 2015.
[31] H. Sahu, and R. Ayyagari, “Interval Fuzzy Type-II Controller for the Level Control of a Three Tank System,” IFAC-PapersOnLine, vol. 49, no. 1, pp. 561-566, 2016.
[32] K. Srinivasan, J. Devassy, S. Dhanapal, “Level control of three-tank system using intelligent techniques,” International Journal of Image Mining, vol. 2, no. 3-4, pp. 318-328, 2017.
[33] Castillo, O., Cervantes, L., Melin, P. et al. “A new approach to control of multivariable systems through a hierarchical aggregation of fuzzy controllers,” Granular Computing, pp. 1-13, 2018.