A Novel Method for Optimal Sensor and Actuator Placements: The “Infinite Value Algorithm”
Subject Areas : Electrical Engineering
Mahdi
Zavar
1
(Department of Electrical Engineering, Faculty of Engineering, Golestan University, Gorgan, Iran)
Mohammad
Shahraeini
2
(Department of Electrical Engineering, Golestan University, Gorgan, Iran)
Alireza
Safa
3
(Department of Electrical Engineering, Golestan University, Gorgan, Iran)
Niki
Manouchehri
4
(Department of Electrical Engineering,, Golestan University, Gorgan, Iran)
Keywords: Infinite value algorithm, Sensor placement, Actuator placement, Observability, Controllability.,
Abstract :
Cyber-physical systems rely heavily on the functionality of sensors and actuators to operate effectively. Sensors transfer measurements from the physical part to the control and cyber part and while actuators that play the role of applying control signals to the physical part. The placement of sensors and actuators is an important issue for ensuring system’s observability and controllability. This placement should be done in way that the system remains controllable and observable with fewest number of sensors and actuators.. Minimizing the number of sensors and actuators has a significant effect on cost and energy reduction. In this study, a new approach is introduced based on the existing paths and non-existent paths between the states of a system. In the proposed approach, the non-existent paths are defined as infinite paths. The best nodes are selected as the location of sensors and actuators based on the infinite paths and their numbers.The numerical simulations illustrate that the Infinite Value Algorithm has performed better in the placements in this way that it has consumed the unique solution in less time compared the Genetic Algorithms.
[1] Bakirtzis, Georgios, Christina Vasilakopoulou, and Cody H Fleming. "Compositional Cyber-Physical Systems Modeling." arXiv preprint arXiv:2101.10484 (2021).
[2] Ho, Nicholas, Pooi-Mun Wong, Ngoc-Son Hoang, Dun-Kai Koh, Matthew Chin Heng Chua, and Chee-Kong Chui. "Cps-Based Manufacturing Workcell for the Production of Hybrid Medical Devices." Journal of Ambient Intelligence and Humanized Computing 12 (2021): 10865-79.
[3] Tavčar, Jože, Jože Duhovnik, and Imre Horváth. "From Validation of Medical Devices Towards Validation of Adaptive Cyber-Physical Systems." Journal of Integrated Design and Process Science 23, no. 1 (2019): 37-59.
[4] Castillo-Martínez, Diego Hilario, Adolfo Josué Rodríguez-Rodríguez, Adrian Soto, Alberto Berrueta, David Tomás Vargas-Requena, Ignacio R Matias, Pablo Sanchis, Alfredo Ursúa, and Wenceslao Eduardo Rodríguez-Rodríguez. "Design and on-Field Validation of an Embedded System for Monitoring Second-Life Electric Vehicle Lithium-Ion Batteries." Sensors 22, no. 17 (2022): 6376.
[5] Hu, Zhongxu, Shanhe Lou, Yang Xing, Xiao Wang, Dongpu Cao, and Chen Lv. "Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles." IEEE Transactions on Intelligent Vehicles (2022).
[6] Li, Ning, Haiyi Sun, Xin Jing, and Zhongtang Chen. "Dynamic Modeling and Aperiodically Intermittent Strategy for Adaptive Finite-Time Synchronization Control of the Multi-Weighted Complex Transportation Networks with Multiple Delays." Chinese Physics B 30, no. 9 (2021): 090507.
[7] Wu, Jianping, and Dongping Fang. "Role of Cps in Smart Cities." Cyber-Physical Systems in the Built Environment (2020): 255-72.
[8] Cui, Yi, Feifei Bai, Tapan Saha, and Jalil Yaghoobi. "Authenticating Source Information of Distribution Synchrophasors at Intra-State Locations for Cyber-Physical Resilient Power Networks." International Journal of Electrical Power & Energy Systems 139 (2022): 108009.
[9] Khan, Izhar Ahmed, Dechang Pi, Nasrullah Khan, Zaheer Ullah Khan, Yasir Hussain, Asif Nawaz, and Farman Ali. "A Privacy-Conserving Framework Based Intrusion Detection Method for Detecting and Recognizing Malicious Behaviours in Cyber-Physical Power Networks." Applied Intelligence (2021): 1-16.
[10] Cui, Xinyue. "Cyber-Physical System (Cps) Architecture for Real-Time Water Sustainability Management in Manufacturing Industry." Procedia CIRP 99 (2021): 543-48.
[11] Liu, Yongtuo, Sara Magliacane, Miltiadis Kofinas, and Efstratios Gavves. "Graph Switching Dynamical Systems." arXiv preprint arXiv:2306.00370 (2023).
[12] Vazirgiannis, Michalis. "Gnns and Graph Generative Models for Biomedical Applications." Proceedings of the ACM Web Conference 2023, Austin, TX, USA, Association for Computing Machinery, 2023.
[13] Adamos, Konstantinos, George Stergiopoulos, Michalis Karamousadakis, and Dimitris Gritzalis. "Enhancing Attack Resilience of Cyber-Physical Systems through State Dependency Graph Models." International Journal of Information Security (2023): 1-12.
[14] Bodkhe, Umesh, Dhyey Mehta, Sudeep Tanwar, Pronaya Bhattacharya, Pradeep Kumar Singh, and Wei-Chiang Hong. "A Survey on Decentralized Consensus Mechanisms for Cyber Physical Systems." IEEE Access 8 (2020): 54371-401.
[15] Mittal, Saurabh, and Andreas Tolk. Complexity Challenges in Cyber Physical Systems: Using Modeling and Simulation (M&S) to Support Intelligence, Adaptation and Autonomy. John Wiley & Sons, 2019.
[16] Abbas, Arbab Waseem, and Safdar Nawaz Khan Marwat. "Scalable Emulated Framework for Iot Devices in Smart Logistics Based Cyber-Physical Systems: Bonded Coverage and Connectivity Analysis." IEEE Access 8 (2020): 138350-72.
[17] Fataliyev, Tahmasib Kh, and Shakir A Mehdiyev. "Integration of Cyber-Physical Systems in E-Science Environment: State-of-the-Art, Problems and Effective Solutions." International Journal of Modern Education and Computer Science 11, no. 9 (2019): 35.
[18] Colabianchi, Silvia, Francesco Costantino, Giulio Di Gravio, Fabio Nonino, and Riccardo Patriarca. "Discussing Resilience in the Context of Cyber Physical Systems." Computers & Industrial Engineering 160 (2021): 107534.
[19] Leitold, Dániel, Ágnes Vathy-Fogarassy, and János Abonyi. "Network-Based Observability and Controllability Analysis of Dynamical Systems: The Nocad Toolbox." F1000Research 8 (2019).
[20] Civera, Marco, Marica Leonarda Pecorelli, Rosario Ceravolo, Cecilia Surace, and Luca Zanotti Fragonara. "A Multi‐Objective Genetic Algorithm Strategy for Robust Optimal Sensor Placement." Computer‐Aided Civil and Infrastructure Engineering 36, no. 9 (2021): 1185-202.
[21] Dhuri, KD, and P Seshu. "Multi-Objective Optimization of Piezo Actuator Placement and Sizing Using Genetic Algorithm." Journal of sound and vibration 323, no. 3-5 (2009): 495-514.
[22] Peng, Yuhuai, Alireza Jolfaei, Qiaozhi Hua, Wen-Long Shang, and Keping Yu. "Real-Time Transmission Optimization for Edge Computing in Industrial Cyber-Physical Systems." IEEE Transactions on Industrial Informatics 18, no. 12 (2022): 9292-301.
[23] Zhou, Xin, Xiaodong Gou, Tingting Huang, and Shunkun Yang. "Review on Testing of Cyber Physical Systems: Methods and Testbeds." IEEE Access 6 (2018): 52179-94.
[24] Tutte, William Thomas. Graph Theory. Vol. 21: Cambridge university press, 2001.
[25] Shahraeini, Mohammad, Panayiotis Kotzanikolaou, and Mehrab Nasrolahi. "Communication Resilience for Smart Grids Based on Dependence Graphs and Eigenspectral Analysis." IEEE Systems Journal 16, no. 4 (2022): 6558-68.
[26] Bhunia, Pintu, Santanu Bag, and Kallol Paul. "Bounds for Eigenvalues of the Adjacency Matrix of a Graph." Journal of Interdisciplinary Mathematics 22, no. 4 (2019): 415-31.
[27] Shahraeini, Mohammad, Shahla Khormali, and Ahad Alvandi. "Optimal Pmu Placement Considering Reliability of Measurement System in Smart Grids." Paper presented at the 2022 12th International Conference on Computer and Knowledge Engineering (ICCKE), 2022.
[28] Xie, Jun, Qiguang Miao, Ruyi Liu, Wentian Xin, Lei Tang, Sheng Zhong, and Xuesong Gao. "Attention Adjacency Matrix Based Graph Convolutional Networks for Skeleton-Based Action Recognition." Neurocomputing 440 (2021): 230-39.
[29] Jungers, Raphael M, Atreyee Kundu, and WPMH Heemels. "Observability and Controllability Analysis of Linear Systems Subject to Data Losses." IEEE Transactions on Automatic Control 63, no. 10 (2017): 3361-76.
[30] Yan, Jiayuan, Bin Hu, Zhi-Hong Guan, Tao Li, and Ding-Xue Zhang. "On Controllability and Observability of a Class of Fractional-Order Switched Systems with Impulse." Nonlinear Analysis: Hybrid Systems 50 (2023): 101378.
[31] Chen, Chen, Ruiyue Peng, Lei Ying, and Hanghang Tong. "Fast Connectivity Minimization on Large-Scale Networks." ACM Transactions on Knowledge Discovery from Data (TKDD) 15, no. 3 (2021): 1-25.
[32] Sun, Wen, Junxia Guan, Jinhu Lü, Zhigang Zheng, Xinghuo Yu, and Shihua Chen. "Synchronization of the Networked System with Continuous and Impulsive Hybrid Communications." IEEE Transactions on Neural Networks and Learning Systems 31, no. 3 (2019): 960-71.
[33] Bopardikar, Shaunak D. "A Randomized Approach to Sensor Placement with Observability Assurance." Automatica 123 (2021): 109340. https://doi.org/https://doi.org/10.1016/j.automatica.2020.109340.
[34] Manohar, Krithika, J Nathan Kutz, and Steven L Brunton. "Optimal Sensor and Actuator Selection Using Balanced Model Reduction." IEEE Transactions on Automatic Control 67, no. 4 (2021): 2108-15. https://doi.org/https://doi.org/10.1109/TAC.2021.3082502.
[35] Takahashi, Shun, Yasuo Sasaki, Takayuki Nagata, Keigo Yamada, Kumi Nakai, Yuji Saito, and Taku Nonomura. "Sensor Selection by Greedy Method for Linear Dynamical Systems: Comparative Study on Fisher-Information-Matrix, Observability-Gramian and Kalman-Filter-Based Indices." IEEE Access (2023). https://doi.org/https://doi.org/10.1109/ACCESS.2023.3291415.
[36] Yamada, Keigo, Yasuo Sasaki, Takayuki Nagata, Kumi Nakai, Daisuke Tsubakino, and Taku Nonomura. "Efficient Sensor Node Selection for Observability Gramian Optimization." Sensors 23, no. 13 (2023): 5961. https://doi.org/https://doi.org/10.3390/s23135961.
[37] Shirajuddin, Talhah Mohamad, Nur Shazwani Muhammad, and Jazuri Abdullah. "Optimization Problems in Water Distribution Systems Using Non-Dominated Sorting Genetic Algorithm Ii: An Overview." Ain Shams Engineering Journal 14, no. 4 (2023): 101932.
[38]Shahraeini, Mohammad. “Modified Erdős–Rényi Random Graph Model for Generating Synthetic Power Grids.” IEEE Systems Journal. Institute of Electrical and Electronics Engineers (IEEE), 2023. https://doi.org/10.1109/jsyst.2023.3339664.
