Konsep Dasar Sistem Kendali dalam Perspektif Rekayasa Sistem

Authors

  • Sulfikar Universitas Muhammadiyah Sinjai
  • Hasrul Bakri Universitas Negeri Makassar
  • Nur Alam Fajar Universitas Negeri Jakarta
  • Irfan Universitas Muhammadiyah Sinjai

DOI:

https://doi.org/10.47134/jte.v3i1.5632

Keywords:

Sistem Kendali, Rekayasa Sistem, Sistem Dinamis, Integrasi Teknologi, Kontrol Adaptif

Abstract

Penelitian ini bertujuan untuk menganalisis konsep dasar sistem kendali dalam perspektif rekayasa sistem serta mengkaji perannya dalam pengelolaan sistem teknologi modern yang kompleks. Penelitian menggunakan pendekatan kualitatif dengan metode deskriptif melalui studi pustaka terhadap berbagai sumber literatur akademik, termasuk buku ilmiah dan artikel jurnal yang relevan. Proses analisis dilakukan melalui identifikasi tema, reduksi data, kategorisasi konsep, serta penarikan kesimpulan secara induktif guna memperoleh pemahaman yang komprehensif. Hasil penelitian menunjukkan bahwa sistem kendali memiliki peran krusial dalam mengelola sistem dinamis melalui mekanisme umpan balik, stabilitas, dan optimasi kinerja. Dalam konteks rekayasa sistem, sistem kendali berfungsi sebagai elemen integratif yang memastikan koordinasi antar subsistem dalam lingkungan yang kompleks dan berubah. Perkembangan teknologi mutakhir juga mendorong integrasi sistem kendali dengan pendekatan seperti pembelajaran mesin, sistem siber-fisik, dan digital twin, yang memungkinkan peningkatan kemampuan adaptasi, efisiensi, serta keandalan sistem. Implikasi penelitian ini menegaskan bahwa pemahaman konseptual dan integratif terhadap sistem kendali sangat penting dalam pengembangan sistem teknologi modern, khususnya pada bidang robotika, energi, dan industri cerdas. Selain itu, integrasi teknologi digital dalam sistem kendali membuka peluang bagi inovasi lanjutan dalam pengembangan sistem yang lebih otonom dan responsif terhadap perubahan lingkungan.

References

Abraham, D., & Padmakumari, P. (2024). A methodological framework for descriptive phenomenological research. Western Journal of Nursing Research. https://doi.org/10.1177/01939459241308071

Baetica, A. A., Westbrook, A. M., & El-Samad, H. (2019). Control theoretical concepts for synthetic and systems biology. Current Opinion in Systems Biology. https://doi.org/10.1016/J.COISB.2019.02.010

Baillie, J. (2019). Commentary: An overview of the qualitative descriptive design within nursing research. Journal of Research in Nursing. https://doi.org/10.1177/1744987119881056

Balaci, A. T., & Suh, E. S. (2024). Systematic approach to a government led technology roadmap for future ready adaptive traffic signal control systems. Systems Engineering. https://doi.org/10.1002/sys.21772

Bandaranayake, P. (2024). Application of grounded theory methodology in library and information science research: An overview. Sri Lanka Library Review. https://doi.org/10.4038/sllr.v38i2.70

Belotto, M. (2018). Data analysis methods for qualitative research: Managing the challenges of coding, interrater reliability, and thematic analysis. The Qualitative Report. https://doi.org/10.46743/2160-3715/2018.3492

Bingham, A. (2023). From data management to actionable findings: A five phase process of qualitative data analysis. International Journal of Qualitative Methods. https://doi.org/10.1177/16094069231183620

Doyle, L., McCabe, C., Keogh, B., Brady, A., & McCann, M. (2019). An overview of the qualitative descriptive design within nursing research. Journal of Research in Nursing. https://doi.org/10.1177/1744987119880234

Fife, S., & Gossner, J. (2024). Deductive qualitative analysis: Evaluating, expanding, and refining theory. International Journal of Qualitative Methods. https://doi.org/10.1177/16094069241244856

Granikov, V., Hong, Q., Crist, E., & Pluye, P. (2020). Mixed methods research in library and information science: A methodological review. Library & Information Science Research. https://doi.org/10.1016/j.lisr.2020.101003

Jiang, Y., Wu, S., Ma, R., Liu, M., Luo, H., & Kaynak, O. (2023). Monitoring and defense of industrial cyber physical systems under typical attacks: From a systems and control perspective. IEEE Transactions on Industrial Cyber Physical Systems. https://doi.org/10.1109/TICPS.2023.3317237

Jimenez, S., Berbegal Mirabent, J., & De La Torre, R. (2024). How do university libraries contribute to the research process. The Journal of Academic Librarianship. https://doi.org/10.1016/j.acalib.2024.102930

Kalpokaite, N., & Radivojevic, I. (2018). Demystifying qualitative data analysis for novice qualitative researchers. The Qualitative Report. https://doi.org/10.46743/2160-3715/2019.4120

Lee, J. H., Shin, J., & Realff, M. (2017). Machine learning: Overview of the recent progresses and implications for the process systems engineering field. Computers and Chemical Engineering. https://doi.org/10.1016/j.compchemeng.2017.10.008

Li, B., Wang, S., Guo, Z., Zhu, S., Huang, J., Sun, J., Wen, G., & Wen, S. (2025). Safe control framework of multi agent systems from a performance enhancement perspective. IEEE Transactions on Automation Science and Engineering. https://doi.org/10.1109/TASE.2024.3466791

Liu, Y., Lyu, C., Bai, F., Parishwad, O., & Li, Y. (2023). The role of intelligent technology in the development of urban air mobility systems. Fundamental Research. https://doi.org/10.1016/j.fmre.2023.08.006

Marshall, J. A., Sun, W., & L’Afflitto, A. (2021). A survey of guidance navigation and control systems for autonomous multi rotor small unmanned aerial systems. Annual Reviews in Control. https://doi.org/10.1016/j.arcontrol.2021.10.013

Martinelli, A., Gargiani, M., Draskovic, M., & Lygeros, J. (2022). Data-driven optimal control of affine systems: A linear programming perspective. IEEE Control Systems Letters. https://doi.org/10.1109/LCSYS.2022.3180898

Nghiem, T. X., Drgona, J., Jones, C. N., Nagy, Z., Schwan, R., Dey, B., Chakrabarty, A., Di Cairano, S., Paulson, J. A., Carron, A., Zeilinger, M. N., Cortez, W. S., & Vrabie, D. (2023). Physics informed machine learning for modeling and control of dynamical systems. https://doi.org/10.23919/acc55779.2023.10155901

Ögren, P., & Sprague, C. I. (2021). Behavior trees in robot control systems. Annual Review of Control, Robotics, and Autonomous Systems. https://doi.org/10.1146/annurev-control-042920-095314

Pan, G., Ou, R., & Faulwasser, T. (2021). On a stochastic fundamental lemma and its use for data-driven optimal control. IEEE Transactions on Automatic Control. https://doi.org/10.1109/TAC.2022.3232442

Pileggi, P., Lazovik, E., Broekhuijsen, J., Borth, M., & Verriet, J. (2020). Lifecycle governance for effective digital twins: A joint systems engineering and IT perspective. IEEE Systems Conference. https://doi.org/10.1109/SysCon47679.2020.9275662

Porras Vázquez, A., & Romero Pérez, J. (2018). A new methodology for facilitating the design of safety related parts of control systems in machines according to ISO 13849: 2006 standard. Reliability Engineering and System Safety. https://doi.org/10.1016/j.ress.2018.02.018

Pratt, M. (2025). On the evolution of qualitative methods in organizational research. Annual Review of Organizational Psychology and Organizational Behavior. https://doi.org/10.1146/annurev-orgpsych-111722-032953

Ringwood, J. V., Mérigaud, A., Faedo, N., & Fusco, F. (2020). An analytical and numerical sensitivity and robustness analysis of wave energy control systems. IEEE Transactions on Control Systems Technology. https://doi.org/10.1109/TCST.2019.2909719

Sivaramakrishnan, K., Puliyanda, A., Tefera, D., Ganesh, A., & Thirumalaivasan, S. (2019). A perspective on the impact of process systems engineering on reaction engineering. Industrial & Engineering Chemistry Research. https://doi.org/10.1021/ACS.IECR.9B00280

Togia, A., & Malliari, A. (2017). Research methods in library and information science. https://doi.org/10.5772/intechopen.68749

Tsiamis, A., Ziemann, I. M., Matni, N., & Pappas, G. (2022). Statistical learning theory for control: A finite-sample perspective. IEEE Control Systems. https://doi.org/10.1109/MCS.2023.3310345

Vila Henninger, L., Dupuy, C., Van Ingelgom, V., Caprioli, M., Teuber, F., Pennetreau, D., Bussi, M., & Gall, C. (2022). Abductive coding: Theory building and qualitative reanalysis. Sociological Methods and Research. https://doi.org/10.1177/00491241211067508

Wang, H., Li, H., Tang, C., Zhang, X., & Wen, X. (2019). Unified design approach for systems engineering by integrating model-based systems design with axiomatic design. Systems Engineering. https://doi.org/10.1002/sys.21505

Zhang, R., & Guo, L. (2019). Controllability of Nash equilibrium in game based control systems. IEEE Transactions on Automatic Control. https://doi.org/10.1109/TAC.2019.2893150

Downloads

Published

2026-04-06

How to Cite

Sulfikar, Bakri, H., Fajar, N., & Irfan. (2026). Konsep Dasar Sistem Kendali dalam Perspektif Rekayasa Sistem. Journal of Electrical Engineering, 3(1), 11. https://doi.org/10.47134/jte.v3i1.5632

Issue

Section

Articles

Similar Articles

1 2 > >> 

You may also start an advanced similarity search for this article.